Rozprawy doktorskie: „Mobility prediction”

1

Dong, Fang. "Moving Object Trajectory Based Spatio-Temporal Mobility Prediction". Thesis, KTH, Geodesi och geoinformatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-99033.

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Bergh, Andre E. "Prediction assisted fast handovers for seamless IP mobility". Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/5248.

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Word processed copy.
Includes bibliographical references (leaves 94-98).
This research investigates the techniques used to improve the standard Mobile IP handover process and provide proactivity in network mobility management. Numerous fast handover proposals in the literature have recently adopted a cross-layer approach to enhance movement detection functionality and make terminal mobility more seamless. Such fast handover protocols are dependent on an anticipated link-layer trigger or pre-trigger to perform pre-handover service establishment operations. This research identifies the practical difficulties involved in implementing this type of trigger and proposes an alternative solution that integrates the concept of mobility prediction into a reactive fast handover scheme.

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Venkatachalaiah, Suresh, i suresh@catt rmit edu au. "Mobility prediction and Multicasting in Wireless Networks: Performance and Analysis". RMIT University. Electrical and Computer Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070301.130037.

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Handoff is a call handling mechanism that is invoked when a mobile node moves from one cell to another. Such movement may lead to degradation in performance for wireless networks as a result of packet losses. A promising technique proposed in this thesis is to apply multicasting techniques aided by mobility prediction in order to improve handoff performance. In this thesis, we present a method that uses a Grey model for mobility prediction and a fuzzy logic controller that has been fine-tuned using evolutionary algorithms in order to improve prediction accuracy. We also compare the self-tuning algorithm with two evolutionary algorithms in terms of accuracy and their convergence times. Our proposed method takes into account signal strengths from the base stations and predicts the signal strength of the next candidate base station in order to provide improved handover performance. The primary decision for mobility prediction is the accurate prediction of signal strengths obtained from the base stations and remove any unwanted errors in the prediction using suitable optimisation techniques. Furthermore, the model includes the procedures of fine-tuning the predicted data using fuzzy parameters. We also propose suitable multicasting algorithms to minimise the reservation of overall network resource requirements during handoff with the mobility prediction information. To be able to efficiently solve the problem, the situation is modelled using a multicast tree that is defined to maintain connectivity with the mobile node, whilst ensuring bandwidth guarantees and a minimum hop-count. In this approach, we have tried to solve the problem by balancing two objectives through putting a weight on each of two costs. We provide a detailed description of an algorithm to implement join and prune mechanisms, which will help to build an optimal multicast tree with QoS requirements during handoff as well as incorporating dynamic changes in the positions of mobile nodes. An analysis of how mobility prediction helps in the selection of potential Access Routers (AR) with QoS requirements - which affects the multicast group size and bandwidth cost of the multicast tree -- is presented. The proposed technique tries to minimise the number of multicast tree join and prune operations. Our results show that the expected size of the multicast group increases linearly with an increase in the number of selected destination AR's for multicast during handoff. We observe that the expected number of joins and prunes from the multicast tree increases with group size. A special simulation model was developed to demonstrate both homogeneous and heterogeneous handoff which is an emerging requirement for fourth generation mobile networks. The model incorporates our mobility prediction model for heterogeneous handoff between the Wireless LAN and a cellular network. The results presented in this thesis for mobility prediction, multicasting techniques and heterogeneous handoff include proposed algorithms and models which aid in the understanding, analysing and reducing of overheads during handoff.

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Baumann, Paul. "Human Mobility and Application Usage Prediction Algorithms for Mobile Devices". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-212427.

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Mobile devices such as smartphones and smart watches are ubiquitous companions of humans’ daily life. Since 2014, there are more mobile devices on Earth than humans. Mobile applications utilize sensors and actuators of these devices to support individuals in their daily life. In particular, 24% of the Android applications leverage users’ mobility data. For instance, this data allows applications to understand which places an individual typically visits. This allows providing her with transportation information, location-based advertisements, or to enable smart home heating systems. These and similar scenarios require the possibility to access the Internet from everywhere and at any time. To realize these scenarios 83% of the applications available in the Android Play Store require the Internet to operate properly and therefore access it from everywhere and at any time. Mobile applications such as Google Now or Apple Siri utilize human mobility data to anticipate where a user will go next or which information she is likely to access en route to her destination. However, predicting human mobility is a challenging task. Existing mobility prediction solutions are typically optimized a priori for a particular application scenario and mobility prediction task. There is no approach that allows for automatically composing a mobility prediction solution depending on the underlying prediction task and other parameters. This approach is required to allow mobile devices to support a plethora of mobile applications running on them, while each of the applications support its users by leveraging mobility predictions in a distinct application scenario. Mobile applications rely strongly on the availability of the Internet to work properly. However, mobile cellular network providers are struggling to provide necessary cellular resources. Mobile applications generate a monthly average mobile traffic volume that ranged between 1 GB in Asia and 3.7 GB in North America in 2015. The Ericsson Mobility Report Q1 2016 predicts that by the end of 2021 this mobile traffic volume will experience a 12-fold increase. The consequences are higher costs for both providers and consumers and a reduced quality of service due to congested mobile cellular networks. Several countermeasures can be applied to cope with these problems. For instance, mobile applications apply caching strategies to prefetch application content by predicting which applications will be used next. However, existing solutions suffer from two major shortcomings. They either (1) do not incorporate traffic volume information into their prefetching decisions and thus generate a substantial amount of cellular traffic or (2) require a modification of mobile application code. In this thesis, we present novel human mobility and application usage prediction algorithms for mobile devices. These two major contributions address the aforementioned problems of (1) selecting a human mobility prediction model and (2) prefetching of mobile application content to reduce cellular traffic. First, we address the selection of human mobility prediction models. We report on an extensive analysis of the influence of temporal, spatial, and phone context data on the performance of mobility prediction algorithms. Building upon our analysis results, we present (1) SELECTOR – a novel algorithm for selecting individual human mobility prediction models and (2) MAJOR – an ensemble learning approach for human mobility prediction. Furthermore, we introduce population mobility models and demonstrate their practical applicability. In particular, we analyze techniques that focus on detection of wrong human mobility predictions. Among these techniques, an ensemble learning algorithm, called LOTUS, is designed and evaluated. Second, we present EBC – a novel algorithm for prefetching mobile application content. EBC’s goal is to reduce cellular traffic consumption to improve application content freshness. With respect to existing solutions, EBC presents novel techniques (1) to incorporate different strategies for prefetching mobile applications depending on the available network type and (2) to incorporate application traffic volume predictions into the prefetching decisions. EBC also achieves a reduction in application launch time to the cost of a negligible increase in energy consumption. Developing human mobility and application usage prediction algorithms requires access to human mobility and application usage data. To this end, we leverage in this thesis three publicly available data set. Furthermore, we address the shortcomings of these data sets, namely, (1) the lack of ground-truth mobility data and (2) the lack of human mobility data at short-term events like conferences. We contribute with JK2013 and UbiComp Data Collection Campaign (UbiDCC) two human mobility data sets that address these shortcomings. We also develop and make publicly available a mobile application called LOCATOR, which was used to collect our data sets. In summary, the contributions of this thesis provide a step further towards supporting mobile applications and their users. With SELECTOR, we contribute an algorithm that allows optimizing the quality of human mobility predictions by appropriately selecting parameters. To reduce the cellular traffic footprint of mobile applications, we contribute with EBC a novel approach for prefetching of mobile application content by leveraging application usage predictions. Furthermore, we provide insights about how and to what extent wrong and uncertain human mobility predictions can be detected. Lastly, with our mobile application LOCATOR and two human mobility data sets, we contribute practical tools for researchers in the human mobility prediction domain.

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5

Chen, Guangshuo. "Human Habits Investigation : from Mobility Reconstruction to Mobile Traffic Prediction". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLX026/document.

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La capacité à prévoir les activités humaines a des implications essentielles dans de nombreux aspects des réseaux cellulaires. En particulier, la haute disponibilité de la prédiction de la mobilité peut permettre différents scénarios d'application; une meilleure compréhension de la demande de trafic de données mobiles peut aider à améliorer la conception de solutions pour l'équilibrage de la charge du réseau. Bien que de nombreux chercheurs aient étudié le sujet de la prédiction de la mobilité humaine, il y a eu peu de discussions sur l'anticipation du trafic de données mobiles dans les réseaux cellulaires.Pour comprendre la mobilité humaine, les ensembles de données de téléphones mobiles, consistant en des enregistrements de données de taxation (CDR), constituent un choix pratique d'empreintes humaines. Comme le déploiement du réseau cellulaire est très irrégulier et que les fréquences d'interaction sont généralement faibles, les données CDR sont souvent caractérisées par une parcimonie spatio-temporelle qui, à son tour, peut biaiser les analyses de mobilité basées sur de telles données et provoquer la perte de trajectoires individuelles.Dans cette thèse, nous présentons de nouvelles solutions de reconstruction de trajectoires individuelles et de prédiction de trafic de données mobiles individuelles. Nos contributions abordent les problèmes de (1) surmonter l'incomplétude des informations de mobilité pour l'utilisation des ensembles de données de téléphonie mobile et (2) prédire la future demande de trafic de données mobiles pour le support des applications de gestion de réseau.Premièrement, nous nous concentrons sur la faille de l'information sur la mobilité dans les ensembles de données de téléphones mobiles. Nous rapportons une analyse en profondeur de son effet sur la mesure des caractéristiques de mobilité individuelles et l'exhaustivité des trajectoires individuelles. En particulier, (1) nous fournissons une confirmation des résultats antérieurs concernant les biais dans les mesures de mobilité causées par la rareté temporelle de la CDR; (2) nous évaluons le décalage géographique provoqué par la cartographie des emplacements des utilisateurs vers les tours cellulaires et révélons le biais causé par la rareté spatiale de la CDR; (3) nous fournissons une estimation empirique de l'exhaustivité des données des trajectoires CDR individuelles. (4) nous proposons de nouvelles solutions de complétion CDR pour reconstruire incomplète. Nos solutions tirent parti de la nature des modèles de mouvements humains répétitifs et des techniques d'inférence de données de pointe et surpassent les approches précédentes illustrées par des simulations axées sur les données.Deuxièmement, nous abordons la prédiction des demandes de trafic de données mobiles générées par les abonnés individuels du réseau mobile. Sur la base de trajectoires complétées par nos solutions développées et nos historiques de consommation de données extraites d'un ensemble de données de téléphonie mobile à grande échelle, (1) nous étudions les limites de prévisibilité en mesurant la prévisibilité maximale que tout algorithme peut atteindre. les approches de prédiction du trafic de données mobiles qui utilisent les résultats de l'analyse théorique de la prévisibilité. Notre analyse théorique montre qu'il est théoriquement possible d'anticiper la demande individuelle avec une précision typique de 75% malgré l'hétérogénéité des utilisateurs et avec une précision améliorée de 80% en utilisant la prédiction conjointe avec des informations de mobilité. Notre pratique basée sur des techniques d'apprentissage automatique peut atteindre une précision typique de 65% et avoir un degré d'amélioration de 1% à 5% en considérant les déplacements individuels.En résumé, les contributions mentionnées ci-dessus vont dans le sens de l'utilisation des ensembles de données de téléphonie mobile et de la gestion des opérateurs de réseau et de leurs abonnés
The understanding of human behaviors is a central question in multi-disciplinary research and has contributed to a wide range of applications. The ability to foresee human activities has essential implications in many aspects of cellular networks. In particular, the high availability of mobility prediction can enable various application scenarios such as location-based recommendation, home automation, and location-related data dissemination; the better understanding of mobile data traffic demand can help to improve the design of solutions for network load balancing, aiming at improving the quality of Internet-based mobile services. Although a large and growing body of literature has investigated the topic of predicting human mobility, there has been little discussion in anticipating mobile data traffic in cellular networks, especially in spatiotemporal view of individuals.For understanding human mobility, mobile phone datasets, consisting of Charging Data Records (CDRs), are a practical choice of human footprints because of the large-scale user populations and the vast diversity of individual movement patterns. The accuracy of mobility information granted by CDR depends on the network infrastructure and the frequency of user communication events. As cellular network deployment is highly irregular and interaction frequencies are typically low, CDR data is often characterized by spatial and temporal sparsity, which, in turn, can bias mobility analyses based on such data and cause the loss of whereabouts in individual trajectories.In this thesis, we present novel solutions of the reconstruction of individual trajectories and the prediction of individual mobile data traffic. Our contributions address the problems of (1) overcoming the incompleteness of mobility information for the use of mobile phone datasets and (2) predicting future mobile data traffic demand for the support of network management applications.First, we focus on the flaw of mobility information in mobile phone datasets. We report on an in-depth analysis of its effect on the measurement of individual mobility features and the completeness of individual trajectories. In particular, (1) we provide a confirmation of previous findings regarding the biases in mobility measurements caused by the temporal sparsity of CDR; (2) we evaluate the geographical shift caused by the mapping of user locations to cell towers and reveal the bias caused by the spatial sparsity of CDR; (3) we provide an empirical estimation of the data completeness of individual CDR-based trajectories. (4) we propose novel solutions of CDR completion to reconstruct incomplete. Our solutions leverage the nature of repetitive human movement patterns and the state-of-the-art data inference techniques and outperform previous approaches shown by data-driven simulations.Second, we address the prediction of mobile data traffic demands generated by individual mobile network subscribers. Building on trajectories completed by our developed solutions and data consumption histories extracted from a large-scale mobile phone dataset, (1) we investigate the limits of predictability by measuring the maximum predictability that any algorithm has potential to achieve and (2) we propose practical mobile data traffic prediction approaches that utilize the findings of the theoretical predictability analysis. Our theoretical analysis shows that it is theoretically possible to anticipate the individual demand with a typical accuracy of 75% despite the heterogeneity of users and with an improved accuracy of 80% using joint prediction with mobility information. Our practical based on machine learning techniques can achieve a typical accuracy of 65% and have a 1%~5% degree of improvement by considering individual whereabouts.In summary, the contributions mentioned above provide a step further towards supporting the use of mobile phone datasets and the management of network operators and their subscribers

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Aljeri, Noura. "Efficient AI and Prediction Techniques for Smart 5G-enabled Vehicular Networks". Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41497.

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With the recent growth and wide availability of heterogeneous wireless access technologies, inter-vehicle communication systems are expected to culminate in integrating various wireless standards for the next generation of connected and autonomous vehicles. The role of 5G-enabled vehicular networks has become increasingly important, as current Internet clients and providers have urged robustness and effectiveness in digital services over wireless networks to cope with the latest advances in wireless mobile communication. However, to enable 5G wireless technologies' dense diversity, seamless and reliable wireless communication protocols need to be thoroughly investigated in vehicular networks. 5G-enabled vehicular networks applications and services such as routing, mobility management, and service discovery protocols can integrate mobility-based prediction techniques to elevate those applications' performance with various vehicles, applications, and network measurements. In this thesis, we propose a novel suite of 5G-enabled smart mobility prediction and management schemes and design a roadmap guide to mobility-based predictions for intelligent vehicular network applications and protocols. We present a thorough review and classification of vehicular network architectures and components, in addition to mobility management schemes, benchmarks advantages, and drawbacks. Moreover, multiple mobility-based schemes are proposed, in which vehicles' mobility is managed through the utilization of machine learning prediction and probability analysis techniques. We propose a novel predictive mobility management protocol that incorporates a new networks' infrastructure discovery and selection scheme. Next, we design an efficient handover trigger scheme based on time-series prediction and a novel online neural network-based next roadside unit prediction protocol for smart vehicular networks. Then, we propose an original adaptive predictive location management technique that utilizes vehicle movement projections to estimate the link lifetime between vehicles and infrastructure units, followed by an efficient movement-based collision detection scheme and infrastructure units localization strategy. Last but not least, the proposed techniques have been extensively evaluated and compared to several benchmark schemes with various networks' parameters and environments. Results showed the high potentials of empowering vehicular networks' mobility-based protocols with the vehicles' future projections and the prediction of the network's status.

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Pamuluri, Harihara Reddy. "Predicting User Mobility using Deep Learning Methods". Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19340.

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Context: The context of this thesis to predict user mobility using deep learning algorithms which can increase the quality of service for the users and reduce the cost of paging for telecom carriers. Objectives: This study first investigates to find the suitable deep learning algorithms that can be used to predict user mobility and then an experiment is performed with the chosen algorithms as a global model and individual model then evaluate the performance of algorithms. Methods: Firstly, a Literature review is used to find suitable deep learning algorithms and then based on finding an experiment is performed to evaluate the chosen deep learning algorithms. Results: Results from the literature review show that the RNN, LSTM, and variants of the LSTM are the suitable deep learning algorithms. The models are evaluated with metrics accuracy. The results from the experiment showed that the individual model gives better performance in predicting user mobility when compared to the global model. Conclusions: From the results obtained from the experiment, it can be concluded that the individual model is the technique of choice in predicting user mobility.

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Baumann, Paul [Verfasser]. "Human Mobility and Application Usage Prediction Algorithms for Mobile Devices / Paul Baumann". München : Verlag Dr. Hut, 2016. http://d-nb.info/1120763134/34.

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Senatore, Carmine. "Prediction of mobility, handling, and tractive efficiency of wheeled off-road vehicles". Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/37781.

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Our society is heavily and intrinsically dependent on energy transformation and usage. In a world scenario where resources are being depleted while their demand is increasing, it is crucial to optimize every process. During the last decade the concept of energy efficiency has become a leitmotif in several fields and has directly influenced our everyday life: from light bulbs to airplane turbines, there has been a general shift from pure performance to better efficiency. In this vein, we focus on the mobility and tractive efficiency of off-road vehicles. These vehicles are adopted in military, agriculture, construction, exploration, recreation, and mining applications and are intended to operate on soft, deformable terrain. The performance of off-road vehicles is deeply influenced by the tire-soil interaction mechanism. Soft soil can drastically reduce the traction performance of tires up to the point of making motion impossible. In this study, a tire model able to predict the performance of rigid wheels and flexible tires is developed. The model follows a semi-empirical approach for steady-state conditions and predicts basic features, such as the drawbar pull, the driving torque and the lateral force, as well as complex behaviors, such as the slip-sinkage phenomenon and the multi-pass effect. The tractive efficiency of different tire-soil configurations is simulated and discussed. To investigate the handling and the traction efficiency, the tire model is implemented into a four-wheel vehicle model. Several tire geometries, vehicle configurations (FWD, RWD, AWD), soil types, and terrain profiles are considered to evaluate the performance under different simulation scenarios. The simulation environment represents an effective tool to realistically analyze the impact of tire parameters (size, inflation pressure) and torque distribution on the energy efficiency. It is verified that larger tires and decreased inflation pressure generally provide better traction and energy efficiency (under steady-state working conditions). The torque distribution strategy between the axles deeply affects the traction and the efficiency: the two variables canâ t clearly be maximized at the same time and a trade-off has to be found.
Ph. D.

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Lui, Sin Ting Angela. "Enhancing stochastic mobility prediction models for robust planetary navigation on unstructured terrain". Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/12904.

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is challenging on unstructured terrain, and especially on deformable terrain, due to the complex interaction between the platform and its environment. In this thesis, we propose to enhance stochastic transition models for planning, where the outcomes of the control actions are learnt from experience and represented statistically using probability density functions. These transition models that capture control uncertainty are known as Stochastic Mobility Prediction Models (SMPM). Rovers may traverse a mixture of rigid and deformable terrain. However, current SMPMs are only capable of estimating one dimension of control uncertainty in rigid terrain. We propose to enhance the SMPM by Learning from Exteroception, a training method that relies on sample executions of motion primitives on representative terrain and the corresponding platform configurations collected along the executed path. This method enables the estimation of the outcome of future control actions on deformable terrain. The SMPM is further enhanced by using multi-output Gaussian process regression by simultaneously considering the correlation between multiple dimensions of uncertainty. The enhanced SMPM is integrated into a Markov decision process framework and dynamic programming is used to construct a control policy for navigation to a goal region in a terrain map. We consider both rigid and deformable terrain, consisting of uneven ground, small rocks, and non-traversable rocks. Over 300 experimental trials are reported using a planetary rover platform in a Mars-analogue environment. Our results demonstrate increased path safety and reliability by the improved traversal cost and actions executed; due to the SMPM improvement in predicting control action outcomes.

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Farzana, Fatema Hoque. "Estimation and Prediction of Mobility and Reliability Measures Using Different Modeling Techniques". FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3880.

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The goal of this study is to investigate the predictive ability of less data intensive but widely accepted methods to estimate mobility and reliability measures. Mobility is a relatively mature concept in the traffic engineering field. Therefore, many mobility measure estimation methods are already available and widely accepted among practitioners and researchers. However, each method has their inherent weakness, particularly when they are applied and compared with real-world data. For instances, Bureau of Public Roads (BPR) Curves are very popular in static route choice assignment, as part of demand forecasting models, but it is often criticized for underperforming in congested traffic conditions where demand exceeds capacity. This study applied five mobility estimation methods (BPR Curve, Akcelic Function, Florida State University (FSU) Regression Model, Queuing Theory, and Highway Capacity Manual (HCM) Facility Procedures) for different facility types (i.e. Freeway and Arterial) and time periods (AM Peak, Mid-Day, PM Peak). The study findings indicate that the methods were able to accurately predict mobility measures (e.g. speed and travel time) on freeways, particularly when there was no congestion and the volume was less than the capacity. In the presence of congestion, none of the mobility estimation methods predicted mobility measures closer to the real-world measure. However, compared with the other prediction models, the HCM procedure method was able to predict mobility measures better. On arterials, the mobility measure predictions were not close to the real-world measurements, not even in the uncongested periods (i.e. AM Peak and Mid-Day). However, the predictions are relatively better in the AM and Mid-Day periods that have lower volume/capacity ration compared to the PM Peak period. To estimate reliability measures, the study applied three products from the Second Strategic Highway Research Program (SHRP2) projects (Project Number L03, L07, and C11) to estimate three reliability measures; the 80th percentile travel time index, 90th percentile travel time index, and 95th percentile travel time index. A major distinction between mobility estimation process and reliability estimation process lies in the fact that mobility can be estimated for any particular day, but reliability estimation requires a full year of data. Inclusion of incident days and weather condition are another important consideration for reliability measurements. The study found that SHRP2 products predicted reliability measures reasonably well for freeways for all time periods (except C11 in the PM Peak). On arterials, the reliability predictions were not close to the real-world measure, although the differences were not as drastic as seen in the case of arterial mobility measures.

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Daoud, Mohammad. "An intelligent mobility prediction scheme for location-based service over cellular communications network". Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/8697.

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One of the trickiest challenges introduced by cellular communications networks is mobility prediction for Location Based-Services (LBSs). Hence, an accurate and efficient mobility prediction technique is particularly needed for these networks. The mobility prediction technique incurs overheads on the transmission process. These overheads affect properties of the cellular communications network such as delay, denial of services, manual filtering and bandwidth. The main goal of this research is to enhance a mobility prediction scheme in cellular communications networks through three phases. Firstly, current mobility prediction techniques will be investigated. Secondly, innovation and examination of new mobility prediction techniques will be based on three hypothesises that are suitable for cellular communications network and mobile user (MU) resources with low computation cost and high prediction success rate without using MU resources in the prediction process. Thirdly, a new mobility prediction scheme will be generated that is based on different levels of mobility prediction. In this thesis, a new mobility prediction scheme for LBSs is proposed. It could be considered as a combination of the cell and routing area (RA) prediction levels. For cell level prediction, most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the New Markov-Based Mobility Prediction (NMMP) and Prediction Location Model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression and insufficient accuracy. In this thesis, Location Prediction based on a Sector Snapshot (LPSS) is introduced, which is based on a Novel Cell Splitting Algorithm (NCPA). This algorithm is implemented in a micro cell in parallel with the new prediction technique. The LPSS technique, compared with two classic prediction techniques and the experimental results, shows the effectiveness and robustness of the new splitting algorithm and prediction technique. In the cell side, the proposed approach reduces the complexity cost and prevents the cell level prediction technique from performing in time slots that are too close. For these reasons, the RA avoids cell-side problems. This research discusses a New Routing Area Displacement Prediction for Location-Based Services (NRADP) which is based on developed Ant Colony Optimization (ACO). The NRADP, compared with Mobility Prediction based on an Ant System (MPAS) and the experimental results, shows the effectiveness, higher prediction rate, reduced search stagnation ratio, and reduced computation cost of the new prediction technique.

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Merah, Amar Farouk. "Vehicular Movement Patterns: A Sequential Patterns Data Mining Approach Towards Vehicular Route Prediction". Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22851.

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Behavioral patterns prediction in the context of Vehicular Ad hoc Networks (VANETs)has been receiving increasing attention due to enabling on-demand, intelligent traffic analysis and response to real-time traffic issues. One of these patterns, sequential patterns, are a type of behavioral patterns that describe the occurence of events in a timely-ordered fashion. In the context of VANETs, these events are defined as an ordered list of road segments traversed by vehicles during their trips from a starting point to their final intended destination, forming a vehicular path. Due to their predictable nature, undertaken vehicular paths can be exploited to extract the paths that are considered frequent. From the extracted frequent paths through data mining, the probability that a vehicular path will take a certain direction is obtained. However, in order to achieve this, samples of vehicular paths need to be initially collected over periods of time in order to be data-mined accordingly. In this thesis, a new set of formal definitions depicting vehicular paths as sequential patterns is described. Also, five novel communication schemes have been designed and implemented under a simulated environment to collect vehicular paths; such schemes are classified under two categories: Road Side Unit-Triggered (RSU-Triggered) and Vehicle-Triggered. After collection, extracted frequent paths are obtained through data mining, and the probability of these frequent paths is measured. In order to evaluate the e ciency and e ectiveness of the proposed schemes, extensive experimental analysis has been realized. From the results, two of the Vehicle-Triggered schemes, VTB-FP and VTRD-FP, have improved the vehicular path collection operation in terms of communication cost and latency over others. In terms of reliability, the Vehicle-Triggered schemes achieved a higher success rate than the RSU-Triggered scheme. Finally, frequent vehicular movement patterns have been effectively extracted from the collected vehicular paths according to a user-de ned threshold and the confidence of generated movement rules have been measured. From the analysis, it was clear that the user-de ned threshold needs to be set accordingly in order to not discard important vehicular movement patterns.

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Bower, Jennifer. "Speciation, Distribution, Prediction, and Mobility of Lead in Urban Soils: A Multiscale Study". ScholarWorks @ UVM, 2017. http://scholarworks.uvm.edu/graddis/715.

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Lead (Pb), a trace metal notorious for its impacts on human health, has achieved worldwide environmental dispersal resulting from centuries of use by human society. The toxicity of Pb is governed largely by its mineral form, which is in turn controlled by pH, localized reactivity and soil processes that differ according to soil type, location and Pb source. Given the context of these localized dependencies, or site specificity, efforts to predict Pb toxicity and refine sustainable remediation techniques are most useful when Pb behavior is constrained and predicted within environments with homogeneous conditions, such as a single soil. I evaluated and predicted the behavior of Pb, a typical anthropogenic contaminant, within a single soil using bioaccessibility testing and predictive geospatial modeling to assess potential impacts and refine sustainable remediation methods. To test the hypothesis that Pb speciation is influenced by competitive sorption processes in soils, I investigated changes in mobility and speciation of Pb upon addition of amendments at multiple scales using flow-through column experiments, soil characterization and synchrotron-based x-ray techniques. Kriging and cokriging maps provided a successful estimation of background and total Pb, the latter incorporating housing age as a secondary variable to increase model accuracy, though efforts to automate detection of background Pb were complicated by approximation of building extents, and overall heterogeneity of soil Pb concentration gives high error. Acute Pb heterogeneity is observed at the scale of a single site among near-structure samples. At the city-scale, determination of bioaccessibility revealed that bioaccessible and total Pb are well-correlated, to the extent that bioaccessibility may be predicted for the soil underlying Burlington, VT; this information, combined with predictive blood lead level modeling and the CDC's recent establishment of 5 μg kg-1 as a threshold for blood lead toxicity, enabled the establishment of a site-specific revised soil Pb limit of 360 mg kg-1, lower than the EPA's general soil Pb threshold of 400 mg kg-1. Characterization of leached and unleached soil using scanning electron microscope energy dispersive spectroscopy (SEM-EDS) and microfocused x-ray techniques provided a first look at Pb paint species using synchrotron technologies. Pb was present within paint chips as hydrocerussite, but appeared to weather to anglesite over time. Pb also seemed to act as cation bridge, attracting clay minerals electrostatically and becoming incorporated into heterogeneous soil aggregates. Accessory paint elements are identified in soil and within paint chips and may further complicate these systems. Column experiments, at acidic pH, yielded little evidence of Pb mobility change in response to modification of competitive sorbents. Kinetics of Pb release were driven by pH, with Pb solubilizing at pH of ˜4.9 as column soil acidifies. This work provides evidence for changes in Pb speciation over time in urban soils impacted by Pb paint, and presents a framework for predictive risk analysis at a local site using experimental and modeling tools. Multiscale observations and analytical results can be used in future efforts to model and refine sustainable remediation solutions within a site-specific context.

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Gailey, Robert Stuart. "The amputee mobility predictor : a functional assessment instrument for the prediction of the lower limb amputee's readiness to ambulate". Thesis, University of Strathclyde, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367028.

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Gunnarsson, Robin, i Alexander Åkermark. "Approaching sustainable mobility utilizing graph neural networks". Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45191.

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This report is done in collaboration with WirelessCar for the master of science thesis at Halmstad University. Many different parameters influence fuel consumption. The objective of the report is to evaluate if Graph neural networks are a practical model to perform fuel consumption prediction on areas. The model uses a partitioning of geographical locations of trip observations to capture their spatial information. The project also proposes a method to capture the non-stationary behavior of vehicles by defining a vehicle node as a separate entity. The model then captures their different features in a dense layer neural network and utilizes message passing to capture context about neighboring nodes. The model is compared to a baseline neural network with a similar network architecture as the graph neural network. The data is partitioned to define an area with Kmeans and static gridnet partition with and without terrain details. This partition is used to structure a homogeneous graph that is underperforming. The practical drawbacks of the initial homogeneous graph are inspected and addressed to develop a heterogeneous graph that can outperform the neural network baseline.

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Mohammadi, Neda. "Urban Spatiotemporal Energy Flux". Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/89611.

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Urban energy systems are often studied in a very similar way in the sense that the characteristics of the underlying physical infrastructure are weighted as the main determinants of energy use predictions, while the behavior of the human population in relation to this systemthe so-called ``energy consumers''in time and urban spaces is effectively neglected. The spatial and temporal variations in infrastructure-population interactivity greatly complicate urban energy systems; the unremitting growth in population and advances in technology mean that the dynamic interrelationship between the population and urban environment will continue to grow exponentially, resulting in increasing uncertainties, unreliable predictions and poor management decisions given the inadequacy of existing approaches. In this dissertation, I explore the interdependencies of spatiotemporal fluctuations of human mobility as an indicator for human activities and energy use in urban areas in three main studies. First, I show that the fluctuations of intra-urban human mobility and energy use have an underlying structure across both time and space, and that human mobility can indeed be used as a predictor for energy use in both dimensions. Second, I examine how one of the dominant drivers of this structure, namely individuals' location-based activities, influence patterns in energy supply and demand across building types (i.e. residential and commercial buildings) and show how variations in the human mobility networks of two distinct urban populations (the so-called returners and explorers) can explain fluctuations in energy use. Third, I introduce an integrated approach for predicting urban energy use across time and space by incorporating these interdependencies. Generating predictive models that capture the spatiotemporal variations in these determinants in urban settings, as suggested in this research, will contribute to our understanding of how variations in urban population activities for particular times and locations influence can be applied to estimate energy use patterns in surrounding areas.
PHD

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Leng, Yan Ph D. Massachusetts Institute of Technology. "Urban computing using call detail records : mobility pattern mining, next-location prediction and location recommendation". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104156.

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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 145-152).
Urban computing fuses computer science with other fields, such as transportation, in the context of urban spaces by connecting ubiquitous sensing technologies, analytical models and visualizations to solve challenging problems in urban environment and operation systems. This paper focuses on Call Detail Records, one widely collected opportunistic sensing data source for billing purposes, to understand presence patterns, develop mobility prediction methods and reduce traffic congestions with location recommendations. Understanding human mobility and presence patterns at locations are the building blocks for behavior prediction, service design and system improvements. In the first part, this thesis focuses on 1) understanding presence patterns at user locations with a proposed metric Normalized Hourly Presence, 2) extracting common presence patterns across the population with Principal Component Analysis; 3) and infer home and workplaces using K-means Clustering and Fuzzy C-means Clustering. The proposed method was implemented on MIT Reality Mining data, by which we demonstrate that with inference rates of 56% and 82%, the method can improve 79% and 34% in accuracy respectively in home and workplace inference comparing to the baseline model. In addition, it was implemented on the CDR data collected in a crowded city in China to prove its scalability and applicability in real-world applications. With Fuzzy C-means Clustering, we could flexibly trade-off between inference rate and accuracy to understand the interplay between the two and apply it for various purposes. With an understanding of mobility patterns, the next crucial foundation in urban computing is mobility prediction, enabling transportation practitioners to take actions beforehand and commercial organizations to send location-based advertisements, etc. Specifically, this paper focuses on next-location prediction from Call Detail Records. Mobility traces was analogized to language models, mapping cell towers to words and individual location traces to sentences. Recurrent Neural Network is a successful tool in natural language processing, which is applied in mobility prediction due to its acceptance of sequential input, variable input length and ability to learn the 'meaning' of cell towers. By implementing the method on Call Detail Records collected in Andorra, we show that the method improved more than 40% over the baseline model, with 67% and 78% accuracy in next location at cell tower and merged cell tower level respectively. The 'meanings' of the cell tower could also be inferred, the same as learning the meanings of words in sentences, from the embedding layer of Recurrent Neural Network. The last project aims at tackling the challenge of severe traffic congestions with location recommendations. The availability of large-scale longitudinal geolocation data, such as Call Detail Records, offers planners and service providers an unprecedented opportunity to understand location preferences and alleviate traffic congestions. Location recommendation is a potential tool to achieve these two objectives. Previous research on location recommendations has focused on automatically and accurately inferring users' preferences, while little attention has been devoted to the constraints of service capacity. The ignorance may lead to congestion and long waiting time. We argue that Call Detail Records could help planners and authorities make interventions by providing personalized recommendations given the comprehensive urban-wide picture of historical behaviors and preferences. In this research, we propose a method to make location recommendations for system efficiency, defined as maximizing satisfactions toward recommendations subject to capacity constraints, exploiting travelers' choice flexibilities. We infer implicit location preferences based on sparse and passively-collected Call Detail Records. We then formulate an optimization model the defined system efficiency. As a proof-of-concept experiment, we implement the method in Andorra, a small European country heavily relying on tourism. By extensive simulations, we demonstrate that the method can reduce the travel time increased by congestion during peak hour from 11.73 minutes to 5.6 minutes with idealized trips under full compliance rates. We show that the average travel time increased by congestion is 6.17, 6.98, 8.37 and 10.98 minutes with 80%, 60%, 40% and 20% compliance rates. Overall, our results indicate that Call Detail Records can be used to make locations recommendation while reduce traffic congestion for system efficiency. The proposed method can be applied to other large-scale location traces and extended to other location or events recommendation applications.
by Yan Leng.
S.M. in Transportation
S.M.

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Ben, Cheikh Ahlam. "Gestion de la mobilité dans les réseaux femtocells". Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066656.

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Les femtocellules sont déployées par des FAPs dans la couverture des macrocellules afin d'offrir aux utilisateurs un service continu aussi bien à l'intérieur qu'à l'extérieur.Elles sont caractérisées par une courte portée,faible puissance et ne peuvent couvrir qu'un nombre limité des utilisateurs.Ces caractéristiques rendent la gestion de la mobilité l'un des plus importants défis à résoudre.Dans cette thèse,nous proposons des nouveaux algorithmes de handover.En premier lieu,nous considérons la direction du mobile comme un paramètre clé pour la prise de décision de Handover.Nous proposons un algorithme de handover nommé OHMF basé sur l'optimisation de la liste de FAPs candidats tout en considérant la qualité de signal ainsi que la direction de mouvement de mobile.Ensuite,nous proposons un processus de prédiction de direction basé sur la régression linéaire.L'idée est de prédire la position future du mobile tout en tenant compte des positions actuelle et précédente.Cet algorithme est intitulé OHDP. En deuxième lieu,nous nous intéressons au problème de prédiction de mobilité pour être plus rigoureux lors de prise de décision de handover.Pour cela,nous utilisons les chaînes de markov cachées comme prédicteur du prochain FAP et nous proposons un algorithme de handover nommé OHMP. Afin d'adapter notre solution à toutes les contraintes du réseau femtocellules,nous proposons un algorithme de handover intitulé OHMP-CAC qui intègre un CAC approprié au réseau étudié et une différenciation de service avec et sans contraintes de QoS.Des études de performances basées sur des simulations et des traces de mobilité réelles ont été réalisées pour évaluer l'efficacité de nos propositions
Femtocell network are deployed in the macrocell’s coverage to provide extended services with better performances. Femtocells have a short-range and low power transmissions.Each FAP supports a few number of connected users.Owing to these inherent features, one of the most challenging issues for the femtocellular network deployment remains the mobility management.In this thesis, we propose new handovers algorithms adapted to the characteristics of femtocells network.As a first part,we consider the direction of mobile user as a key parameter for the handover decision.To do so,we propose a new handover algorithm called OHMF. Its main purpose is the optimization of the list of FAPs candidates based on signal quality as well as the mobile direction to better choose the FAP target.After that, we propose an algorithm called OHDP based on the direction prediction using the linear regression.The idea behind this is to predict the future position of mobile based on its current and previous position. As a second part, we focus on mobility prediction problem to make an efficient handover decision.We propose a novel handoff decision algorithm called OHMP that uses HMM as a predictor to accurately estimate the next FAP that a mobile UE would visit,given its current and historical movement information.In order to adapt our solution to the characteristics of femtocells network,we propose a handover algorithm called OHMP-CAC based on HMM tool as a predictor, a proposed CAC and the availability of resources of the predicted FAP,SINR and the traffic type.In order to assess the efficiency of our proposals,all underlying algorithms are evaluated through simulations and real mobility traces

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Martin, Kathryn S. "Measurement and prediction of mobility outcome pre and post stroke rehabilitation using Clinical Outcome Variables (COVS)". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0006/MQ42660.pdf.

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Kewlani, Gaurav. "Stochastic approaches to mobility prediction, path planning and motion control for ground vehicles in uncertain environments". Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/55270.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 107-111).
The ability of autonomous or semi-autonomous unmanned ground vehicles (UGVs) to rapidly and accurately predict terrain negotiability, generate efficient paths online and have effective motion control is a critical requirement for their safety and use in unstructured environments. Most techniques and algorithms for performing these functions, however, assume precise knowledge of vehicle and/or environmental (i.e. terrain) properties. In practical applications, significant uncertainties are associated with the estimation of the vehicle and/or terrain parameters, and these uncertainties must be considered while performing the above tasks. Here, computationally inexpensive methods based on the polynomial chaos approach are studied that consider imprecise knowledge of vehicle and/or terrain parameters while analyzing UGV dynamics and mobility, evaluating safe, traceable paths to be followed and controlling the vehicle motion. Conventional Monte Carlo methods, that are relatively more computationally expensive, are also briefly studied and used as a reference for evaluating the computational efficiency and accuracy of results from the polynomial chaos-based techniques.
by Gaurav Kewlani.
S.M.

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Zhao, Zhan Ph D. Massachusetts Institute of Technology. "Uncovering individual mobility patterns from Transit Smart Card data : trip prediction, activity inference, and change detection". Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122383.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: Ph. D. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 149-160).
While conventional travel survey data are limited in sample size and observation period, recent advances in urban sensing technologies afford the opportunity to collect traces of individual mobility at a large scale and over extended periods of time. As a result, individual mobility has become an emerging field dedicated to extracting patterns that describe individual movements in time and space. Individual mobility is the result of spatiotemporal choices (e.g., the decision to go somewhere at some time) made by individuals with diverse and dynamic preferences and lifestyles. These spatiotemporal choices vary across individuals, but also for the same person over time. However, our understanding of the behavioral mechanism underlying individual mobility is lacking. The objective of this dissertation is to develop statistical approaches to extract dynamic and interpretable travel-activity patterns from individual-level longitudinal travel records.
Specifically, this work focuses on three problems related to the spatiotemporal behavioral structures in individual mobility--next trip prediction, latent activity inference, and pattern change detection. Transit smart card data from London's rail network are used as a case study for the analysis. To account for the sequential dependency between trips, a predictive model is developed for the prediction of the next trip based on the previous one. Each trip is defined by a combination of start time t (aggregated to hours), origin o, and destination d. To predict the next trip of an individual, we first predict whether the individual will travel again in the period of interest (trip making prediction), and, if so, predict the attributes of the next trip (t, o, d) (trip attribute prediction). For trip attribute prediction, a Bayesian n-gram model is developed to estimate the probability distribution of the next trip conditional on the previous one.
Based on regularized logistic regression, the trip making prediction models achieve median accuracy levels of over 80%. The prediction accuracy for trip attributes varies by the attribute considered--around 40% for t, 70-80% for o and 60-70% for d. The first trip of the day is more difficult to predict than later trips. Significant variations are found across individuals in terms of the model performance, implying diverse mobility patterns. Human activities have long been recognized as the fundamental driver for travel demand. While passively-collected human mobility data sources, such as the transit smart card data, can accurately capture the time and location of individual movements, they do not explicitly provide any behavioral explanation regarding why people travel, e.g., activity types or travel purposes.
Probabilistic topic models, which are widely used in natural language processing for document classification, can be adapted to uncover latent activity patterns from human mobility data in an unsupervised manner. In this case, the activity episodes (i.e., discrete activity participations between trips) of an individual are treated as words in a document, and each "topic" represents a unique distribution over space and time that corresponds to some activity type. Specifically, a classical topic model, Latent Dirichlet Allocation (LDA), is extended to incorporate multiple heterogeneous spatiotemporal attributes--the location, arrival time, day of week, and duration of stay. The model is tested with different choices of the number of activities Z, and the results demonstrate how new patterns may emerge as Z increases. The discovered latent activities reveal diverse spatiotemporal patterns, and provide a new way to characterize individual activity profiles.
Although stable in the short term, individual mobility patterns are subject to change in the long term. The ability to detect such changes is critical for developing behavior models that are adaptive over time. In this study, a travel pattern change is defined as "an abrupt, substantial, and persistent change in the underlying pattern of travel". To detect these changes from longitudinal travel records, we specify one distribution for each of the three dimensions of travel behavior (the frequency of travel, time of travel, and origins/destinations), and interpret the change of the parameters of the distributions as indicating a pattern change. A Bayesian method is developed to estimate the probability that a pattern change occurs at any given time for each behavioral dimension. The test results show that the method can successfully identify significant changepoints in travel patterns.
Compared to the traditional generalized likelihood ratio (GLR) approach, the Bayesian method requires fewer predefined parameters and is more robust. It is generalizable and may be applied to detect changes in other aspects of travel behavior and human behavior in general.
by Zhan Zhao.
Ph. D. in Transportation
Ph.D.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

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RAJSHIVA, KIRTIMAAN. "PERFORMANCE ENHANCEMENTS FOR Ad Hoc NETWORKS USING MOBILITY-LOCATION INFORMATION". University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1132338696.

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Uppoor, Sandesh. "Understanding and Exploiting Mobility in Wireless Networks". Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00912521.

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Le degré de pénétration du marché des appareils intelligents tels que les smartphones et les tablettes avec les technologies de communication embarquées comme le WiFi, 3G et LTE a explosé en moins d'une décennie. En complément de cette tendance technologique, les appli- cations des réseaux sociaux ont virtuellement connecté une grande partie de la population, en génèrant une demande de trafic de données croissant vers et depuis l'infrastructure de com- munication. Les communications pervasive ont aussi acquis une importance dans l'industrie automobile. L'émergence d' une gamme impressionnante d' appareils intelligents dans les véhicules permettant services tels que assistance au conducteur, infotainment, suivi à dis- tance du vehicule, et connectivité àux réseaux sociaux même en déplacement. La demande exponentielle de connectivité a encore défié les fournisseurs de services de télécommunications pour répondre aux attentes des utilisateurs du réseau à grande vitesse. L'objectif de cette thèse est de modéliser et comprendre la mobilité dynamique des utilisateurs à grande vitesse et leurs effets sur les architectures de réseau sans fil. Compte tenu de l' importance du développement de notre étude sur une représentation réal- iste de la mobilité des véhicules, nous étudions tout d'abord les approches les plus populaires pour la génération de trafic routier synthétique et discutons les caractéristiques des ensem- bles de données accessibles au public qui decrivent des mobilités véhiculaires. En utilisant l'information des déplacements de la population dans une région métropolitaine, les données du réseau routier détaillées et des modèles réalistes de conduite microscopiques, nous pro- posons un jeux de données de mobilité véhiculaire original qui redéfinit l'état de l'art et qui replie la circulation routière de facon realiste dans le temps et dans l'espace. Nous étudions ensuite l'impact des dynamiques de mobilité du point de vue de la couverture cellulaire en présence d'un déploiement réel des stations de base. En outre, en examinant les effets de la mobilité des véhicules sur les réseaux autonomes, nous voyons des possibilités pour les futurs paradigmes de réseaux hétérogènes. Motivés par l'évolution dynamique dans le temps de la mobilité des véhicules observée dans notre jeux de données, nous proposons également une approche en ligne pour prédire les flux de trafic macroscopiques. Nous analysons les paramètres affectant la prédiction de la mobilité en milieu urbain. Nous dévoilons quand et où la gestion des ressources réseau est plus crucial pour accueillir le trafic généré par les utilisateurs à bord. Ces études dévoilent des multiples opportunités de gestion intelligente des transports, soit pour construire de nouvelles routes, soit pour l'installation de bornes de recharge électriques, ou pour la conception de systèmes de feux de circulation intelligents, contribuant ainsi à la planification urbaine.

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Pedley, Gillian Elizabeth. "The prediction of hospital-acquired pressure ulcers in mobility-impaired, elderly orthopaedic patients : A prospective cohort study". Thesis, St George's, University of London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511955.

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Ferroni, Nicola. "Un sistema di previsione degli itinerari per applicazioni di smart mobility". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11547/.

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In questo lavoro verrà presentato lo sviluppo di un'applicazione nell'ambito della "Smart Mobility". In particolare verrà fornita l'implementazione di un modulo che sarà parte integrante di un'infrastruttura molto complessa, SMAll. Verranno quindi presentate alcune tecnologie utilizzate per la raccolta dei dati e l'utilizzo delle mappe, con particolare attenzione riguardo a OpenStreetMap. Seguirà quindi una presentazione del progetto divisa nelle fasi di analisi e progettazione, dettagliando tramite opportuni diagrammi il lavoro svolto. Infine ci sarà una discussione riguardo i risultati ottenuti e sugli sviluppi futuri che potranno essere intrapresi.

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Baumann, Paul [Verfasser], Silvia [Akademischer Betreuer] Santini i Anind K. [Gutachter] Dey. "Human Mobility and Application Usage Prediction Algorithms for Mobile Devices / Paul Baumann ; Gutachter: Anind K. Dey ; Betreuer: Silvia Santini". Dresden : Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://d-nb.info/1119363306/34.

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Choutri, Amira. "Gestion des ressources et de la consommation énergétique dans les réseaux mobiles hétérogènes". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLV043/document.

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L'objectif de cette thèse est de développer les méthodes nécessaires à une gestion ciblée et efficace de la mobilité des utilisateurs dans un réseau mobile hétérogène. Ces réseaux sont caractérisés par le déploiement de différents types de cellules (macro, micro, pico et/ou femto). Le déploiement massif des petites cellules (pico et femto) a permis d'offrir une capacité et une qualité de couverture accrue au réseau, notamment dans les zones à forte densité. Cependant, les contraintes temps réel engendrées limitent la QoS offerte aux utilisateurs. De plus, pour des raisons commerciales et/ou environnementales, la nécessité de réduire la consommation énergétique des réseaux mobiles est devenue une réalité. Ainsi, les opérateurs mobiles doivent trouver le bon compromis entre d'une part, la garantie de la QoS offerte aux utilisateurs et la vitesse de mobilité de ces derniers, et d'une autre part, le coût énergétique engendré pour le déploiement du réseau. Pour cela, dans le cadre de la gestion de la mobilité des utilisateurs, nous proposons des modèles pour la gestion des ressources des stations de base ainsi que pour la gestion de leur consommation énergétique. Le premier modèle proposé vise à gérer le partage des ressources entre les clients de l'opérateur mobile. Basé sur la prédiction de la mobilité des utilisateurs, ce modèle permet d'anticiper la gestion des ressources d'une station de base. Le deuxième modèle gère la consommation énergétique du réseau en se basant sur un contrôle d'affectation des utilisateurs mobiles. Cela permet de contrôler en continu la consommation énergétique des stations de base et la QoS qu'elles offrent aux utilisateurs mobiles. Par simulation, en utilisant une topologie réelle d'un réseau mobile, les performances des méthodes proposées sont évaluées en considérant différents scénarios possibles. Leurs performances sont comparées à celles de l'approche adoptée par des opérateurs mobiles actuels, ainsi qu'à celles de certaines approches proposées dans la littérature
The objective of this thesis is to develop methods for a targeted and efficient management of users mobility in heterogeneous mobile networks. This network is characterized by the deployment of different types of cells (macro, micro, pico and/or femto). The massive deployment of small cells (pico and femto) provides a supplementary coverage and capacity to mobile networks, specially in dense areas. However, the resulting real-time constraints limit the offered QoS. Furthermore, for commercial and/or environmental reasons, the needs to reduce the energy consumed by mobile networks became reality. Thus, mobile operators have to find a good compromise between, on the one hand, the users velocity and the guaranteed QoS, and on the other hand, the cost of deployment of such networks. For that, in the context of users mobility management, we propose models for resource and energy consumption management of base stations. The first model aims at controlling resource sharing between clients of the mobile operators. Based on a mobility prediction of users, this model anticipates the resource management of a base station. The second model aims at reducing energy consumption of the network by managing mobile users assignment to detected cells. This allows a continuous control of consumed energy of base stations while offered QoS is guaranteed. Based on simulation of a real mobile network topology, the performances of proposed models are evaluated while considering different possible scenarios. They are compared to the performances of different strategies as the ones proposed in literature or adopted by current mobile operators

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Karakoc, Mucahit. "Comparison Of Domain-independent And Domain-specific Location Predictors With Campus-wide Wi-fi Mobility Data". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612402/index.pdf.

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In mobile computing systems, predicting the next location of a mobile wireless user has gained interest over the past decade. Location prediction may have a wide-range of application areas such as network load balancing, advertising and web page prefetching. In the literature, there exist many location predictors which are divided into two main classes: domain-independent and domain-specific. Song et al. compare the prediction accuracy of the domain-independent predictors from four major families, namely, Markov-based, compression-based, PPM and SPM predictors on Dartmouth'
s campus-wide Wi-Fi mobility data. As a result, the low-order Markov predictors are found as the best predictor. In another work, Bayir et al. propose a domain-specific location predictor (LPMP) as the application of a framework used for discovering mobile cell phone user profiles. In this thesis, we evaluate LPMP and the best Markov predictor with Dartmouth'
s campus-wide Wi-Fi mobility data in terms of accuracy. We also propose a simple method which improves the accuracy of LPMP slightly in the location prediction part of LPMP. Our results show that the accuracy of the best Markov predictor is better than that of LPMP in total. However, interestingly, LPMP yields more accurate results than the best Markov predictor does for the users with the low prediction accuracy.

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Ben, Cheikh Ahlam. "Gestion de la mobilité dans les réseaux femtocells". Electronic Thesis or Diss., Paris 6, 2016. http://www.theses.fr/2016PA066656.

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Les femtocellules sont déployées par des FAPs dans la couverture des macrocellules afin d'offrir aux utilisateurs un service continu aussi bien à l'intérieur qu'à l'extérieur.Elles sont caractérisées par une courte portée,faible puissance et ne peuvent couvrir qu'un nombre limité des utilisateurs.Ces caractéristiques rendent la gestion de la mobilité l'un des plus importants défis à résoudre.Dans cette thèse,nous proposons des nouveaux algorithmes de handover.En premier lieu,nous considérons la direction du mobile comme un paramètre clé pour la prise de décision de Handover.Nous proposons un algorithme de handover nommé OHMF basé sur l'optimisation de la liste de FAPs candidats tout en considérant la qualité de signal ainsi que la direction de mouvement de mobile.Ensuite,nous proposons un processus de prédiction de direction basé sur la régression linéaire.L'idée est de prédire la position future du mobile tout en tenant compte des positions actuelle et précédente.Cet algorithme est intitulé OHDP. En deuxième lieu,nous nous intéressons au problème de prédiction de mobilité pour être plus rigoureux lors de prise de décision de handover.Pour cela,nous utilisons les chaînes de markov cachées comme prédicteur du prochain FAP et nous proposons un algorithme de handover nommé OHMP. Afin d'adapter notre solution à toutes les contraintes du réseau femtocellules,nous proposons un algorithme de handover intitulé OHMP-CAC qui intègre un CAC approprié au réseau étudié et une différenciation de service avec et sans contraintes de QoS.Des études de performances basées sur des simulations et des traces de mobilité réelles ont été réalisées pour évaluer l'efficacité de nos propositions
Femtocell network are deployed in the macrocell’s coverage to provide extended services with better performances. Femtocells have a short-range and low power transmissions.Each FAP supports a few number of connected users.Owing to these inherent features, one of the most challenging issues for the femtocellular network deployment remains the mobility management.In this thesis, we propose new handovers algorithms adapted to the characteristics of femtocells network.As a first part,we consider the direction of mobile user as a key parameter for the handover decision.To do so,we propose a new handover algorithm called OHMF. Its main purpose is the optimization of the list of FAPs candidates based on signal quality as well as the mobile direction to better choose the FAP target.After that, we propose an algorithm called OHDP based on the direction prediction using the linear regression.The idea behind this is to predict the future position of mobile based on its current and previous position. As a second part, we focus on mobility prediction problem to make an efficient handover decision.We propose a novel handoff decision algorithm called OHMP that uses HMM as a predictor to accurately estimate the next FAP that a mobile UE would visit,given its current and historical movement information.In order to adapt our solution to the characteristics of femtocells network,we propose a handover algorithm called OHMP-CAC based on HMM tool as a predictor, a proposed CAC and the availability of resources of the predicted FAP,SINR and the traffic type.In order to assess the efficiency of our proposals,all underlying algorithms are evaluated through simulations and real mobility traces

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31

Makhlouf, Nermin. "Predikce Pohybu Bezdrátových Uzlů v Mobilních Ad Hoc Sítích (MANET)". Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-399211.

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Rychlý vývoj v oblasti mobilní informatiky vyústil v nový, alternativní způsob mobilní komunikace, v němž mobilní uzly tvoří samoorganizující se bezdrátovou síť, jíž se říká mobilní síť ad hoc (Mobile Ad hoc Network, MANET). Specifické vlastnosti sítí MANET stavějí návrh síťového protokolu před řadu problémů na všech vrstvách protokolové sady . Příčinou jsou nepředvídatelné změny topologie a mobilní povaha těchto sítí. Nástrojem, který řeší problémy plynoucí z mobility uzlů, je predikce budoucích změn v topologii sítě. To má zásadní význam pro různé úlohy jako přesměrování. Tato disertační práce se zabývá dvěma metodami predikce mobility pro sítě MANET. První metoda se nazývá „predikce mobility s využitím virtuální mapy“ (mobility prediction using virtual map) a předpokládá, že každý uzel si dokáže vybudovat svou virtuální mapu v závislosti na svém umístění v průběhu času. Vyvinutý predikční algoritmus byl implementován do síťového simulátoru NS-2, aby jej bylo možné vyhodnotit. V této práci zkoumám stávající modely mobility a způsob, jakým v nich lze aplikovat tuto metodu predikce. Simulace sledují zlepšení výkonnosti, co se týče průměrného zpoždění na bázi end-to-end, poměru doručených paketů a propustnosti sítě. Navržený koncept predikce byl implementován pomocí směrovacího protokolu AODV(Ad Hoc On-Demand Distance Vector). Pro druhou metodu jsem vyvinula umělou neuronovou síť pro predikci pohybů v sítích MANET. Model pro predikci mobility vznikl na základě dat shromážděných ze vzorců umístění. K učení či trénování ANN byl využit bayesovský přístup. Ten byl implementován v softwaru pro trénování bayesovských neuronových sítí s názvem Model Manager. Nejlepším způsobem hodnocení závěrečného modelu je provedení predikcí a jejich srovnání s cílovými daty. Predikce vznikají na základě 50 vzorců jako vstupních proměnných. Dosažené výsledky prezentované s diskutované v práci se vyznačují zlepšením zásadních parametrů komunikační sítě, jako jsou propustnost, zpoždění, Poměr doručených paketů, až o 30% v porovnání s klasickým směrovacím protokolem AODV, kde není implementován predikční model.

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Magnano, Alexander. "Predictive Mobile IP Handover for Vehicular Networks". Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34350.

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Vehicular networks are an emerging technology that offer potential for providing a variety of new services. However, extending vehicular networks to include IP connections is still problematic, due in part to the incompatibility of mobile IP handovers with the increased mobility of vehicles. The handover process, consisting of discovery, registration, and packet forwarding, has a large overhead and disrupts connectivity. With increased handover frequency and smaller access point dwell times in vehicular networks, the handover causes a large degradation in performance. This thesis proposes a predictive handover solution, using a combination of a Kalman filter and an online hidden Markov model, to minimize the effects of prediction errors and to capitalize on advanced handover registration. Extensive simulated experiments were carried out in NS-2 to study the performance of the proposed solution within a variety of traffic and network topology scenarios. Results show a significant improvement to both prediction accuracy and network performance when compared to recent proposed approaches.

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Ernault, Estève. "Thermo-oxydation de résines époxy/amine". Thesis, Paris, ENSAM, 2016. http://www.theses.fr/2016ENAM0060/document.

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Les résines époxy/amine obtenues grâce au mélange d’un prépolymère époxy et d’un durcisseur amine, sont utilisées dans divers domaines d’applications : peinture, potting de composés électroniques... L’objectif de cette thèse est la prédiction de la durée de vie de trois résines : DGEBA ou DGEBU/cycloalipahtique diamine, DGEBA/aliphatique diamine, soumises à un vieillissement thermo-oxydant. Pour cela, une étude multi échelle de l’oxydation est réalisée à différentes conditions de température (de 110°C à 200°C) et de pression d’oxygène (0,2 bars et 50 bars). A l’échelle moléculaire, la spectroscopie IRTF a montré la formation d’amides et de carbonyles. A l’échelle macromoléculaire, les coupures de chaînes semblent prédominantes lorsque le durcisseur est une diamine cycloaliphatique. En revanche, lorsque le système contient des séquences méthylènes portées par des segments flexibles, elles peuvent induire un mécanisme de réticulation qui peut prédominer. Ces résultats gouvernent l’évolution des propriétés fonctionnelles : la fragilisation mécanique et la dégradation des propriétés diélectriques de DGEBA/cycloaliphatique diamine se produit pour des temps d’exposition inférieurs à ceux observés pour DGEBA/aliphatique diamine. L’extrapolation des durées de vie est réalisée grâce à une modélisation cinétique basée sur un schéma mécanistique de l’oxydation des trois résines. La résolution de ce schéma cinétique permet la modélisation de l’ensemble des résultats expérimentaux (concentration en produits d’oxydation, coupures de chaînes et réticulation) pour une oxydation homogène ou bien sur des échantillons épais présentant un gradient d’oxydation. Les contraintes mécaniques engendrées lors de l’oxydation d’un échantillon épais (3 mm) de DGEBA/cycloaliphatique diamine ont été simulées afin de prédire la fissuration spontanée
Epoxy/amine resins are thermoset materials made of epoxy prepolymer and amine hardener. Those materials are used in several industrial applications, such as paint or to encapsulate electronics. The main goal of this work is to predict lifetime of three resins: DGEBA or DGEBU/cycloaliphatic diamine, DGEBA/aliphatic diamine, in thermo-oxidative environment. In order to achieve this, a multi scale study of the oxidation is done, at several temperatures (from 110°C to 200°C) and oxygen partial pressures (0,2 bars et 50 bars). At molecular scale, the formation of amides and carbonyls has been noticed. At macromolecular scale, chain scission has been observed in epoxy/cycloaliphatic diamine but in DGEBA/aliphatic diamine cross linking seems to be predominant. Those properties are directly related to functional properties: mechanical and dielectric break down appear later in DGEBA/aliphatic diamine than in epoxy/cycloaliphatic diamine. The extrapolation of life is possible thank to kinetic modelling, based on chemical mechanistic scheme. The resolution of this kinetic scheme allowed us to model all experimental data (concentration of oxidation products, chain scission and cross linking), either in homogenous oxidation and in thick samples (3 mm). Stresses induced by oxidation in a thick sample of DGEBA/cycloaliphatic diamine have been simulated thanks to Matlab ® and finite elements by Abaqus ®

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34

Kurda, Reben. "Cooperation strategies for inter-cell interference mitigation in OFDMA systems". Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112032/document.

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Récemment, l'utilisation des réseaux cellulaires a radicalement changé avec l’émergence de la quatrième génération (4G) de systèmes de télécommunications mobiles LTE/LTE-A (Long Term Evolution-Advanced). Les réseaux de générations précédentes (3G), initialement conçus pour le transport de la voix et les données à faible et moyen débits, ont du mal à faire face à l’augmentation accrue du trafic de données multimédia tout en répondant à leurs fortes exigences et contraintes en termes de qualité de service (QdS). Pour mieux répondre à ces besoins, les réseaux 4G ont introduit le paradigme des Réseaux Hétérogènes (HetNet).Les réseaux HetNet introduisent une nouvelle notion d’hétérogénéité pour les réseaux cellulaires en introduisant le concept des smalls cells (petites cellules) qui met en place des antennes à faible puissance d’émission. Ainsi, le réseau est composé de plusieurs couches (tiers) qui se chevauchent incluant la couverture traditionnelle macro-cellulaire, les pico-cellules, les femto-cellules, et les relais. Outre les améliorations des couvertures radio en environnements intérieurs, les smalls cells permettent d’augmenter la capacité du système par une meilleure utilisation du spectre et en rapprochant l’utilisateur de son point d’accès au réseau. Une des conséquences directes de cette densification cellulaire est l’interférence générée entre les différentes cellules des diverses couches quand ces dernières réutilisent les mêmes fréquences. Aussi, la définition de solutions efficaces de gestion des interférences dans ce type de systèmes constitue un de leurs défis majeurs. Cette thèse s’intéresse au problème de gestion des interférences dans les systèmes hétérogènes LTE-A. Notre objectif est d’apporter des solutions efficaces et originales au problème d’interférence dans ce contexte via des mécanismes d’ajustement de puissance des petites cellules. Nous avons pour cela distingués deux cas d’étude à savoir un déploiement à deux couches macro-femtocellules et macro-picocellules. Dans la première partie dédiée à un déploiement femtocellule et macrocellule, nous concevons une stratégie d'ajustement de puissance des femtocellules assisté par la macrocellule et qui prend en compte les performances des utilisateurs des femtocells tout en atténuant l'interférence causée aux utilisateurs des macrocellules sur leurs liens montants. Cette solution offre l’avantage de la prise en compte de paramètres contextuels locaux aux femtocellules (tels que le nombre d’utilisateurs en situation de outage) tout en considérant des scénarios de mobilité réalistes. Nous avons montré par simulation que les interférences sur les utilisateurs des macrocellules sont sensiblement réduites et que les femtocellules sont en mesure de dynamiquement ajuster leur puissance d'émission pour atteindre les objectifs fixés en termes d’équilibre entre performance des utilisateurs des macrocellules et celle de leurs propres utilisateurs. Dans la seconde partie de la thèse, nous considérons le déploiement de picocellules sous l'égide de la macrocellule. Nous nous sommes intéressés ici aux solutions d’extension de l’aire picocellulaire qui permettent une meilleure association utilisateur/cellule permettant de réduire l’interférence mais aussi offrir une meilleure efficacité spectrale. Nous proposons donc une approche basée sur un modèle de prédiction de la mobilité des utilisateurs qui permet de mieux ajuster la proportion de bande passante à partager entre la macrocellule et la picocellule en fonction de la durée de séjour estimée de ces utilisateurs ainsi que de leur demandes en bande passante. Notre solution a permis d’offrir un bon compromis entre les débits réalisables de la Macro et des picocellules
Recently the use of modern cellular networks has drastically changed with the emerging Long Term Evolution Advanced (LTE-A) technology. Homogeneous networks which were initially designed for voice-centric and low data rates face unprecedented challenges for meeting the increasing traffic demands of high data-driven applications and their important quality of service requirements. Therefore, these networks are moving towards the so called Heterogeneous Networks (HetNets). HetNets represent a new paradigm for cellular networks as their nodes have different characteristics such as transmission power and radio frequency coverage area. Consequently, a HetNet shows completely different interference characteristics compared to homogeneous deployment and attention must be paid to these disparities when different tiers are collocated together. This is mostly due to the potential spectrum frequency reuse by the involved tiers in the HetNets. Hence, efficient inter-cell interference mitigation solutions in co-channel deployments of HetNets remain a challenge for both industry and academic researchers. This thesis focuses on LTE-A HetNet systems which are based on Orthogonal Frequency Division Multiplexing Access (OFDMA) modulation. Our aim is to investigate the aggressive interference issue that appears when different types of base stations are jointly deployed together and especially in two cases, namely Macro-Femtocells and Macro-Picocells co-existence. We propose new practical power adjustment solutions for managing inter-cell interference dynamically for both cases. In the first part dedicated to Femtocells and Macrocell coexistence, we design a MBS-assisted femtocell power adjustment strategy which takes into account femtocells users performance while mitigating the inter-cell interference on victim macrocell users. Further, we propose a new cooperative and context-aware interference mitigation method which is derived for realistic scenarios involving mobility of users and their varying locations. We proved numerically that the Femtocells are able to maintain their interference under a desirable threshold by adjusting their transmission power. Our strategies provide an efficient means for achieving the desired level of macrocell/femtocell throughput trade-off. In the second part of the studies where Picocells are deployed under the umbrella of the Macrocell, we paid a special attention and efforts to the interference management in the situation where Picocells are configured to set up a cell range expansion. We suggest a MBS-assisted collaborative scheme powered by an analytical model to predict the mobility of Macrocell users passing through the cell range expansion area of the picocell. Our goal is to adapt the muting ratio ruling the frequency resource partitioning between both tiers according to the mobility behavior of the range-expanded users, thereby providing an efficient trade-off between Macrocell and Picocell achievable throughputs

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Celma, Tirado Alberto. "New developments to refine target, suspect and non-target screening strategies for comprehensive monitoring of the aquatic environment". Doctoral thesis, Universitat Jaume I, 2021. http://dx.doi.org/10.6035/14104.2021.366313.

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The amount of organic micropollutants (OMP) currently being released to the aquatic environment is incommensurable. Thus, different analytical strategies were developed over the recent years to monitor the occurrence of OMP in environmental samples. In this thesis, different tools have been applied to refine target, suspect and non-target screening strategies for the monitoring of the aquatic environment with special emphasis on the hyphenation of ion mobility separation (IMS) to high resolution mass spectrometry. Additionally, the development of refinement tools for suspect screening strategies such as retention time indexing or in silico prediction of IMS data, as well as the implementation of effect-directed analysis for a comprehensive overview of the quality of water bodies have also been explored. Finally, the monitoring of new psychoactive substances in complex matrices such as influent wastewater and pooled urine samples is evaluated, with special aid of the previously developed tools.
La cantidad de microcontaminantes orgánicos (OMP) emitidos al medio ambiente acuático en la actualidad es incalculable. Por ello, se han desarrollado distintas estrategias analíticas para monitorizar la incidencia de OMP en muestras ambientales. En esta tesis se han aplicado diferentes herramientas para refinar estrategias de cribado dirigidas, de sospechosos y no dirigidas para la monitorización del medio ambiente acuático con especial énfasis en el acoplamiento de la separación por movilidad iónica (IMS) con espectrometría de masas de alta resolución. Adicionalmente, se ha explorado el desarrollo de herramientas de mejora para los cribados de sospechosos como, por ejemplo, indexación de tiempo de retención o predicción computacional de datos de IMS, así como la implementación de análisis basados en efecto (EDA) para una visión completa de la calidad de los cuerpos acuáticos. Finalmente, se ha evaluado la monitorización de Nuevas Sustancias Psicoactivas (NPS) en muestras complejas tales como aguas residuales y orina.
Programa de Doctorat en Ciències

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Saint-Guillain, Michael. "Models and algorithms for online stochastic vehicle routing problems". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI068.

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Quels seront les objectifs et défis des métropoles de demain ? La plupart des problèmes issus du monde réel sont sujets à l'inconnu, nécessitant de prendre de nouvelles décisions de façon dynamique, à la demande, en fonction des évènements aléatoires qui se réalisent. Dans cette thèse, nous nous attaquons à un problème majeur, du moins en perspectives: la gestion dynamique d'une flotte de véhicules en contexte urbain. Les applications pratiques des tournées de véhicules à la demande sont nombreuses, incluant les transports publics intelligents, les services de livraison, les soins et interventions à domicile, etc. Étant donnés une flotte de véhicules et un ensemble de clients, chacun pouvant potentiellement et à tout moment émettre une requête nécessitant une intervention, l'objectif de cette thèse est de fournir une réponse à la question suivante. Étant donné l'état courant à un moment donné, comment gérer notre flotte de véhicules afin de maximiser l'espérance du nombre total de requêtes satisfaites à la fin de la journée ? Ou encore, comment minimiser l'espérance du délai moyen d'intervention de nos véhicules ? Bien entendu, la difficulté réside en ce que la plupart des requêtes, avant d'apparaître dynamiquement, ne sont pas connues. Pour chaque problème, nous considérons qu'il nous est fourni une connaissance, sous forme d'information probabiliste, telle que la probabilité qu'une requête apparaisse à un certain endroit, et à un certain moment de la journée. Grâce à des techniques issues de la recherche opérationnelle et de la programmation stochastique, nous sommes en mesure de construire et résoudre des modèles calculant les actions anticipatives les plus adéquates, comme le redéploiement préventif des véhicules, minimisant le coût total espéré, ou encore maximisant la qualité de service. La question de l'optimisation sous incertitude se pose depuis déjà plusieurs décennies. Grâce aux avancées à la fois théoriques et technologiques, nous sommes chaque jour un peu plus en mesure de palier à l'inconnu. Cependant, la plupart des problèmes intéressants restent extrêmement difficiles à résoudre, si ce n'est impossible. Il reste beaucoup à faire. Cette thèse explore certains concepts fondamentaux de l'optimisation sous incertitude. En intégrant une composante stochastique aux modèles à optimiser, nous verrons ensemble comment il est en effet possible de créer de l'anticipation
What will be tomorrow's big cities objectives and challenges? Most of the operational problems from the real world are inherently subject to uncertainty, requiring the decision system to compute new decisions dynamically, as random events occur. In this thesis, we aim at tackling an important growing problem in urban context: online dynamic vehicle routing. Applications of online vehicle routing in the society are manyfold, from intelligent on demand public transportation to sameday delivery services and responsive home healthcare. Given a fleet of vehicles and a set of customers, each being potentially able to request a service at any moment, the current thesis aims at answering the following question. Provided the current state at some moment of the day, which are the best vehicle actions such that the expected number of satisfied requests is maximized by the end of the operational day? How can we minimize the expected average intervention delays of our mobile units? Naturally, most of the requests remain unknown until they appear, hence being revealed online. We assume a stochastic knowledge on each operational problem we tackle, such as the probability that customer request arise at a given location and a given time of the day. By using techniques from operations research and stochastic programming, we are able to build and solve mathematical models that compute near-optimal anticipative actions, such as preventive vehicle relocations, in order to either minimize the overall expected costs or maximize the quality of service. Optimization under uncertainty is definitely not a recent issue. Thanks to evolution of both theoretical and technological tools, our ability to face the unknown constantly grows. However, most of the interesting problems remain extremely hard, if not impossible, to solve. There is still a lot of work. Generally speaking, this thesis explores some fundamentals of optimization under uncertainty. By integrating a stochastic component into the models to be optimized, we will see how it is in fact possible to create anticipation

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Nuñez, del Prado Cortez Miguel. "Inference attacks on geolocated data". Thesis, Toulouse, INSA, 2013. http://www.theses.fr/2013ISAT0028/document.

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Au cours des dernières années, nous avons observé le développement de dispositifs connectéset nomades tels que les téléphones mobiles, tablettes ou même les ordinateurs portablespermettant aux gens d’utiliser dans leur quotidien des services géolocalisés qui sont personnalisésd’après leur position. Néanmoins, les services géolocalisés présentent des risques enterme de vie privée qui ne sont pas forcément perçus par les utilisateurs. Dans cette thèse,nous nous intéressons à comprendre les risques en terme de vie privée liés à la disséminationet collection de données de localisation. Dans ce but, les attaques par inférence que nousavons développé sont l’extraction des points d’intérêts, la prédiction de la prochaine localisationainsi que la désanonymisation de traces de mobilité, grâce à un modèle de mobilité quenous avons appelé les chaînes de Markov de mobilité. Ensuite, nous avons établi un classementdes attaques d’inférence dans le contexte de la géolocalisation se basant sur les objectifsde l’adversaire. De plus, nous avons évalué l’impact de certaines mesures d’assainissement àprémunir l’efficacité de certaines attaques par inférence. En fin nous avons élaboré une plateformeappelé GEoPrivacy Enhanced TOolkit (GEPETO) qui permet de tester les attaques parinférences développées
In recent years, we have observed the development of connected and nomad devices suchas smartphones, tablets or even laptops allowing individuals to use location-based services(LBSs), which personalize the service they offer according to the positions of users, on a dailybasis. Nonetheless, LBSs raise serious privacy issues, which are often not perceived by the endusers. In this thesis, we are interested in the understanding of the privacy risks related to thedissemination and collection of location data. To address this issue, we developed inferenceattacks such as the extraction of points of interest (POI) and their semantics, the predictionof the next location as well as the de-anonymization of mobility traces, based on a mobilitymodel that we have coined as mobility Markov chain. Afterwards, we proposed a classificationof inference attacks in the context of location data based on the objectives of the adversary.In addition, we evaluated the effectiveness of some sanitization measures in limiting the efficiencyof inference attacks. Finally, we have developed a generic platform called GEPETO (forGEoPrivacy Enhancing Toolkit) that can be used to test the developed inference attacks

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Kiss, Zoltan. "Predictive Mobility Management for future mobile telecommunication networks". Thesis, De Montfort University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391858.

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Tatar, Alexandru-Florin. "Predicting User-Centric Behavior : mobility and content popularity". Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066202/document.

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Comprendre le comportement des utilisateurs est fondamentale pour créer des systèmes de communication efficaces. Dévoiler les interactions complexes entre les utilisateurs dans le monde réel ou en ligne, déchiffrer leurs activité sur Internet, ou comprendre la mobilité humaine - toutes les formes des activités - peuvent avoir un impact direct sur la performance d'un réseau de communication. Mais l'observation du comportement de l'utilisateur n'est pas suffisant. Pour transformer l'information en connaissance utile, il faut cependant aller au-delà de l'observation et l' explication du passé et de créer des modèles permettant de prédire le comportement. Dans cette thèse, nous nous concentrons sur le cas des utilisateurs qui consomment du contenu dans leurs trajets quotidiens, en particulier lorsque la connectivité est faible ou intermittente. Nous considérons que les utilisateurs peuvent communiquer entre eux en utilisant l'infrastructure mais aussi directement en utilisant les communications opportunistes. Nous proposons de nouvelles perspectives sur la façon d'utiliser des information sur le comportement des utilisateurs dans la conception de solutions plus efficaces pour les communications mobiles opportunistes. En particulier, nous mettons en avant que le comportement des utilisateurs, à la fois en termes de consommation de contenu et les contacts entre les utilisateurs mobiles, peut être utilisé pour élaborer des stratégies dynamiques de réplication de données
Understanding user behavior is fundamental in the design of efficient communication systems. Unveiling the complex online and real-life interactions among users, deciphering online activity, or understanding user mobility patterns all forms of user activity have a direct impact on the performance of the network. But observing user behavior is not sufficient. To transform information in valuable knowledge, one needs however to make a step forward and go beyond observing and explaining the past to building models that will predict future behavior. In this thesis, we focus on the case of users consuming content on the move, especially when connectivity is poor or intermittent. We consider both traditional infrastructure-based communications and opportunistic device-to-device transfers between neighboring users. We offer new perspectives of how to use additional information about user behavior in the design of more efficient solutions for mobile opportunistic communications. In particular, we put forward the case that the collective user behavior, both in terms of content consumption and contacts between mobile users, can be used to build dynamic data replication strategies

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Tatar, Alexandru-Florin. "Predicting User-Centric Behavior : mobility and content popularity". Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066202.

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Comprendre le comportement des utilisateurs est fondamentale pour créer des systèmes de communication efficaces. Dévoiler les interactions complexes entre les utilisateurs dans le monde réel ou en ligne, déchiffrer leurs activité sur Internet, ou comprendre la mobilité humaine - toutes les formes des activités - peuvent avoir un impact direct sur la performance d'un réseau de communication. Mais l'observation du comportement de l'utilisateur n'est pas suffisant. Pour transformer l'information en connaissance utile, il faut cependant aller au-delà de l'observation et l' explication du passé et de créer des modèles permettant de prédire le comportement. Dans cette thèse, nous nous concentrons sur le cas des utilisateurs qui consomment du contenu dans leurs trajets quotidiens, en particulier lorsque la connectivité est faible ou intermittente. Nous considérons que les utilisateurs peuvent communiquer entre eux en utilisant l'infrastructure mais aussi directement en utilisant les communications opportunistes. Nous proposons de nouvelles perspectives sur la façon d'utiliser des information sur le comportement des utilisateurs dans la conception de solutions plus efficaces pour les communications mobiles opportunistes. En particulier, nous mettons en avant que le comportement des utilisateurs, à la fois en termes de consommation de contenu et les contacts entre les utilisateurs mobiles, peut être utilisé pour élaborer des stratégies dynamiques de réplication de données
Understanding user behavior is fundamental in the design of efficient communication systems. Unveiling the complex online and real-life interactions among users, deciphering online activity, or understanding user mobility patterns all forms of user activity have a direct impact on the performance of the network. But observing user behavior is not sufficient. To transform information in valuable knowledge, one needs however to make a step forward and go beyond observing and explaining the past to building models that will predict future behavior. In this thesis, we focus on the case of users consuming content on the move, especially when connectivity is poor or intermittent. We consider both traditional infrastructure-based communications and opportunistic device-to-device transfers between neighboring users. We offer new perspectives of how to use additional information about user behavior in the design of more efficient solutions for mobile opportunistic communications. In particular, we put forward the case that the collective user behavior, both in terms of content consumption and contacts between mobile users, can be used to build dynamic data replication strategies

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41

Mathews, Melissa. "Predicting Age Related Changes in Mobility and Driving Habits". TopSCHOLAR®, 2005. http://digitalcommons.wku.edu/theses/460.

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Older adults encounter many changes as they age, both cognitively and physically. These changes tend to impact one's mobility in terms of driving ability and exposure. It has been well documented that this population is increasing in number (Lyman, Ferguson, Braver, & Williams, 2002) and that they pose a higher crash risk than a younger population (Braver & Trempel, 2004; Dellinger, Kresnow, White, & Seghal, 2004; Tavris, Kuhn, & Layde, 2001). These cognitive and physical changes combined with increased crash risk lead a number of drivers to reduce the amount that they dri\ c or cease dri\ ing altogether, thereby limiting their independence. Some studies ha\e examined the domains on w hich these changes occur and have found that various medical conditions, cognitiv e deficits, and physical limitations lead to these changes in driving habits (Ball, Ow sley, Stalvey, Roenker, Sloane & Graves, 1998; Lyman, McGwin. & Sims, 2001). The present study sought to replicate a structural equation model proposed by Vance, Roenker, Cissell, Edwards, Wadley, and Ball (in press) in which it was found that a particular battery of tests (GRIMPS and UFOV) was predictive of both increased avoidance of certain situations and decreased exposure. Specifically, they found that the latent constructs of health and cognitive function were predictive of both exposure and avoidance. However, physical function appeared to make no contribution. The current study attempted to replicate this model on a sample ( N = 299) that participated as part of the driver's licensing process at three Motor Vehicle Administration sites in Maryland. It was found that this sample did decline over time in the areas of health, physical, and cognitive functionn. Also, they reduced the amount of driving that they did and increased their avoidance of many situations. However, the structural equation model for this sample found the latent construct of physical functioning to be the only significant predictor of driving avoidance and exposure.

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42

au, Knebworth@iinet net, i Iain Cameron. "Understanding, modelling and predicting transport mobility in urban environments". Murdoch University, 2004. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20050513.141512.

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In the last three decades the global population has been growing at an essentially constant rate, at around 1.5 per cent per year, to about 6.026 billion in 2000 when it was estimated that 47% of that population live in an urban environment. Further, a United Nations projection indicates that 60% of the total global population may be living in an urban settlement by the year 2025. This increasing urbanisation brings with it increased employment, that delivers affluence, which then continues the cycle of migration and movement to these growing metropolitan areas in both developed and developing countries. As cities increase in population and expand their urban area, there is a consequential expansion of urban transportation and accompanying service infrastructure. People travel daily, irrespective of their vast differences in culture, economic conditions and means of transportation. This daily mobility is sought for its own sake as well as to bridge the spatial distance that separates their homes from the work place, to accomplish their households domestic needs and to undertake social journeys, such as visiting friends and taking holidays. As the worlds urban population undertakes its daily mobility by a variety of transportation modes, an individuals mobility behaviour and mode-choice is governed by a complex matrix of physical and human, social and management indicators, measures and/or drivers. A literature review describes the current understanding of this complex matrix and concludes by identifying and defining a set of fundamental underlying measures that drive private motorised, public transport and non-motorised (walking and bicycling) mobility at national, city and household levels. As practical instruments, transportation models play an important role in providing decision-makers with analytical tools to help them understand their citys transportation and the different future scenarios it may face. While not necessarily producing foolproof information or predictions, models are still the best methods available to test the likely implications of alternative transportation policy decisions in a rapidly changing urban environment. Urban transport models are generally based on the notion that traffic can be modelled in aggregate measures through statistical data and predictive modelling techniques. In this research, dimensional analysis is used to derive sketch-plan models for private motorised, public transport and non-motorised mobility for any urban environment based on four-decades of detailed land-use and travel pattern data from a large international sample of cities. These models are developed on the basis of a set of fundamental underlying measures that are deemed to drive private motorised, public transport and non-motorised (walking and bicycling) mobility at the city level. Importantly, the models also embody three key attributes. They are: easy to use, minimising user requirements and data inputs policy-sensitive, capable of assessing a sufficient range of policy options reliable and robust over time, so that the results can be consistently believed. The capacity of the sketch-plan models to predict personal mobility in an urban environment is statistically validated against an independent land-use and travel pattern data set for 83 cities located on five continents. Despite their simplicity and maintaining a consistent functional form over a time-series of four-decades and across all geographic and cultural regions, the private motorised mobility model can consistently explain up to 92% of the variance in private motorised urban mobility. The results for the public transport mobility model are less reliable and consistent, in particular when developing cities are part of the model. Results for developed or wealthier cities are much better. Reasons for these results and their inadequacies are discussed. The non-motorised modes mobility model is the least successful part of the modelling work. This can be attributed to a combination of inadequate data and, very likely, the more micro-level determinants of usage of these modes. The private motorised urban mobility sketch-plan model equation developed in this thesis is able to predict present and future trends of automobile use in individual cities to a high degree of statistical reliability. The model equation offers urban transport planners a focused direction on the fundamental measures that have the potential to control and deliver automobile restraint policies and strategies. A series of case studies shows that this model has wide applications in understanding past trends in private motorised mobility and in developing urban environmental strategy and policy through its ability to calculate and assess current and future motor vehicle emissions inventories in cities. The thesis makes suggestions for future work in this area of metropolitan level transport modelling, in particular, how to improve the public and non-motorised transport models so that total urban transport mobility can be better understood and modelled.

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43

Cameron, Iain. "Understanding, modelling and predicting transport mobility in urban environments". Thesis, Cameron, Iain (2004) Understanding, modelling and predicting transport mobility in urban environments. PhD thesis, Murdoch University, 2004. https://researchrepository.murdoch.edu.au/id/eprint/499/.

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In the last three decades the global population has been growing at an essentially constant rate, at around 1.5 per cent per year, to about 6.026 billion in 2000 when it was estimated that 47% of that population live in an urban environment. Further, a United Nations' projection indicates that 60% of the total global population may be living in an urban settlement by the year 2025. This increasing urbanisation brings with it increased employment, that delivers affluence, which then continues the cycle of migration and movement to these growing metropolitan areas in both developed and developing countries. As cities increase in population and expand their urban area, there is a consequential expansion of urban transportation and accompanying service infrastructure. People travel daily, irrespective of their vast differences in culture, economic conditions and means of transportation. This daily mobility is sought for its own sake as well as to bridge the spatial distance that separates their homes from the work place, to accomplish their household's domestic needs and to undertake social journeys, such as visiting friends and taking holidays. As the world's urban population undertakes its daily mobility by a variety of transportation modes, an individual's mobility behaviour and mode-choice is governed by a complex matrix of physical and human, social and management indicators, measures and/or drivers. A literature review describes the current understanding of this complex matrix and concludes by identifying and defining a set of fundamental underlying measures that drive private motorised, public transport and non-motorised (walking and bicycling) mobility at national, city and household levels. As practical instruments, transportation models play an important role in providing decision-makers with analytical tools to help them understand their city's transportation and the different future scenarios it may face. While not necessarily producing foolproof information or predictions, models are still the best methods available to test the likely implications of alternative transportation policy decisions in a rapidly changing urban environment. Urban transport models are generally based on the notion that traffic can be modelled in aggregate measures through statistical data and predictive modelling techniques. In this research, dimensional analysis is used to derive sketch-plan models for private motorised, public transport and non-motorised mobility for any urban environment based on four-decades of detailed land-use and travel pattern data from a large international sample of cities. These models are developed on the basis of a set of fundamental underlying measures that are deemed to drive private motorised, public transport and non-motorised (walking and bicycling) mobility at the city level. Importantly, the models also embody three key attributes. They are: * easy to use, minimising user requirements and data inputs * policy-sensitive, capable of assessing a sufficient range of policy options * reliable and robust over time, so that the results can be consistently believed. The capacity of the sketch-plan models to predict personal mobility in an urban environment is statistically validated against an independent land-use and travel pattern data set for 83 cities located on five continents. Despite their simplicity and maintaining a consistent functional form over a time-series of four-decades and across all geographic and cultural regions, the private motorised mobility model can consistently explain up to 92% of the variance in private motorised urban mobility. The results for the public transport mobility model are less reliable and consistent, in particular when developing cities are part of the model. Results for developed or wealthier cities are much better. Reasons for these results and their inadequacies are discussed. The non-motorised modes mobility model is the least successful part of the modelling work. This can be attributed to a combination of inadequate data and, very likely, the more micro-level determinants of usage of these modes. The private motorised urban mobility sketch-plan model equation developed in this thesis is able to predict present and future trends of automobile use in individual cities to a high degree of statistical reliability. The model equation offers urban transport planners a focused direction on the fundamental measures that have the potential to control and deliver automobile restraint policies and strategies. A series of case studies shows that this model has wide applications in understanding past trends in private motorised mobility and in developing urban environmental strategy and policy through its ability to calculate and assess current and future motor vehicle emissions inventories in cities. The thesis makes suggestions for future work in this area of metropolitan level transport modelling, in particular, how to improve the public and non-motorised transport models so that total urban transport mobility can be better understood and modelled.

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44

Cameron, Iain. "Understanding, modelling and predicting transport mobility in urban environments". Cameron, Iain (2004) Understanding, modelling and predicting transport mobility in urban environments. PhD thesis, Murdoch University, 2004. http://researchrepository.murdoch.edu.au/499/.

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In the last three decades the global population has been growing at an essentially constant rate, at around 1.5 per cent per year, to about 6.026 billion in 2000 when it was estimated that 47% of that population live in an urban environment. Further, a United Nations' projection indicates that 60% of the total global population may be living in an urban settlement by the year 2025. This increasing urbanisation brings with it increased employment, that delivers affluence, which then continues the cycle of migration and movement to these growing metropolitan areas in both developed and developing countries. As cities increase in population and expand their urban area, there is a consequential expansion of urban transportation and accompanying service infrastructure. People travel daily, irrespective of their vast differences in culture, economic conditions and means of transportation. This daily mobility is sought for its own sake as well as to bridge the spatial distance that separates their homes from the work place, to accomplish their household's domestic needs and to undertake social journeys, such as visiting friends and taking holidays. As the world's urban population undertakes its daily mobility by a variety of transportation modes, an individual's mobility behaviour and mode-choice is governed by a complex matrix of physical and human, social and management indicators, measures and/or drivers. A literature review describes the current understanding of this complex matrix and concludes by identifying and defining a set of fundamental underlying measures that drive private motorised, public transport and non-motorised (walking and bicycling) mobility at national, city and household levels. As practical instruments, transportation models play an important role in providing decision-makers with analytical tools to help them understand their city's transportation and the different future scenarios it may face. While not necessarily producing foolproof information or predictions, models are still the best methods available to test the likely implications of alternative transportation policy decisions in a rapidly changing urban environment. Urban transport models are generally based on the notion that traffic can be modelled in aggregate measures through statistical data and predictive modelling techniques. In this research, dimensional analysis is used to derive sketch-plan models for private motorised, public transport and non-motorised mobility for any urban environment based on four-decades of detailed land-use and travel pattern data from a large international sample of cities. These models are developed on the basis of a set of fundamental underlying measures that are deemed to drive private motorised, public transport and non-motorised (walking and bicycling) mobility at the city level. Importantly, the models also embody three key attributes. They are: * easy to use, minimising user requirements and data inputs * policy-sensitive, capable of assessing a sufficient range of policy options * reliable and robust over time, so that the results can be consistently believed. The capacity of the sketch-plan models to predict personal mobility in an urban environment is statistically validated against an independent land-use and travel pattern data set for 83 cities located on five continents. Despite their simplicity and maintaining a consistent functional form over a time-series of four-decades and across all geographic and cultural regions, the private motorised mobility model can consistently explain up to 92% of the variance in private motorised urban mobility. The results for the public transport mobility model are less reliable and consistent, in particular when developing cities are part of the model. Results for developed or wealthier cities are much better. Reasons for these results and their inadequacies are discussed. The non-motorised modes mobility model is the least successful part of the modelling work. This can be attributed to a combination of inadequate data and, very likely, the more micro-level determinants of usage of these modes. The private motorised urban mobility sketch-plan model equation developed in this thesis is able to predict present and future trends of automobile use in individual cities to a high degree of statistical reliability. The model equation offers urban transport planners a focused direction on the fundamental measures that have the potential to control and deliver automobile restraint policies and strategies. A series of case studies shows that this model has wide applications in understanding past trends in private motorised mobility and in developing urban environmental strategy and policy through its ability to calculate and assess current and future motor vehicle emissions inventories in cities. The thesis makes suggestions for future work in this area of metropolitan level transport modelling, in particular, how to improve the public and non-motorised transport models so that total urban transport mobility can be better understood and modelled.

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45

Yin, ChengXin. "Predictive Simulation for the Design of Robotic Device for Mobility-Aid". Electronic Thesis or Diss., Bourges, INSA Centre Val de Loire, 2020. http://www.theses.fr/2020ISAB0007.

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Dans cette thèse, nous avons proposé une méthodologie pour aider dans la conception d'un exosquelette robotique. En effet, le travail principal est d'aider le concepteur à sélectionner les comportements dynamiques adéquats des mouvements induit par un exosquelette pour une personne à mobilité réduite. En ajustant les paramètres de chaque actionneur, les tâches de mouvement humain peuvent être assistées par l'application d'une aide à la mobilité robotisée via une interaction hommerobot. Il n'y aura qu'un seul groupe de paramètres d'actionneurs les plus appropriés créés par optimisation pour une locomotion humaine particulière. Sur la base des résultats optimisés, nous sommes en mesure d'interpréter l'interaction homme-robot pour proposer une conception de variables de contrôle pour une tâche de mouvement spécifiée. La première étape de cette méthode consiste à mettre en œuvre la modélisation neuromusculosquelettique (NMS) et la simulation, pour mieux décrire les caractéristiques dynamiques humaines. Cette étape peut illustrer les natures physiologiques du corps humain sous la forme de «Actionneur Musculaire - Accélération -Trajectoire» pendant une période de mouvement. Par exemple, on peut rechercher la fonction des muscles dans l'actionnement de la locomotion humaine grâce à une simulation de la poursuite de trajectoire. En outre, des cas de simulation ont été créés pour évaluer de nouveaux mouvements et adaptations à différentes conditions. La mise en œuvre de la simulation prédictive le rend possible: ce quiconstitue également la deuxième étape de notre étude. Pour réaliser les prédictions, elles doivent d'abord formuler notre problèmes de contrôle optimal puis le résoudre par des algorithmes numériques. Une interface de programmation applicable (API) àOpenSim-Matlab a été utilisée pour intégrer un solveur numérique et discrétiser les problèmes et résoudre les processus. Ces propositions ont été validées via une étude de cas d'aide à la mobilité robotique, le système humainESTA. ESTA est un exosquelette conçu pour compenser les degrés de liberté (DOF) du bras de l'utilisateur. L'humanoïde NMS a été modélisé comme un membre supérieur d'un côté. Les effets d'interaction entre l'humain et le dispositif ont été considérés comme les actionneurs virtuels équivalents qui fournissent des forces et moments ajustés pour des articulations humaines particulières. Un problème de contrôle optimal a été formulé pour représenter les simulations prédictives. Ensuite, nous avons également testé une variété de variables de contrôle optimales afin de prédire les situations «What if» . Des données expérimentales ont été collectées pour valider les systèmes ainsi que pour fixer les trajectoires référencées aux prédictions. Les résultats montrent que notre méthode pour proposer un modèle d'actionnement pour un exosquelette robotique est prometteuse et permet de préciser le mouvement humain par une tâche donnée
In this thesis, we have proposed a methodology on design of the robotic exoskeleton. The main work is to help the designer to select adequate dynamical behaviors of the movements induced by an exoskeleton for a person with reduced mobility. Hence by adjusting the parameters for each actuator, the human motion tasks can be assisted by the robotic mobilityaid application via human-device interaction. There is only one group of the most suitable actuator parameters created via optimization for a particular human locomotion. Based on the optimized results, we are able to interpret the human-device interaction as well as to propose the design of control variables for a specified motion task. The first stage of this method consists of the implementation of the neuromusculoskeletal (NMS) modeling and simulation, which is for better describing the human dynamical characteristics. This stage can illustrate the physiological natures of human bodies in the form of 'Muscular ActuatorAcceleration-Trajectory' during a period of motion. For instance, one can search the function of muscles in actuating human locomotion through a motion-tracking simulation. Besides, the 'what if' cases were created to evaluate novel movements and adaptions to different conditions. The implementation of predictive simulation makes it feasible : which also constitutes thesecond stage of our study. To fulfill the predictions, we have to formulate our problems as optimal control processes and then solve them by numerical algorithms. Here, an OpenSimMatlab applicable programming interface (API) was modeled to embed a numerical solver and discretize the problems and solve the processes. These propositions have been validated via a case-study of robotic mobility-aid, the human-ESTA system. ESTA is an exoskeleton designed for compensating degrees-of-freedom (dofs) of the user's arm. The NMS humanoid was modeled as one-side upper extremity limb. Interaction effects between the human and device were considered as the equivalent virtual actuators which provide adjusted forces and moments for particular human joints. An optimal control problem was set to represent the predictive simulations. We also tested a variety of the optimal control variables in order to predict the 'what if' situations. Experimental data were collected for validating the systems as well as setting the referred trajectories to the predictions. Results showthat our method for proposing an actuating pattern for a robotic exoskeleton is promising and allowed to specify the human movement for a given task

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46

Moro, Lorenzo. "Structure borne noise due to marine diesel engines: experimental study and numerical simulation for the prediction of the dynamic behaviour of resilient mounts". Doctoral thesis, Università degli studi di Trieste, 2015. http://hdl.handle.net/10077/11114.

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2013/2014
Gli alti livelli di comfort che sono richiesti oggigiorno a bordo di navi da crociera e mega-yachts, portano i progettisti a concentrare la loro attenzione sul problema del rumore strutturale. I motori diesel quattro tempi che sono installati a bordo nave come motori principali o diesel generatori, sono tra le principali sorgenti di rumore strutturale. Per questa ragione, al fine di ridurre l’energia vibrazionale generata da queste sorgenti e trasmessa, tramite le strutture nave, ai locali alloggio, i motori diesel sono sospesi mediante elementi resilienti. Tali elementi resilienti disaccoppiano la sorgente di rumore e vibrazioni (motore diesel) dal mezzo di propagazione (le strutture nave) e isolano dunque la sorgente dalle strutture riceventi. I livelli di rumore strutturale misurati alle fondazioni del motore diesel dipendono dai livelli di velocità misurati sulla sorgente (cioè ai piedi del motore diesel), dai livelli di impedenza meccanica degli elementi resilienti e dai livelli di mobilità meccanica delle fondazioni del motore diesel. Il single-point approach è un approccio semplificato per la previsione dei livelli di rumore strutturale che trascura l’interazione tra elementi resilienti. Secondo tale teoria, al fine di ridurre il rumore strutturale trasmesso attraverso gli elementi resilienti alle strutture nave, si deve ridurre l’impedenza meccanica degli elementi resilienti così come la mobilità meccanica delle fondazioni del motore diesel. In altre parole, si devono aumentare la rigidezza dinamica degli elementi resilienti così come l’impedenza meccanica delle fondazioni del motore diesel. Ad oggi, l’impedenza meccanica degli elementi resilienti può essere ricavata solo mediante prove sperimentali in laboratorio, mentre la mobilità meccanica del motore diesel è solitamente misurata quando la nave è in costruzione. Dunque non vi è la possibilità di predire, in fase progettuale, il rumore strutturale dovuto ai motori diesel. In questa tesi, viene presentata una procedura per la simulazione del rumore strutturale dovuto a motori diesel marini. La procedura si basa su test sperimentali e simulazioni numeriche. Nella prima parte della tesi sono richiamate le basi teoriche necessarie per l’esecuzione delle procedure numeriche e delle prove sperimentali. Sono dunque presentati i risultati delle analisi numeriche per simulare la mobilità delle fondazioni dei motori diesel marini. I risultati delle analisi FEM sono stati validati mediante confronto dei risultati delle analisi numeriche con i dati ottenuti da una campagna di misure eseguite a bordo nave. Successivamente sono presentati i risultati di una serie di prove eseguite per collaudare una nuova macchina sperimentale per misurare l’impedenza meccanica degli elementi resilienti. Lo scopo del collaudo era definire una procedura per l’utilizzo della macchina e per l’esecuzione di prove sperimentali in accordo alla ISO 10846, che è considerata normativa di riferimento per questo tipo di prove. Si è dunque proceduto con l’esecuzione di prove sperimentali eseguite su un elemento resiliente per motori diesel marini. Le prove sono state eseguite a differenti carichi statici. I risultati di queste prove sperimentali sono stati utilizzati per settare un modello numerico che simuli il comportamento non-lineare del componente in gomma del resiliente. I risultati ottenuti sia dalle prove sperimentali sia dalle simulazioni numeriche sono stati utilizzati per predire il rumore strutturale generato dai motori diesel, in accordo al single-point approach. I risultati ottenuti dall’applicazione del metodo sono stati confrontati con misure eseguite a bordo e sono stati discussi per evidenziare vantaggi e svantaggi dell’applicazione del metodo. Le procedure numeriche per la simulazione del comportamento dinamico del resiliente e della fondazione costituiscono un primo passo per l’ottimizzazione del sistema di isolazione del motore diesel marino.
The high level of comfort that is required today on board cruise vessels and mega-yachts, leads the designers to focus their attention on structure-borne noise issues. Four-stroke diesel engines that are installed on board as main diesel engines for the propulsion system and as gen-sets, are usually the main sources of structure-borne noise. For this reason, the diesel engines are usually resiliently mounted in order to reduce the vibration energy generated by these sources and transmitted through the ship structures to the accommodation areas. These mounts decouple the noise and vibration source (diesel engine) from the means of wave propagation (ship structures) and so, they isolate the source from the receiving structures. The structure-borne noise levels measured at the diesel engine foundation depend on the velocity levels measured at the source (diesel engine feet), on the mechanical impedance levels of the resilient mounts and on the mechanical mobility levels of the diesel engine foundation. The simplified theory of the single-point approach neglects the interaction among the resilient mounts. According to this theory, to decrease the structure-borne noise transmitted through the resilient mounts towards the ship structures, the mechanical impedance of the resilient mounts as well as the mechanical mobility of the diesel engine foundation are to be lowered. In other words the dynamic stiffness of the resilient mounts has to be decreased and the mechanical impedance of the diesel engine foundation has to be increased. To date, the mechanical impedance of real resilient mounts can only be obtained by laboratory tests and the mechanical mobility of the diesel engine foundation is usually measured when the ship is under construction, so it is not available for predictive analyses. In the thesis, a procedure for simulating the structure-borne noise generated by marine diesel engine is discussed. The procedure is based on both experimental tests and numerical simulations. In the first part of the thesis, some notes on the theoretical background are presented. Then, the results of FE analyses for simulating the mechanical mobility of a diesel engine foundation are shown. The FE models have been validated by the results of a measurement campaign carried out on board a ship. Then, the results of a series of tests performed to tune a new test rig, designed and built up at the University of Trieste for measuring the mechanical impedance of resilient mounts, are discussed. The campaign for tuning the test rig has been carried out in order to set an experimental procedure that allows achieving results in compliance with the ISO 10846 Standard, which is a sound reference for this kind of tests. As a case study, a large resilient mount for marine diesel engines has been tested to achieve its mechanical impedance curve at different static pre-loads. The outcomes of the experimental tests have been used for tuning the best numerical model of the resilient mount that properly takes into account the nonlinear behaviour of the rubber core. The data of the experimental tests carried out on board ships as well as in laboratory and the outcomes of numerical simulations have been used to predict the structure-borne noise according to the single-point approach. The outcomes achieved by the application of the method have been compared with on board measurements and pros and cons of the method are widely discussed. Moreover, the numerical procedures for the simulation of the dynamic behaviour of the resilient mount and the diesel engine foundation, pave the way for the optimization of the decoupling system of marine diesel engines.
XXVII Ciclo
1982

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47

Liu, Yuanyang. "Predicting labor market competition and employee mobility — a machine learning approach". Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6977.

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Applying data analytics for talent acquisition and retention has been identified as one of the most urgent challenges facing HR leaders around the world; however, it is also one of the challenges that firms are least prepared to tackle. Our research strives to narrow such a capability gap between the urgency and readiness of data-driven human resource management. First, we predict interfirm competitors for human capital in the labor market utilizing the rich information contained in over 89,000 LinkedIn users' profiles. Using employee migrations across firms, we derive and analyze a human capital flow network. We leverage this network to extract global cues about interfirm human capital overlap through structural equivalence and community classification. The online employee profiles also provide rich data on the explicit knowledge base of firms and allow us to measure the interfirm human capital overlap in terms of similarity in their employees' skills. We validate our proposed human capital overlap metrics in a predictive analytics framework using future employee migrations as an indicator of labor market competition. The results show that our proposed metrics have superior predictive power over conventional firm-level economic and human resource measures. Second, we estimate the effect of skilled immigrants on the native U.S. workers' turnover probability. We apply unsupervised machine learning to categorize employees' self-reported skills and find that skilled immigrants disproportionately specialize in IT. In contrast, the native workers predominantly focus on management and analyst skills. Utilizing the randomness in the H-1B visa lottery system and a 2SLS design, we find that a 1 percentage point increase in a firm's proportion of skilled immigrant employees leads to a decrease of 0.69 percentage points in a native employee's turnover risk. However, this beneficial crowding-in effect varies for native workers with different skills. Our methodology highlights the need to account for a multifaceted view of the skilled immigration's effect on native workers. Finally, we also propose a set of features and models that are able to effectively predict future employee turnover outcomes. Our predictive models can provide significant utility to managers by identifying individuals with the highest turnover risks.

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48

Dakin, John D. "Using experimental loads with finite element analysis for durability predictions". Thesis, Loughborough University, 1995. https://dspace.lboro.ac.uk/2134/10407.

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This research work involved the prediction of the fatigue life of an automotive rear suspension twistbeam assembly fitted to a vehicle travelling over a customer correlated durability route. This was achieved by making use of the integrated concepts of scaling and superposition of linear static finite element analysis being driven by experimental load data - the so called 'quasi-static time domain' approach. A study of the free body diagram of the twistbeam resulted in an indeterminate load set of some 24 components, with experimental data indicating that a state of static unbalance existed. Subsequent to developing a matrix-based generalised method ofload cell calibration to confum the foregoing, a modal technique was developed to partition the experimental data into a static load set, causing elastic deformations, and a rigid load set, imparting rigid body accelerations. The semi-independent characteristics of the twistbeam necessitated the coupling of large structural displacements with inertia relief. This required extensive modifications to the current techniques and led to the development and use of a three dimensional functional response matrix in place of the conventional two dimensional one. Recommendations concerning appropriate finite element boundary conditions were also formulated to handle these effects. Finally, the limitations of the uniaxial fatigue model were revealed under the application of a set of tools for analysing the biaxiality and mobility of the maximum absolute principal stress.

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Teater, Barbra A. "Residential mobility and the Section 8 Housing Choice Voucher Program factors predicting mobility and the residential decision-making process of recipients /". Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1164641312.

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Lamprecht, Andreas. "Energieprädiktion und Reichweitendarstellung durch Navigationsdaten im Kraftfahrzeug". Doctoral thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-213218.

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Im Zuge der immer größer werdenden Knappheit fossiler Ressourcen und des damit verbundenen Anstiegs des Rohölpreises ergibt sich ein Trend hin zur Elektromobilität. In den nächsten Jahren werden jedoch nur Elektrofahrzeuge mit deutlich eingeschränkter maximaler Reichweite im Vergleich zu Benzin- oder Dieselfahrzeugen produziert werden können. Um den täglichen Umgang des Kunden mit einem Elektrofahrzeug trotzdem möglichst reibungslos zu ermöglichen, wurde im Rahmen dieser Arbeit eine neuartige Anzeige der verbleibenden Reichweite auf der Navigationskarte entwickelt. Nach detaillierter Analyse vorhandener Ansätze wurde je ein empirisches und ein modellbasiertes Verfahren ausgearbeitet. Die Ansätze wurden systematisch verglichen und zu einem komplett neuartigen, hybriden Ansatz kombiniert. Die auftretenden Verbräuche des Fahrzeugs werden im Kundenbetrieb erfasst, je nach Fahrsituation klassifiziert und für eine Extrapolation in der Zukunft verwendet. Die entwickelte Methodik zur Untersuchung der erreichbaren Genauigkeit ergab ein erzielbares Fehlermaß von durchschnittlich unter 10%
Due to the prospect of a worldwide shortage of fossil fuels and the correlated increase of prices for crude-oil, a global trend to invest in electric mobility has started. During the next couple of years, electric vehicles will still have restrictions on the maximum distance that can be driven before having the need to recharge the battery. The potential costumers face the so-called „range-anxiety“, the fear to be stranded prior to reaching the destination. In order to provide a safe and easy way of operating such a vehicle, the work conducted in the course of this doctoral thesis led to a new way of displaying the remaining range of the vehicle on a navigation map. After detailed analysis of the state of the art, an empirical- and a model-based solution for calculating the remaining range were developed utilizing predictive map-data from a roadnetwork. After a systematical optimization of the developed solutions, an embedded prototype was developed which captured the driving situation of the vehicle together with the corresponding energy-consumption in order to provide a context-aware interpolation of the remaining range, depending on where the costumer would drive next. A developed methodology of objectively determining the error produced by the system resulted in a mean-deviation of 10% of absolute value

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