Dissertations / Theses: 'Analysis crowd'

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Mehran, Ramin. "Analysis of behaviors in crowd videos." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4801.

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In this dissertation, we address the problem of discovery and representation of group activity of humans and objects in a variety of scenarios, commonly encountered in vision applications. The overarching goal is to devise a discriminative representation of human motion in social settings, which captures a wide variety of human activities observable in video sequences. Such motion emerges from the collective behavior of individuals and their interactions and is a significant source of information typically employed for applications such as event detection, behavior recognition, and activity recognition. We present new representations of human group motion for static cameras, and propose algorithms for their application to variety of problems. We first propose a method to model and learn the scene activity of a crowd using Social Force Model for the first time in the computer vision community. We present a method to densely estimate the interaction forces between people in a crowd, observed by a static camera. Latent Dirichlet Allocation (LDA) is used to learn the model of the normal activities over extended periods of time. Randomly selected spatio-temporal volumes of interaction forces are used to learn the model of normal behavior of the scene. The model encodes the latent topics of social interaction forces in the scene for normal behaviors. We classify a short video sequence of $n$ frames as normal or abnormal by using the learnt model. Once a sequence of frames is classified as an abnormal, the regions of anomalies in the abnormal frames are localized using the magnitude of interaction forces. The representation and estimation framework proposed above, however, has a few limitations. This algorithm proposes to use a global estimation of the interaction forces within the crowd. It, therefore, is incapable of identifying different groups of objects based on motion or behavior in the scene. Although the algorithm is capable of learning the normal behavior and detects the abnormality, but it is incapable of capturing the dynamics of different behaviors. To overcome these limitations, we then propose a method based on the Lagrangian framework for fluid dynamics, by introducing a streakline representation of flow. Streaklines are traced in a fluid flow by injecting color material, such as smoke or dye, which is transported with the flow and used for visualization. In the context of computer vision, streaklines may be used in a similar way to transport information about a scene, and they are obtained by repeatedly initializing a fixed grid of particles at each frame, then moving both current and past particles using optical flow. Streaklines are the locus of points that connect particles which originated from the same initial position. This approach is advantageous over the previous representations in two aspects: first, its rich representation captures the dynamics of the crowd and changes in space and time in the scene where the optical flow representation is not enough, and second, this model is capable of discovering groups of similar behavior within a crowd scene by performing motion segmentation. We propose a method to distinguish different group behaviors such as divergent/convergent motion and lanes using this framework. Finally, we introduce flow potentials as a discriminative feature to recognize crowd behaviors in a scene. Results of extensive experiments are presented for multiple real life crowd sequences involving pedestrian and vehicular traffic. The proposed method exploits optical flow as the low level feature and performs integration and clustering to obtain coherent group motion patterns. However, we observe that in crowd video sequences, as well as a variety of other vision applications, the co-occurrence and inter-relation of motion patterns are the main characteristics of group behaviors. In other words, the group behavior of objects is a mixture of individual actions or behaviors in specific geometrical layout and temporal order. We, therefore, propose a new representation for group behaviors of humans using the inter-relation of motion patterns in a scene. The representation is based on bag of visual phrases of spatio-temporal visual words. We present a method to match the high-order spatial layout of visual words that preserve the geometry of the visual words under similarity transformations. To perform the experiments we collected a dataset of group choreography performances from the YouTube website. The dataset currently contains four categories of group dances. ID: 031001560; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Title from PDF title page (viewed August 26, 2013).; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 100-104). Ph.D. Doctorate Electrical Engineering and Computer Science Engineering and Computer Science Electrical Engineering

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Jan, Yasir. "Novel architectures for spectator crowd image analysis." Thesis, Jan, Yasir (2020) Novel architectures for spectator crowd image analysis. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/59147/.

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Crowd image analysis can involve various tasks, such as head detection, head pose estimation, and body detection. These tasks face a range of issues including low resolution, varying crowd density, overlapping bodies, and image corruptions. Additionally, the techniques performing these tasks have computational overhead as well. Existing head detection techniques perform poorly for very low-resolution images. They also cannot perform head detection and head pose estimation simultaneously for multiple heads. To address these issues, we propose a novel neural network architecture (WNet), which performs joint tasks on low-resolution multiple heads. Experiments on the spectator crowd dataset (S-HOCK) show that fewer images can be used for the simultaneous tasks. Existing body detection techniques rely on the visibility of body parts. But in dense spectator crowd images, the bodies are occluded, and not visible clearly. We propose “pixel matching based body detection” (PMBD) technique, to reduce the eﬀect of occlusion in body parts. It can locate the body region by color matching and proximity. Experiments are performed on the S-HOCK dataset to accurately detect occluded bodies in a crowd image. When low-resolution images, such as spectator head images, get distorted with corrup-tions e.g. blurriness, pixelation, and fog, they are poorly classiﬁed by the neural networks. Existing robustness techniques aim towards a speciﬁc type of corruption and improve the accuracy. We propose a novel technique, called “Edge to edge scanline smoothing” (ESS), for image enhancement to mitigate the eﬀect of a wide range of corruption. Training of neural networks is a computationally extensive task. The proposed structure of neurons called the “Multiple Output Neurons” (MON), in contrast to conventional single output neurons, can be used in the training process to reduce computation in the neural networks. We demonstrate a reduction in computation for various tasks, such as spectator crowd head pose classiﬁcation.

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Holmer, Torsten, and Jörg Rainer Noennig. "Listening to the Crowd." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234390.

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In der Stadtplanung hat sich in der jüngeren Vergangenheit Partizipation als neues Paradigma durchgesetzt. Projektentwickler, Planer und Politiker haben erkannt, dass Bauprojekte mit großem Einfluss auf Stadtgesellschaft und Stadtentwicklung nicht mehr ohne umfassende Bürgerbeteiligung durchgeführt werden können. Vorfälle wie die Unruhen um das Bahnhofsprojekt Stuttgart 21 haben gezeigt, dass die regulären Verfahren der Bauleitplanung mit ihren Instrumenten der formalen Bürgerbeteiligung (Anzeige und Auslage von Planungsunterlagen) nicht ausreichen, um einen gesellschaftlichen Konsens zu kontroversen Projekten zu erzielen. Die Problematik lässt sich zu einem großen Teil auf das sogenannte „Planungsparadox“ zurückführen: dezidierte Meinungen und Kritik aus der Bevölkerung bilden sich oft erst, wenn das jeweilige Projekt zur Ausführung kommt und konkrete Formen annimmt – also wenn die Planungen bereits abgeschlossen sind und jegliche weitere Änderung mit erheblichen Aufwendungen verbunden ist. [... aus dem Text]

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Holmer, Torsten, and Jörg Rainer Noennig. "Listening to the Crowd." TUDpress, 2017. https://tud.qucosa.de/id/qucosa%3A30888.

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In der Stadtplanung hat sich in der jüngeren Vergangenheit Partizipation als neues Paradigma durchgesetzt. Projektentwickler, Planer und Politiker haben erkannt, dass Bauprojekte mit großem Einfluss auf Stadtgesellschaft und Stadtentwicklung nicht mehr ohne umfassende Bürgerbeteiligung durchgeführt werden können. Vorfälle wie die Unruhen um das Bahnhofsprojekt Stuttgart 21 haben gezeigt, dass die regulären Verfahren der Bauleitplanung mit ihren Instrumenten der formalen Bürgerbeteiligung (Anzeige und Auslage von Planungsunterlagen) nicht ausreichen, um einen gesellschaftlichen Konsens zu kontroversen Projekten zu erzielen. Die Problematik lässt sich zu einem großen Teil auf das sogenannte „Planungsparadox“ zurückführen: dezidierte Meinungen und Kritik aus der Bevölkerung bilden sich oft erst, wenn das jeweilige Projekt zur Ausführung kommt und konkrete Formen annimmt – also wenn die Planungen bereits abgeschlossen sind und jegliche weitere Änderung mit erheblichen Aufwendungen verbunden ist. [... aus dem Text]

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Guler, Puren. "Automated Crowd Behavior Analysis For Video Surveillance Applications." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614659/index.pdf.

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Automated analysis of a crowd behavior using surveillance videos is an important issue for public security, as it allows detection of dangerous crowds and where they are headed. Computer vision based crowd analysis algorithms can be divided into three groups people counting, people tracking and crowd behavior analysis. In this thesis, the behavior understanding will be used for crowd behavior analysis. In the literature, there are two types of approaches for behavior understanding problem: analyzing behaviors of individuals in a crowd (object based) and using this knowledge to make deductions regarding the crowd behavior and analyzing the crowd as a whole (holistic based). In this work, a holistic approach is used to develop a real-time abnormality detection in crowds using scale invariant feature transform (SIFT) based features and unsupervised machine learning techniques.

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KHAN, SULTAN DAUD. "Automatic Detection and Computer Vision Analysis of Flow Dynamics and Social Groups in Pedestrian Crowds." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/102644.

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Computer vision played a vital role in the field of video surveillance. However, recent developed computer vision algorithms rarely solve the problems related to real time crowd management. The phenomena of crowd like sports, festivals, concerts, political gatherings etc, are mostly observed in urban areas, which attracts hundreds of thousands people. In this thesis, we have developed algorithms that overcome some of the challenges encountered in videos of crowded environments such as sporting events, religious festivals, parades, concerts, train stations, airports, and malls. The main theme of this thesis is two fold ,i.e, understanding crowd dynamics in videos of (i), high density crowds and (ii) low density crowds. Typical examples of high density crowds include marathons, religious festivals while malls, airports, subways etc covers low dense situations. In this thesis, we adopt different approaches in order to deal with different kinds of problems coming from these two categories of crowd. In particular, first part of the thesis, we adopt holistic approach to generate a global representation of the scene that captures both dynamics of the crowd and structure of the scene. This was achieved by extracting global features, i.e optical flow from the scene. For the crowd flow segmentation problem, the optical flows vectors are clustered by using K-means clustering followed by the blob absorption approach. Using the segmentation information, we continue to estimate the number of people in each segment by carrying out the blob analysis and blob size optimization approach. This approach however, provide useful information for understanding crowd dynamics yet it lacks significant information for understanding crowd behavior. Therefore, in this thesis, the current crowd flow segmentation and counting approach is further extended in order to coup the challenges of crowd behavior understanding. The extension adopts optical flow for the identification of pedestrian movements, and it considers the analyzed video as a set of sequences. The latter are analyzed separately, producing tracklets that are then clustered to produce global trajectories, defining both sources and sinks, but also characterizing the movement of pedestrians in the scene. In the second part of the thesis, We propose a novel approach for automatic detection of social groups of pedestrians in crowds by considering only start (source) and stop (sink) locations of pedestrian trajectories. We build an Association Matrix that captures the joint probability distribution of starts and stops locations of all pedestrian trajectories to all other pedestrian trajectories in the scene. Pedestrians exhibiting similar distribution are combining in a group, where as similarity among the distributions is measuread by KL Divergence We adopt bottom-up hierarchical clustering approach, which is three step processes. In first step, we treat all the individuals as independent clusters, In the second step, couples are detected and after pruning of bad couples, Adjacency matrix is generated. Later on, in step three, using the Adjacency Matrix, groups of couples, those have strong intergroup closeness (similarity) are merged into a larger group..

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Bisagno, Niccol&#242. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.

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Crowds of people are gathering at multiple venues, such as concerts, political rallies, as well as in commercial malls, or just simply walking on the streets. More and more people are flocking to live in urban areas, thus generating a lot of scenarios of crowds. As a consequence, there is an increasing demand for automatic tools that can analyze and predict the behavior of crowds to ensure safety. Crowd motion analysis is a key feature in surveillance and monitoring applications, providing useful hints about potential threats to safety and security in urban and public spaces. It is well known that people gatherings are generally difficult to model, due to the diversity of the agents composing the crowd. Each individual is unique, being driven not only by the destination but also by personality traits and attitude. The domain of crowd analysis has been widely investigated in the literature. However, crowd gatherings have sometimes resulted in dangerous scenarios in recent years, such as stampedes or during dangerous situations. To take a step toward ensuring the safety of crowds, in this work we investigate two main research problems: we try to predict each person future position and we try to understand which are the key factors for simulating crowds. Predicting in advance how a mass of people will fare in a given space would help in ensuring the safety of public gatherings.

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McAllister, Kevin Michael. "Analysis of sport crowd behavior adapting Smelser's theory of collective behavior." Thesis, Boston University, 2002. https://hdl.handle.net/2144/32796.

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Thesis (Ed.D.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. The purpose of this study was to validate a new protocol for examining spectator behavior at high school sporting events. The methodology was based on the construct of Smelser's (1962) six determinants of collective behavior - conduciveness, strain, growth of beliefs, precipitating factors, mobilization , and social controls - and operationalised incorporating both qualitative (interviews and observations) and quantitative methods that included a behavioral assessment, an identification scale, and pre- and post-game emotional scales. Fourteen games (3 hockey, 6 soccer, 5 football) were observed over three stages of methodological development. Data were collected by teams of researchers at the games, and then were organized by themes relating to the six determinants. The themes were then examined against social and psychological theories attributed to spectator research, and examined for new construct relationships of the determinants. The research yielded a valid methodology for further spectator research, and suggestions for understanding spectator behavior are offered. 2031-01-01

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Solmaz, Berkan. "Holistic Representations for Activities and Crowd Behaviors." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5870.

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In this dissertation, we address the problem of analyzing the activities of people in a variety of scenarios, this is commonly encountered in vision applications. The overarching goal is to devise new representations for the activities, in settings where individuals or a number of people may take a part in specific activities. Different types of activities can be performed by either an individual at the fine level or by several people constituting a crowd at the coarse level. We take into account the domain specific information for modeling these activities. The summary of the proposed solutions is presented in the following. The holistic description of videos is appealing for visual detection and classification tasks for several reasons including capturing the spatial relations between the scene components, simplicity, and performance [1, 2, 3]. First, we present a holistic (global) frequency spectrum based descriptor for representing the atomic actions performed by individuals such as: bench pressing, diving, hand waving, boxing, playing guitar, mixing, jumping, horse riding, hula hooping etc. We model and learn these individual actions for classifying complex user uploaded videos. Our method bypasses the detection of interest points, the extraction of local video descriptors and the quantization of local descriptors into a code book; it represents each video sequence as a single feature vector. This holistic feature vector is computed by applying a bank of 3-D spatio-temporal filters on the frequency spectrum of a video sequence; hence it integrates the information about the motion and scene structure. We tested our approach on two of the most challenging datasets, UCF50 [4] and HMDB51 [5], and obtained promising results which demonstrates the robustness and the discriminative power of our holistic video descriptor for classifying videos of various realistic actions. In the above approach, a holistic feature vector of a video clip is acquired by dividing the video into spatio-temporal blocks then concatenating the features of the individual blocks together. However, such a holistic representation blindly incorporates all the video regions regardless of their contribution in classification. Next, we present an approach which improves the performance of the holistic descriptors for activity recognition. In our novel method, we improve the holistic descriptors by discovering the discriminative video blocks. We measure the discriminativity of a block by examining its response to a pre-learned support vector machine model. In particular, a block is considered discriminative if it responds positively for positive training samples, and negatively for negative training samples. We pose the problem of finding the optimal blocks as a problem of selecting a sparse set of blocks, which maximizes the total classifier discriminativity. Through a detailed set of experiments on benchmark datasets [6, 7, 8, 9, 5, 10], we show that our method discovers the useful regions in the videos and eliminates the ones which are confusing for classification, which results in significant performance improvement over the state-of-the-art. In contrast to the scenes where an individual performs a primitive action, there may be scenes with several people, where crowd behaviors may take place. For these types of scenes the traditional approaches for recognition will not work due to severe occlusion and computational requirements. The number of videos is limited and the scenes are complicated, hence learning these behaviors is not feasible. For this problem, we present a novel approach, based on the optical flow in a video sequence, for identifying five specific and common crowd behaviors in visual scenes. In the algorithm, the scene is overlaid by a grid of particles, initializing a dynamical system which is derived from the optical flow. Numerical integration of the optical flow provides particle trajectories that represent the motion in the scene. Linearization of the dynamical system allows a simple and practical analysis and classification of the behavior through the Jacobian matrix. Essentially, the eigenvalues of this matrix are used to determine the dynamic stability of points in the flow and each type of stability corresponds to one of the five crowd behaviors. The identified crowd behaviors are (1) bottlenecks: where many pedestrians/vehicles from various points in the scene are entering through one narrow passage, (2) fountainheads: where many pedestrians/vehicles are emerging from a narrow passage only to separate in many directions, (3) lanes: where many pedestrians/vehicles are moving at the same speeds in the same direction, (4) arches or rings: where the collective motion is curved or circular, and (5) blocking: where there is a opposing motion and desired movement of groups of pedestrians is somehow prohibited. The implementation requires identifying a region of interest in the scene, and checking the eigenvalues of the Jacobian matrix in that region to determine the type of flow, that corresponds to various well-defined crowd behaviors. The eigenvalues are only considered in these regions of interest, consistent with the linear approximation and the implied behaviors. Since changes in eigenvalues can mean changes in stability, corresponding to changes in behavior, we can repeat the algorithm over clips of long video sequences to locate changes in behavior. This method was tested on over real videos representing crowd and traffic scenes. Ph.D. Doctorate Electrical Engineering and Computer Science Engineering and Computer Science Electrical Engineering

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Jones, Kyle Thomas. "Innovation Management and Crowdsourcing| A Quantitative Analysis of Sponsor and Crowd Assessments." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10686345.

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Crowdsourcing is an increasingly common method used for new product development in large engineering-focused companies. While effective at generating a large number of ideas, previous research has noted that there is not an efficient mechanism to sort ideas based on the sponsor's desired outcomes. Without such a mechanism, the sponsor is left to evaluate ideas individually in a labor-intensive effort. This paper evaluates the extent to which information revealed by the crowd during the course of a crowdsourcing event can be used to accurately predict sponsor selection of submitted ideas. The praxis reviews current literature relevant to new product development, innovation management, and crowdsourcing as well as methods for efficient sorting. Using a quantitatively-based methodology, the author develops and evaluates several predictive models using various attributes of the crowd reaction to crowdsourced ideas. Ultimately, the praxis proposes a model that can significantly reduce the burden of sorting through submissions and determining the submissions which merit further review.

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Andrews, S., T. Day, K. Domdouzis, L. Hirsch, Raluca Lefticaru, and C. Orphanides. "Analyzing Crowd-Sourced Information and Social Media for Crisis Management." Springer International Publishing, 2016. http://hdl.handle.net/10454/17662.

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Yes The analysis of potentially large volumes of crowd-sourced and social media data is central to meeting the requirements of the ATHENA project. Here, we discuss the various stages of the pipeline process we have developed, including acquisition of the data, analysis, aggregation, filtering, and structuring. We highlight the challenges involved when working with unstructured, noisy data from sources such as Twitter, and describe the crisis taxonomies that have been developed to support the tasks and enable concept extraction. State-of-the-art techniques such as formal concept analysis and machine learning are used to create a range of capabilities including concept drill down, sentiment analysis, credibility assessment, and assignment of priority. We ground many of these techniques using results obtained from a set of tweets which emerged from the Colorado wildfires of 2012 in order to demonstrate the applicability of our work to real crisis scenarios.

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Bailo, Francesco. "The citizen-user and the crowd-mediated politics of the Five Star Movement." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17068.

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This thesis described the trajectory of the Italy’s Five Star Movement (M5S, 2005- 2014) from the perspective of the citizens who, as Internet users, participated in in the political enterprise. Citizen-users, enabled and empowered by Internet and mobile technologies, shaped and sustained the identity and evolution of the movement that became the M5S. The case study selected for this research, the M5S, is exceptional due to the magnitude of its success; but its features (Internet-centered and fluid ideology) are becoming more common among political organisations in Western democracies. The goal of the thesis is to assess the impact of the Internet on the political process, through its connecting, mobilising, organising, and to characterise the shape of political talk among citizens. This is achieved by applying quantitative methods, including network analysis and natural language processing, on 10 years of user-generated data collected mainly from four sources: the blog of the Movement’s founder, the M5S official forum, Facebook and Meetup.com. The thesis finds that the online discussion fora fostered diversity without fragmentation, and contributed on at least one occasion to shape the policy agenda of the M5S. Furthermore, the meetups of the Movement maintained their capacity to attract and mobilise users, and their territorial distribution clearly correlate with local results of the M5S in two elections, suggesting a positive impact of Internet-enabled mobilisation. Finally, given the votes received in the 2013 general election, the political communication generated over the Internet offset the low attention dedicated by TV news broadcast to the Movement during the electoral campaign. As Internet and mobile technologies are routinised, it is easy to see how their importance in political organisation and deliberation will grow. By studying the application of ICTs in the case of the M5S, this thesis offers insights into their use in practice, as well as pointing to possible democratic risks if online deliberation is non controlled to guarantee its fairness and openness but instead steered by the leadership, turning a deliberating community of citizen-users into a noisy crowd.

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Flagg, Matthew. "Capture, analysis and synthesis of photorealistic crowds." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37310.

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This thesis explores techniques for synthesizing crowds from imagery. Synthetic photorealistic crowds are desirable for cinematic gaming, special effects and architectural visualization. While motion captured-based techniques for the animation and control of crowds have been well-studied in computer graphics, the resulting control rig sequences require a laborious model-based graphics pipeline to render photorealistic videos of crowds. Over the past ten years, data-driven techniques for rendering imagery of complex phenomena have become a popular alternative to model-based graphics. This popularity is due in large part to difficulties in constructing the sufficiently-detailed models that are required to achieve photorealism. A dynamic crowd of humans is an extremely challenging example of such phenomena. Example-based synthesis methods such as video textures are an appealing alternative, but current techniques are unable to handle new challenges posed by crowds. This thesis describes how to synthesize video-based crowds by explicitly segmenting pedestrians from input videos of natural crowds and optimally placing them into an output video while satisfying environmental constraints imposed by the scene. There are three key challenges. First, the crowd layout of segmented videos must satisfy constraints imposed by environmental and crowd obstacles. This thesis addresses four types of environmental constraints: (a) ground planes in the scene which are valid for crowd traversal, such as sidewalks, (b) spatial regions of these planes where crowds may enter and exit the scene, (c) static obstacles, such as mailboxes and walls of a building, and (d) dynamic obstacles such as individuals and groups of individuals. Second, pedestrians and groups of pedestrians should be segmented from the input video with no artifacts and minimal interaction time. This is challenging in real world scenes due to significant appearance changes while traveling through the scene. Third, segmented pedestrian videos may not have enough frames or the right shape to compose a path from an artist-defined entrance to exit. Plausible temporal transitions between segmented pedestrians are therefore needed but they are difficult to identify and synthesize due to complex self occlusions. We present a novel algorithm for composing video billboards, represented by crowd tubes, to form a crowd while avoiding collisions between static and dynamic obstacles. Crowd tubes are represented in the scene using a temporal sequence of circles planted in the calibrated ground plane. The approach consists of representing crowd tube samples and constraint violations with a conflict graph. The maximal independent set yields a dense crowd composition. We present a prototype system for the capture, analysis, synthesis and control of video-based crowds. Several results demonstrate the system's ability to generate videos of crowds which exhibit a variety of natural behaviors.

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Jaiswal, Sumeet Kumar. "Busway platform bus capacity analysis." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/43698/1/Sumeet_Jaiswal_Thesis.pdf.

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Bus Rapid Transit (BRT), because of its operational flexibility and simplicity, is rapidly gaining popularity with urban designers and transit planners. Earlier BRTs were bus shared lane or bus only lane, which share the roadway with general and other forms of traffic. In recent time, more sophisticated designs of BRT have emerged, such as busway, which has separate carriageway for buses and provides very high physical separation of buses from general traffic. Line capacities of a busway are predominately dependent on bus capacity of its stations. Despite new developments in BRT designs, the methodology of capacity analysis is still based on traditional principles of kerbside bus stop on bus only lane operations. Consequently, the tradition methodology lacks accounting for various dimensions of busway station operation, such as passenger crowd, passenger walking and bus lost time along the long busway station platform. This research has developed a purpose made bus capacity analysis methodology for busway station analysis. Extensive observations of kerbside bus stops and busway stations in Brisbane, Australia were made and differences in their operation were studied. A large scale data collection was conducted using the video recording technique at the Mater Hill Busway Station on the South East Busway in Brisbane. This research identified new parameters concerning busway station operation, and through intricate analysis identified the elements and processes which influence the bus dwell time at a busway station platform. A new variable, Bus lost time, was defined and its quantitative descriptions were established. Based on these finding and analysis, a busway station platform bus capacity methodology was developed, comprising of new models for busway station lost time, busway station dwell time, busway station loading area bus capacity, and busway station platform bus capacity. The new methodology not only accounts for passenger boarding and alighting, but also covers platform crowd and bus lost time in station platform bus capacity estimation. The applicability of this methodology was shown through demonstrative examples. Additionally, these examples illustrated the significance of the bus lost time variable in determining station capacities.

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Pietschmann, Jan-Frederik. "On some partial differential equation models in socio-economic contexts : analysis and numerical simulations." Thesis, University of Cambridge, 2012. https://www.repository.cam.ac.uk/handle/1810/241495.

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This thesis deals with the analysis and numerical simulation of different partial differential equation models arising in socioeconomic sciences. It is divided into two parts: The first part deals with a mean-field price formation model introduced by Lasry andLions in 2007. This model describes the dynamic behaviour of the price of a good being traded between a group of buyers and a group of vendors. Existence (locally in time) of smooth solutions is established, and obstructions to proving a global existence result are examined. Also, properties of a regularised version of the model are explored and numerical examples are shown. Furthermore, the possibility of reconstructing the initial datum given a number of observations, regarding the price and the transaction rate, is considered. Using a variational approach, the problem can be expressed as a non-linear constrained minimization problem. We show that the initial datum is uniquely determined by the price (identifiability). Furthermore, a numerical scheme is implemented and a variety of examples are presented. The second part of this thesis treats two different models describing the motion of (large) human crowds. For the first model, introduced by R.L. Hughes in 2002, several regularised versions are considered. Existence and uniqueness of entropy solutions are proven using the technique of vanishing viscosity. In one space dimension, the dynamic behaviour of solutions of the original model is explored for some special cases. These results are compared to numerical simulations. Moreover, we consider a discrete cellular automaton model introduced by A. Kirchner and A. Schadschneider in 2002.By (formally) passing to the continuum limit, we obtain a system of partial differential equations. Some analytical properties, such as linear stability of stationary states, areexamined and extensive numerical simulations show capabilities and limitations of the model in both the discrete and continuous setting.

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Zhang, Qingpeng. "Analyzing Cyber-Enabled Social Movement Organizations: A Case Study with Crowd-Powered Search." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/265358.

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The advances in social media and social computing technologies have dramatically changed the way through which people interact, organize, and collaborate. The use of social media also makes the large-scale data revealing human behavior accessible to researchers and practitioners. The analysis and modeling of social networks formed from relatively stable online communities have been extensively studied. The research on the structural and dynamical patterns of large-scale crowds motivated by accomplishing common goals, named the cyber movement organizations (CMO) or cyber-enabled social movement organizations (CeSMO), however, is still limited to anecdotal case studies. This research is one of the first steps towards the understanding of the CMO/CeSMO based on real data collected from online social media.The focus of my research is on the study of an important type of CMO/CeSMO, the crowd-powered search behavior (also known as human flesh search, HFS), in which a large number of Web users voluntarily gathered together to find out the truth of an event or the information of a person that could not be identified by one single person or simple online searches. In this research, I have collected a comprehensive data-set of HFS. I first introduce the phenomenon of HFS and reviewed the study of online social groups/communities. Then, I present the empirical studies of both individual HFS episodes and aggregated HFS communities, and unveiled their unique topological properties. Based on the empirical findings, I propose two models to simulate evolution and topology of individual HFS networks. I conclude the dissertation with discussions of future research of CMO/CeSMO.

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Richardson, Omar. "Large-scale multiscale particle models in inhomogeneous domains." Thesis, University of Technology Eindhoven, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-45862.

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In this thesis, we develop multiscale models for particle simulations in population dynamics. These models are characterised by prescribing particle motion on two spatial scales: microscopic and macroscopic.At the microscopic level, each particle has its own mass, position and velocity, while at the macroscopic level the particles are interpolated to a continuum quantity whose evolution is governed by a system of transport equations.This way, one can prescribe various types of interactions on a global scale, whilst still maintaining high simulation speed for a large number of particles. In addition, the interplay between particle motion and interaction is well tuned in both regions of low and high densities. We analyse links between models on these two scales and prove that under certain conditions, a system of interacting particles converges to a nonlinear coupled system of transport equations.We use this as a motivation to derive a model defined on both modelling scales and prescribe the intercommunication between them. Simulation takes place in inhomogeneous domains with arbitrary conditions at inflow and outflow boundaries. We realise this by modelling obstacles, sources and sinks.Integrating these aspects into the simulation requires a route planning algorithm for the particles. Several algorithms are considered and evaluated on accuracy, robustness and efficiency. All aspects mentioned above are combined in a novel open source prototyping simulation framework called Mercurial. This computational framework allows the design of geometries and is built for high performance when large numbers of particles are involved. Mercurial supports various types of inhomogeneities and global systems of equations. We apply our framework to simulate scenarios in crowd dynamics.We compare our results with test cases from literature to assess the quality of the simulations. Master Thesis in Industrial and Applied Mathematics

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Fagette, Antoine. "Détection de foule et analyse de comportement par analyse vidéo." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066709.

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Cette thèse porte sur la similitude entre un fluide et une foule et sur l'adaptation de l’algorithme de Particle Video pour le suivi et l'analyse de foule, ce qui aboutit à la conception d'un système complet pour l'analyse de la foule. Cette thèse en étudie trois aspects : la détection de la foule, l'estimation de sa densité et le tracking des flux afin d'obtenir des caractéristiques de comportement.L’algorithme de détection de la foule est une méthode totalement non supervisée pour la détection et la localisation des foules denses dans des images non-contextualisées. Après avoir calculé des vecteurs de features multi-échelles, une classification binaire est effectuée afin d'identifier la foule et l'arrière-plan.L'algorithme d'estimation de densité s'attaque au problème de l'apprentissage de modèles de régression dans le cas de larges foules denses. L'apprentissage est alors impossible sur données réelles car la vérité terrain est indisponible. Notre méthode repose donc sur l'utilisation de données synthétiques pour la phase d'apprentissage et prouve que le modèle de régression obtenu est valable sur données réelles.Pour notre adaptation de l’algorithme de Particle Video nous considérons le nuage de particules comme statistiquement représentatif de la foule. De ce fait, chaque particule possède des propriétés physiques qui nous permettent d'évaluer la validité de son comportement en fonction de celui attendu d'un piéton et d’optimiser son mouvement guidé par le flot optique. Trois applications en découlent : détection des zones d’entrée-sortie de la foule, détection des occlusions dynamiques et mise en relation des zones d'entrée et de sortie selon les flux de piétons This thesis focuses on the similarity between a fluid and a crowd and on the adaptation of the particle video algorithm for crowd tracking and analysis. This interrogation ended up with the design of a complete system for crowd analysis out of which, this thesis has addressed three main problems: the detection of the crowd, the estimation of its density and the tracking of the flow in order to derive some behavior features.The contribution to crowd detection introduces a totally unsupervised method for the detection and location of dense crowds in images without context-awareness. After retrieving multi-scale texture-related feature vectors from the image, a binary classification is conducted to identify the crowd and the background.The density estimation algorithm is tackling the problem of learning regression models when it comes to large dense crowds. In such cases, the learning is impossible on real data as the ground truth is not available. Our method relies on the use of synthetic data for the learning phase and proves that the regression model obtained is valid for a use on real data.Our adaptation of the particle video algorithm leads us to consider the cloud of particles as statistically representative of the crowd. Therefore, each particle has physical properties that enable us to assess the validity of its behavior according to the one expected from a pedestrian, and to optimize its motion guided by the optical flow. This leads us to three applications: the detection of the entry and exit areas of the crowd in the image, the detection of dynamic occlusions and the possibility to link entry areas with exit ones, according to the flow of the pedestrians

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Pucher, Isabelle, and Kim Dahlbeck. "Three is a Crowd : A Critical Analysis of Third Party Actor Influence Regarding the Nuclear Negotiations Between P5+1 and Iran." Thesis, Högskolan i Halmstad, Akademin för lärande, humaniora och samhälle, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-29685.

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This thesis examines third-party actor influence on the domestic level in the ongoing diplomatic negotiations between P5+1 and Iran, with the research question being; What demands, arguments and strategies does the Congress and AIPAC use to influence the negotiation process between the U.S. and Iran? Secondly, what are their goals for doing so? Furthermore, the combined theoretical framework has been applied onto the material using a critical method in order to answer the questions. Legislative bills from the Congress, regarding congressional insight to the agreement, have been approved. In this pressured negotiation process with high stakes it is astounding that these actions are allowed. Due to this behavior from Congress, amongst others, it becomes interesting to study the negotiation process and its salient third-party actor influence. The results suggests that legislative actions combined with various demands and arguments, focused on mistrust of Iran, history and the security of Israel, are their main strategies to gain influence. An additional new, third, level has also been discovered by the authors of this thesis in regards to these complicated negotiations.

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Laughridge, James Lee. "An analysis of mechanisms designed to reduce crowd-out among state children's health insurance programs and their implications for public service." Birmingham, Ala. : University of Alabama at Birmingham, 2009. https://www.mhsl.uab.edu/dt/2009m/laughridge.pdf.

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THOVUTTIKUL, SUTASINEE. "Contrastive Analysis of Point of View Effects in Culture-Dependent Social Cognition." Kyoto University, 2019. http://hdl.handle.net/2433/244576.

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Slabbert, Meggan. "Three's a crowd: the process of triadic translation in a South African psychiatric institution." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1002565.

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Mental health care in South Africa has long been governed by inequalities (Foster & Swartz, 1997). During apartheid, those who did not speak English and Afrikaans could not access mental health services in the same way as those who did (Foster & Swartz, 1997). One main reason for this is the majority of mental health practitioners could not, and were not required to speak languages other than English and Afrikaans (Swartz, 1991). The South African mental health literature suggests that language and communication must be prioritised if there is to be an improvement in mental health care services for those individuals who do not speak English and Afrikaans (Bantjes, 1999; Drennan & Swartz, 1999; Swartz & Drennan, 2000; Swartz & MacGregor, 2002). Drawing on Prasad's (2002) interpretation of Gadamer's critical hermeneutic theory and utilising thematic networks analysis (Attride-Stirling, 2001), this study investigated the process of translated clinical assessment interviews within a psychiatric hospital in the Eastern Cape Province within South Africa. Results of the study revealed that contextual factors, issues concerning linguistic and cultural heritage, clinicians' role expectations regarding translators' role performance, as well as relational dynamics regarding individual levels of control and influence within the translation triad, all impacted on the effectiveness of communication, translation and service provision. These fmdings are supported by literature on the theory and practice of translation that identifies these issues as prominent (Robinson, 2003). Specific recommendations regarding the formalisation of translation practices within the hospital setting, as well as the familiari~ation of clinical practitioners and psychiatric nurses with the intricacies of translation processes are offered.

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López, Baeza Jesús. "Unveiling urban dynamics: An exploration of tools and methods using crowd-sourced data for the study of urban space." Doctoral thesis, Universidad de Alicante, 2020. http://hdl.handle.net/10045/108227.

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The following work presents several trans-disciplinary resources for understanding cities beyond just their physical form and spatial processes. The conceptualization of cities from a top-down, modern and post- modern approach to the form-function duality lacks multiple dimensions, which need to be studied in order to gain a proper understanding of how contemporary urban societies perform nowadays. Instead, this work considers settlements as a set of an infinite number of individual perceptions and experiences, which construct overlapping layers of hidden and intangible information that shape cities as complex systems. Social relations that are moving progressively to the virtual realm are becoming major factors in decision-making and location choices by citizens. This definition of a city’s hidden image is developed through the study of data retrieved from online servers. To do so, this work focuses on spatial and temporal activity patterns, values of certain places and their quantitative weight within the urban fabric, the distribution and nature of places, the observation of people’s perception of certain places through the representation of activities captured by pictures posted online, or several other theoretical and methodological approaches under the umbrella of crowd-sourced data in the city.

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Blesik, Till [Verfasser]. "Crowd Knowledge and Blockchain : A conceptualisation of digitised artefacts: An analysis of platform adoption in e-health: Comprehensive application areas in supply chain / Till Blesik." Berlin : ESCP Europe Wirtschaftshochschule Berlin, 2020. http://d-nb.info/1206553936/34.

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Vandoni, Jennifer. "Ensemble Methods for Pedestrian Detection in Dense Crowds." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS116/document.

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Cette thèse s’intéresse à la détection des piétons dans des foules très denses depuis un système mono-camera, avec comme but d’obtenir des détections localisées de toutes les personnes. Ces détections peuvent être utilisées soit pour obtenir une estimation robuste de la densité, soit pour initialiser un algorithme de suivi. Les méthodologies classiques utilisées pour la détection de piétons s’adaptent mal au cas où seulement les têtes sont visibles, de part l’absence d’arrière-plan, l’homogénéité visuelle de la foule, la petite taille des objets et la présence d’occultations très fortes. En présence de problèmes difficiles tels que notre application, les approches à base d’apprentissage supervisé sont bien adaptées. Nous considérons un système à plusieurs classifieurs (Multiple Classifier System, MCS), composé de deux ensembles différents, le premier basé sur les classifieurs SVM (SVM- ensemble) et le deuxième basé sur les CNN (CNN-ensemble), combinés dans le cadre de la Théorie des Fonctions de Croyance (TFC). L’ensemble SVM est composé de plusieurs SVM exploitant les données issues d’un descripteur différent. La TFC nous permet de prendre en compte une valeur d’imprécision supposée correspondre soit à une imprécision dans la procédure de calibration, soit à une imprécision spatiale. Cependant, le manque de données labellisées pour le cas des foules très denses nuit à la génération d’ensembles de données d’entrainement et de validation robustes. Nous avons proposé un algorithme d’apprentissage actif de type Query-by- Committee (QBC) qui permet de sélectionner automatiquement de nouveaux échantillons d’apprentissage. Cet algorithme s’appuie sur des mesures évidentielles déduites des fonctions de croyance. Pour le second ensemble, pour exploiter les avancées de l’apprentissage profond, nous avons reformulé notre problème comme une tâche de segmentation en soft labels. Une architecture entièrement convolutionelle a été conçue pour détecter les petits objets grâce à des convolutions dilatées. Nous nous sommes appuyés sur la technique du dropout pour obtenir un ensemble CNN capable d’évaluer la fiabilité sur les prédictions du réseau lors de l’inférence. Les réalisations de cet ensemble sont ensuite combinées dans le cadre de la TFC. Pour conclure, nous montrons que la sortie du MCS peut être utile aussi pour le comptage de personnes. Nous avons proposé une méthodologie d’évaluation multi-échelle, très utile pour la communauté de modélisation car elle lie incertitude (probabilité d’erreur) et imprécision sur les valeurs de densité estimées This study deals with pedestrian detection in high- density crowds from a mono-camera system. The detections can be then used both to obtain robust density estimation, and to initialize a tracking algorithm. One of the most difficult challenges is that usual pedestrian detection methodologies do not scale well to high-density crowds, for reasons such as absence of background, high visual homogeneity, small size of the objects, and heavy occlusions. We cast the detection problem as a Multiple Classifier System (MCS), composed by two different ensembles of classifiers, the first one based on SVM (SVM-ensemble) and the second one based on CNN (CNN-ensemble), combined relying on the Belief Function Theory (BFT) to exploit their strengths for pixel-wise classification. SVM-ensemble is composed by several SVM detectors based on different gradient, texture and orientation descriptors, able to tackle the problem from different perspectives. BFT allows us to take into account the imprecision in addition to the uncertainty value provided by each classifier, which we consider coming from possible errors in the calibration procedure and from pixel neighbor's heterogeneity in the image space. However, scarcity of labeled data for specific dense crowd contexts reflects in the impossibility to obtain robust training and validation sets. By exploiting belief functions directly derived from the classifiers' combination, we propose an evidential Query-by-Committee (QBC) active learning algorithm to automatically select the most informative training samples. On the other side, we explore deep learning techniques by casting the problem as a segmentation task with soft labels, with a fully convolutional network designed to recover small objects thanks to a tailored use of dilated convolutions. In order to obtain a pixel-wise measure of reliability about the network's predictions, we create a CNN- ensemble by means of dropout at inference time, and we combine the different obtained realizations in the context of BFT. Finally, we show that the output map given by the MCS can be employed to perform people counting. We propose an evaluation method that can be applied at every scale, providing also uncertainty bounds on the estimated density

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Katevas, Kleomenis. "Analysing crowd behaviours using mobile sensing." Thesis, Queen Mary, University of London, 2018. http://qmro.qmul.ac.uk/xmlui/handle/123456789/54059.

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Researchers have examined crowd behaviour in the past by employing a variety of methods including ethnographic studies, computer vision techniques and manual annotation-based data analysis. However, because of the resources to collect, process and analyse data, it remains difficult to obtain large data sets for study. Mobile phones offer easier means for data collection that is easy to analyse and can preserve the user's privacy. The aim of this thesis is to identify and model different qualities of social interactions inside crowds using mobile sensing technology. This Ph.D. research makes three main contributions centred around the mobile sensing and crowd sensing area. Firstly, an open-source licensed mobile sensing framework is developed, named SensingKit, that is capable of collecting mobile sensor data from iOS and Android devices, supporting most sensors available in modern smartphones. The framework has been evaluated in a case study that investigates the pedestrian gait synchronisation phenomenon. Secondly, a novel algorithm based on graph theory is proposed capable of detecting stationary social interactions within crowds. It uses sensor data available in a modern smartphone device, such as the Bluetooth Smart (BLE) sensor, as an indication of user proximity, and accelerometer sensor, as an indication of each user's motion state. Finally, a machine learning model is introduced that uses multi-modal mobile sensor data extracted from Bluetooth Smart, accelerometer and gyroscope sensors. The validation was performed using a relatively large dataset with 24 participants, where they were asked to socialise with each other for 45 minutes. By using supervised machine learning based on gradient-boosted trees, a performance increase of 26.7% was achieved over a proximity-based approach. Such model can be beneficial to the design and implementation of in-the-wild crowd behavioural analysis, design of influence strategies, and algorithms for crowd reconfiguration.

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Dehqan, Agri. ""Writing For the enemy" : Kurdish Language standardization online." Thesis, Blekinge Tekniska Högskola, Institutionen för teknik och estetik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5729.

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The aim of this thesis is to study some of the challenges that the Kurdish language and its standardization face, and offer a bottom-up solution through the “collective intelligence” and “good faith collaboration” of Wikipedia. Therefore, the fragmentation in the Kurdish language—caused by both external factors and those that are inherent to the language itself— is discussed and analyzed. Furthermore, this thesis describes some of the efforts that have been made to unify the Kurdish language, its dialects and its different writing systems. Even though these issues exist both in the physical world as well as online, they are rendered more conspicuous on the Internet. As a result, the problems in Kurdish cross-dialect communication are more pronounced. In spite of that, web 2.0 and its favored platforms for online collaboration provide ample opportunity for the general user of the language to participate in solving such linguistic problems. An overview of Wikipedia, as the world’s most successful platform for online collaboration, is presented along with some of its rules and policies. Additionally, an account of the current Kurdish Wikipedia in three dialects of Kurdish: Kurmanji, Sorani and Zazaki is provided. The situation and shortcomings of Kurdish versions of Wikipedia are examined through two case studies based on two Wikipedia articles in Kurdish and their English and Persian counterparts. Moreover, I argue that a robust Kurdish Wikipedia can be a viable solution for standardizing the language, encouraging orthographic consistency, and unifying Kurdish writing systems and knowledge/information dissemination in Kurdish. +46762801113

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Pellicanò, Nicola. "Tackling pedestrian detection in large scenes with multiple views and representations." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS608/document.

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La détection et le suivi de piétons sont devenus des thèmes phares en recherche en Vision Artificielle, car ils sont impliqués dans de nombreuses applications. La détection de piétons dans des foules très denses est une extension naturelle de ce domaine de recherche, et l’intérêt croissant pour ce problème est lié aux évènements de grande envergure qui sont, de nos jours, des scenarios à risque d’un point de vue de la sûreté publique. Par ailleurs, les foules très denses soulèvent des problèmes inédits pour la tâche de détection. De par le fait que les caméras ont le champ de vision le plus grand possible pour couvrir au mieux la foule les têtes sont généralement très petites et non texturées. Dans ce manuscrit nous présentons un système complet pour traiter les problèmes de détection et de suivi en présence des difficultés spécifiques à ce contexte. Ce système utilise plusieurs caméras, pour gérer les problèmes de forte occultation. Nous proposons une méthode robuste pour l’estimation de la position relative entre plusieurs caméras dans le cas des environnements requérant une surveillance. Ces environnements soulèvent des problèmes comme la grande distance entre les caméras, le fort changement de perspective, et la pénurie d’information en commun. Nous avons alors proposé d’exploiter le flot vidéo pour effectuer la calibration, avec l’objectif d’obtenir une solution globale de bonne qualité. Nous proposons aussi une méthode non supervisée pour la détection des piétons avec plusieurs caméras, qui exploite la consistance visuelle des pixels à partir des différents points de vue, ce qui nous permet d’effectuer la projection de l’ensemble des détections sur le plan du sol, et donc de passer à un suivi 3D. Dans une troisième partie, nous revenons sur la détection supervisée des piétons dans chaque caméra indépendamment en vue de l’améliorer. L’objectif est alors d’effectuer la segmentation des piétons dans la scène en partant d’une labélisation imprécise des données d’apprentissage, avec des architectures de réseaux profonds. Comme dernière contribution, nous proposons un cadre formel original pour une fusion de données efficace dans des espaces 2D. L’objectif est d’effectuer la fusion entre différents capteurs (détecteurs supervisés en chaque caméra et détecteur non supervisé en multi-vues) sur le plan du sol, qui représente notre cadre de discernement. nous avons proposé une représentation efficace des hypothèses composées qui est invariante au changement de résolution de l’espace de recherche. Avec cette représentation, nous sommes capables de définir des opérateurs de base et des règles de combinaison efficaces pour combiner les fonctions de croyance. Enfin, notre approche de fusion de données a été évaluée à la fois au niveau spatial, c’est à dire en combinant des détecteurs de nature différente, et au niveau temporel, en faisant du suivi évidentiel de piétons sur de scènes à grande échelle dans des conditions de densité variable Pedestrian detection and tracking have become important fields in Computer Vision research, due to their implications for many applications, e.g. surveillance, autonomous cars, robotics. Pedestrian detection in high density crowds is a natural extension of such research body. The ability to track each pedestrian independently in a dense crowd has multiple applications: study of human social behavior under high densities; detection of anomalies; large event infrastructure planning. On the other hand, high density crowds introduce novel problems to the detection task. First, clutter and occlusion problems are taken to the extreme, so that only heads are visible, and they are not easily separable from the moving background. Second, heads are usually small (they have a diameter of typically less than ten pixels) and with little or no textures. This comes out from two independent constraints, the need of one camera to have a field of view as high as possible, and the need of anonymization, i.e. the pedestrians must be not identifiable because of privacy concerns.In this work we develop a complete framework in order to handle the pedestrian detection and tracking problems under the presence of the novel difficulties that they introduce, by using multiple cameras, in order to implicitly handle the high occlusion issues.As a first contribution, we propose a robust method for camera pose estimation in surveillance environments. We handle problems as high distances between cameras, large perspective variations, and scarcity of matching information, by exploiting an entire video stream to perform the calibration, in such a way that it exhibits fast convergence to a good solution. Moreover, we are concerned not only with a global fitness of the solution, but also with reaching low local errors.As a second contribution, we propose an unsupervised multiple camera detection method which exploits the visual consistency of pixels between multiple views in order to estimate the presence of a pedestrian. After a fully automatic metric registration of the scene, one is capable of jointly estimating the presence of a pedestrian and its height, allowing for the projection of detections on a common ground plane, and thus allowing for 3D tracking, which can be much more robust with respect to image space based tracking.In the third part, we study different methods in order to perform supervised pedestrian detection on single views. Specifically, we aim to build a dense pedestrian segmentation of the scene starting from spatially imprecise labeling of data, i.e. heads centers instead of full head contours, since their extraction is unfeasible in a dense crowd. Most notably, deep architectures for semantic segmentation are studied and adapted to the problem of small head detection in cluttered environments.As last but not least contribution, we propose a novel framework in order to perform efficient information fusion in 2D spaces. The final aim is to perform multiple sensor fusion (supervised detectors on each view, and an unsupervised detector on multiple views) at ground plane level, that is, thus, our discernment frame. Since the space complexity of such discernment frame is very large, we propose an efficient compound hypothesis representation which has been shown to be invariant to the scale of the search space. Through such representation, we are capable of defining efficient basic operators and combination rules of Belief Function Theory. Furthermore, we propose a complementary graph based description of the relationships between compound hypotheses (i.e. intersections and inclusion), in order to perform efficient algorithms for, e.g. high level decision making.Finally, we demonstrate our information fusion approach both at a spatial level, i.e. between detectors of different natures, and at a temporal level, by performing evidential tracking of pedestrians on real large scale scenes in sparse and dense conditions

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Li, Tianyi. "Solving Mysteries with Crowds: Supporting Crowdsourced Sensemaking with a Modularized Pipeline and Context Slices." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99937.

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The increasing volume and complexity of text data are challenging the cognitive capabilities of expert analysts. Machine learning and crowdsourcing present new opportunities for large-scale sensemaking, but it remains a challenge to model the overall process so that many distributed agents can contribute to suitable components asynchronously and meaningfully. In this work, I explore how to crowdsource sensemaking for intelligence analysis. Specifically, I focus on the complex processes that include developing hypotheses and theories from a raw dataset and iteratively refining the analysis. I first developed Connect the Dots, a web application that implements the concept of "context slices" and supports novice crowds in building relationship networks for exploratory analysis. Then I developed CrowdIA, a software platform that implements the entire crowd sensemaking pipeline and the context slicing for each step, to enable unsupervised crowd sensemaking. Using the pipeline as a testbed, I probed the errors and bottlenecks in crowdsourced sensemaking,and suggested design recommendations for integrated crowdsourcing systems. Building on these insights and to support iterative crowd sensemaking, I developed the concept of "crowd auditing" in which an auditor examines a pipeline of crowd analyses and diagnoses the problems to steer future refinement. I explored the design space to support crowd auditing and developed CrowdTrace, a crowd auditing tool that enables novice auditors to effectively identify the important problems with the crowd analysis and create microtasks for crowd workers to fix the problems.The core contributions of this work include a pipeline that enables distributed crowd collaboration to holistic sensemaking processes, two novel concepts of "context slices" and "crowd auditing", web applications that support crowd sensemaking and auditing, as well as design implications for crowd sensemaking systems. The hope is that the crowd sensemaking pipeline can serve to accelerate research on sensemaking, and contribute to helping people conduct in-depth investigations of large collections of information. Doctor of Philosophy In today's world, we have access to large amounts of data that provide opportunities to solve problems at unprecedented depths and scales. While machine learning offers powerful capabilities to support data analysis, to extract meaning from raw data is cognitively demanding and requires significant person-power. Crowdsourcing aggregates human intelligence, yet it remains a challenge for many distributed agents to collaborate asynchronously and meaningfully. The contribution of this work is to explore how to use crowdsourcing to make sense of the copious and complex data. I first implemented the concept of ``context slices'', which split up complex sensemaking tasks by context, to support meaningful division of work. I developed a web application, Connect the Dots, which generates relationship networks from text documents with crowdsourcing and context slices. Then I developed a crowd sensemaking pipeline based on the expert sensemaking process. I implemented the pipeline as a web platform, CrowdIA, which guides crowds to solve mysteries without expert intervention. Using the pipeline as a testbed, I probed the errors and bottlenecks in crowd sensemaking and provided design recommendations for crowd intelligence systems. Finally, I introduced the concept of ``crowd auditing'', in which an auditor examines a pipeline of crowd analyses and diagnoses the problems to steer a top-down path of the pipeline and refine the crowd analysis. The hope is that the crowd sensemaking pipeline can serve to accelerate research on sensemaking, and contribute to helping people conduct in-depth investigations of large collections of data.

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Choudhury, Ananya. "WiSDM: a platform for crowd-sourced data acquisition, analytics, and synthetic data generation." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/72256.

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Human behavior is a key factor influencing the spread of infectious diseases. Individuals adapt their daily routine and typical behavior during the course of an epidemic -- the adaptation is based on their perception of risk of contracting the disease and its impact. As a result, it is desirable to collect behavioral data before and during a disease outbreak. Such data can help in creating better computer models that can, in turn, be used by epidemiologists and policy makers to better plan and respond to infectious disease outbreaks. However, traditional data collection methods are not well suited to support the task of acquiring human behavior related information; especially as it pertains to epidemic planning and response. Internet-based methods are an attractive complementary mechanism for collecting behavioral information. Systems such as Amazon Mechanical Turk (MTurk) and online survey tools provide simple ways to collect such information. This thesis explores new methods for information acquisition, especially behavioral information that leverage this recent technology. Here, we present the design and implementation of a crowd-sourced surveillance data acquisition system -- WiSDM. WiSDM is a web-based application and can be used by anyone with access to the Internet and a browser. Furthermore, it is designed to leverage online survey tools and MTurk; WiSDM can be embedded within MTurk in an iFrame. WiSDM has a number of novel features, including, (i) ability to support a model-based abductive reasoning loop: a flexible and adaptive information acquisition scheme driven by causal models of epidemic processes, (ii) question routing: an important feature to increase data acquisition efficacy and reduce survey fatigue and (iii) integrated surveys: interactive surveys to provide additional information on survey topic and improve user motivation. We evaluate the framework's performance using Apache JMeter and present our results. We also discuss three other extensions of WiSDM: Adapter, Synthetic Data Generator, and WiSDM Analytics. The API Adapter is an ETL extension of WiSDM which enables extracting data from disparate data sources and loading to WiSDM database. The Synthetic Data Generator allows epidemiologists to build synthetic survey data using NDSSL's Synthetic Population as agents. WiSDM Analytics empowers users to perform analysis on the data by writing simple python code using Versa APIs. We also propose a data model that is conducive to survey data analysis. Master of Science

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Landry, Denis Joseph Carleton University Dissertation Chemistry. "Approaches to the synthesis and sterochemical analysis of aza crown ethers." Ottawa, 1989.

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32

Collison, Earl. "Football crowd violence in Scotland analysed by the value-added theory of collective behaviour." Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/18793.

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Qian, Weiguang. "A preliminary investigation of solid sampling for mass spectrometric analysis of crown ethers." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/490218.

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The purpose of this study was to optimize and investigate crown ether analysis by using a mass spectrometer equipped with a direct insertion solids probe. The typical aliphatic and aromatic crowm ethers, 18-crown-6 and dibenzo-18-crown-6 were chosen for the study. The crown ether samples were prepared by miximg with the reagents (some inorganic and organic salts and glycine) or being supported on the support materials (diatomite and glass supports) in a 1:10 ratio by weight as the samples for testing. The pure crown ethers and their mixtures were tested by the programmed temperature direct insertion probe mass spectrometer. The effects of the reagents and support materials on the peak maximum temperature (Tm) and the spectra of the crown ethers were studied. The results Tm of the crown ethers to increase significantly, and glycine and ammonium salts interfered the spectra of the crown ethers. The effect of sample size and "concentration" on Tm of the crowns also was investigated. The bigger sample size caused the Tm to be higher. No significant effect of the "concentration" on Tm was observed. It was concluded that tha smaller sample size provided better spectra with less interfererences and that some thermally stable reagents or support materials could be used to facilitate the sampling of crown ethers. More detailed study of the effects of iodides on Tm was recommended. In addition, more detailed investigation of the approach of using a CI source without reagent gases is needed. Switching to the CI configuration appears to be a simple and effective method for providing complementary information about the molecules.Ball State UniversityMuncie, IN 47306

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34

Cerrah, Ibrahim. "Crowds and public order policing : an analysis of crowds and interpretations of their behaviour based on observational studies in Turkey and England and Wales." Thesis, University of Leicester, 1995. http://hdl.handle.net/2381/35274.

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Between February 1992 and February 1995, observations were made of 33 heavily-policed crowd events occurring both in Turkey and England & Wales. Informal interviews were conducted with prominent Turkish and British police public order training instructors and practitioners. These interviews often occurred in the context of visits to specialist public order training locations where training exercises and drills were witnessed first hand. Finally, the researcher attended three major public order courses for senior British police officers. These data formed the bedrock of a comparative approach to understanding crowd behaviour and critically evaluating police crowd control techniques. This research analyses the underlying assumptions contained within the existing theories in the field and attempts to adjudicate on the validity of both classical and modern contributions to the understanding of the field. Two hypotheses are considered, first; 'Crowd phenomena like other social issues cannot be examined within the boundaries of a single discipline'. This has led to development of a theory, the 'Combined Factors Approach' (CFA) which attempts to examine the behaviour of crowd using a multitude of factors. The second hypothesis is; 'In terms of exercising their function in so-called public order events, the police, far from being a neutral institution serve and protect the interest of its political masters and the ruling classes rather than serving the entire community'. Observations of existing public order policing practices suggest the validity of a radical and Marxist argument, that the police are an apparatus of the state and therefore of the ruling classes. The thesis concludes that any public order policing regardless of the political system it serves, will tend to be relatively paramilitary and oppressive.

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Erikson, Mats. "Segmentation and classification of individual tree crowns : in high spatial resolution aerial images /." Uppsala : Centre for Image Analysis, Swedish Univ. of Agricultural Sciences, 2004. http://epsilon.slu.se/s320.pdf.

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Oliveira, Eduardo M. A. "Thermal and quantum analysis of a stored state in a photonic crystal CROW structure." Link to electronic thesis, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-112007-105238/.

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Thesis (M.S.) -- Worcester Polytechnic Institute. Keywords: CROW; PBG; PhC; coupled resonator optical waveguide; metamaterials; photonic crystal; Bloch wave; photonic band gap;dynamic waveguide; Brillouin zone; thermal spreading. Includes bibliographical references (p. 84-87).

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37

Slaughter, Derek Emerson. "Strip Crown Prediction: Developing a Refined Dynamic Roll-Stack Model for the Hot Rolling Process." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/34389.

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The steel industry has been producing flat plates through the process of hot rolling since the late 1600s. Hot rolling uses a series of rolls to progressively thin a strip of steel to a desired thickness. In deforming the strip, the rolling process causes variations in thickness across the width of the strip. These variations are commonly referred to as crown, which is specifically the difference in thickness between the center and edge of a strip. For most applications steel mill clients require flat products, or products with little variation in thickness. Therefore, variations represent wasted material which must be removed before the plate or sheet can be used in consumer products. Controlling the flatness of the metal strip is a high priority for the hot rolling business. The purpose of this work was to develop a 3-D dynamic model of the rolling process to simulate the behaviour of a strip while being rolled and predict its profile. To accomplish this task, much of the rolling process needed to be modeled. The profile of the strip is a product of the deformation of the rolls and frame within a mill stand. Therefore, not only did the geometry of these components need to be modeled, but the material properties and dynamic motion were required as well. The dynamic nature of the process necessitated the modeling of the rotation of the rolls and translation of the strip, aspects of rolling which are not typically simulated. Five models were developed during the project. The purpose of the first two models was to find the stiffnesses of the roll-stack and stand frame. The roll-stack refers to the rolls and their arrangement. The reference mill from which data was provided used a four-high roll-stack with two rolls above the strip and two below. The frame that holds the roll-stack, while massive, stretches when the strip is deformed between the rolls. This stretch changes the position of the rolls affecting the load and deformation of the strip. A lumped-mass model was created to simulate the dynamics of the roll-stack and frame. When the strip enters the gap between the rolls, there is a large impact force which causes the rolls to vibrate. The lumped-mass model was used to determine parameters to bring the system to steady state. The final two models simulated the entire rolling process with rotating rolls and moving strip. The 3-D dynamic rolling model was capable of predicting the strip profile due after exiting the rolls. Two calibrations were used to reduce model error before running a validation. The rolling causes thickness variation across the width of the metal strips; therefore, strips are intentionally rolled thick to meet a minimum thickness. In modern steel mills, specialized control systems are used to adjust parameters as the steel strip passes through each stand of rolls. Varying the parameters allows the thickness and profile of the strip to be controlled. Each stand may have several rolls in different configurations. These rolls are either work rolls, which directly contact the strip, or backup rolls, which contact the work rolls and stiffen the roll-stack. The stand frame holds the rolls and provides a means to position them. The validation results showed that the exit thickness, strip crown, and rolling load were less than 5% different from the values measured in the test data. The calibrated model was then used to derive strip crown sensitivities to gap, entry crown, work roll crown, and bending force. The 3-D dynamic model was able to predict the strip crown accurately when given calibrated information about the system. This model will be a useful tool for exploring the mechanics of hot rolling in ways that were not previously possible. Master of Science

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38

Larochelle, Benoit. "Multi-Agent Geo-Simulation of Crowds and Control Forces in conflict situations : Models, Application and Analysis." Thesis, Université Laval, 2009. http://www.theses.ulaval.ca/2009/26818/26818.pdf.

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Peu de modèles et de simulations qui décrivent les comportements de foule en situations de conflit impliquant des forces de l’ordre et des armes non-létales (NLW) existent. Ce mémoire présente des modèles d’agents de la foule et des forces de l’ordre ainsi que des NLWs dans des situations de conflit. Des groupes ainsi que leurs interactions et actions collectives sont explicitement modélisés, ce qui repousse les approches de simulation de foule existantes. Les agents sont caractérisés par des profils d’appréciation de l’agressivité et ils peuvent changer leurs comportements en relation avec la Théorie de l’identité sociale. Un logiciel a été développé et les modèles ont été calibrés avec des scénarios réalistes. Il a démontré la faisabilité technique de modèles sociaux aussi complexes pour des foules de centaines d’agents, en plus de générer des données pour évaluer l’efficacité des techniques d’intervention. Few models and simulations that describe crowd behaviour in conflict situations involving control forces and non-lethal weapons (NLW) exist. This thesis presents models for crowd agents, control forces, and NLWs in crowd control situations. Groups as well as their interactions and collective actions are explicitly modelled, which pushes further currently existing crowd simulation approaches. Agents are characterized by appreciation of aggressiveness profiles and they can change their behaviours in relation with the Social Identity theory. A software application was developed and the models were calibrated with realistic scenarios. It demonstrated the technical feasibility of such complex social models for crowds of hundreds of agents, as well generating data to assess the efficiency of intervention techniques.

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39

Larochelle, Benoît. "Multi-agent geo-simulation of crowds and control forces in conflict situations : models, application and analysis." Master's thesis, Université Laval, 2009. http://hdl.handle.net/20.500.11794/21359.

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Peu de modèles et de simulations qui décrivent les comportements de foule en situations de conflit impliquant des forces de l’ordre et des armes non-létales (NLW) existent. Ce mémoire présente des modèles d’agents de la foule et des forces de l’ordre ainsi que des NLWs dans des situations de conflit. Des groupes ainsi que leurs interactions et actions collectives sont explicitement modélisés, ce qui repousse les approches de simulation de foule existantes. Les agents sont caractérisés par des profils d’appréciation de l’agressivité et ils peuvent changer leurs comportements en relation avec la Théorie de l’identité sociale. Un logiciel a été développé et les modèles ont été calibrés avec des scénarios réalistes. Il a démontré la faisabilité technique de modèles sociaux aussi complexes pour des foules de centaines d’agents, en plus de générer des données pour évaluer l’efficacité des techniques d’intervention. Few models and simulations that describe crowd behaviour in conflict situations involving control forces and non-lethal weapons (NLW) exist. This thesis presents models for crowd agents, control forces, and NLWs in crowd control situations. Groups as well as their interactions and collective actions are explicitly modelled, which pushes further currently existing crowd simulation approaches. Agents are characterized by appreciation of aggressiveness profiles and they can change their behaviours in relation with the Social Identity theory. A software application was developed and the models were calibrated with realistic scenarios. It demonstrated the technical feasibility of such complex social models for crowds of hundreds of agents, as well generating data to assess the efficiency of intervention techniques.

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40

Matracia, Yoon-Mi(Sophie) L. "Pulpotomy to Stainless Steel Crown Ratio in Children with Early Childhood Caries: A Cross Sectional Analysis." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1242096142.

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41

Driega, Alex B. (Alexander Brooke) Carleton University Dissertation Chemistry. "An analysis of factors contributing to isotropic [superscript] 13C shifts in 1,2- Dialkoxybenzene and Cyclohexane derivatives." Ottawa, 1992.

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42

Barry, James Dominic Edward. "A barrister's role in the plea decision : an analysis of drivers affecting advice in the Crown Court." Thesis, Queen Mary, University of London, 2010. http://qmro.qmul.ac.uk/xmlui/handle/123456789/394.

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This thesis explores the reasons behind barristers' advice to defendants in the Crown Court on plea, primarily through interviews with criminal law practitioners themselves. Beginning with a critical overview of the current research, the thesis argues that the views of criminal barristers are a neglected significant source of information in developing an understanding of why particular advice is given. The thesis, in the context of other research, analyses the data from interviews conducted with current practitioners on the London and the Midlands Circuits, and discusses the various drivers that act upon barristers in deciding what advice to give. Starting with the actual advice given and the advising styles adopted, the thesis explores why guilty pleas might be advised and plea bargains sought with prosecutors. The research goes on to examine the impact of various influences, including legal, ethical, cultural, regional and financial to produce an overview of what factors impact upon a barrister's advice. The thesis argues that the current view of the Bar sustained in much of the literature is insufficiently nuanced and outdated, and that the reasons behind the advice given to defendants on plea are extraordinarily varied, occasionally contradictory, and highly complex. The thesis concludes that the data from the interviews warrants a rethink of why particular advice is given and that discovering what drives barristers’ advice is critical to formulating law and government policy.

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43

Stewart, William Elliott. "A Response Surface Exit Crown Model Built from the Finite Element Analysis of a Hot-Rolling Mill." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/45203.

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Nine independent and four dependent variables are used to build a response surface to calculate strip crown using the difference in the industry standard strip height measurements. The single element response surface in use provides the advantages of continuous derivatives and decouples rolling load from the determination of exit height. The data points to build the response surface are the product of a calibrated finite element model. The rolling dynamics in the finite element model creates a transient that requires nonlinear regression to find the system steady-state values. Weighted-least squares is used to build a response surface using isoparametric interpolation with the non-rectangular domain of the mill stands represented as a single element. The regression statistics, the 1-D projections, comparisons against other response surface models and the comparisons against an existing strip crown model are part the validation of the response surface generated. A four-high mill stand is modeled as a quarter-symmetry 3-D finite element model with an elastic-plastic material model. A comparison of the pressure distribution under the arc of contact with existing research supports the pressure distribution found with experiments conducted by Siebel and Lueg [16] and it also suggests the need for one improvement in the initial velocity for the strip in the finite element model. The strip exit heights show more sensitivity to change than strip exit crown in seven out of the nine independent variables, so a response surface built with the strip exit height is statistically superior to using the derived dependent variable strip exit crown. Sensitivity of strip exit crown and the strip exit heights to changes in work-roll crown are about equal. Backup-roll diameter sensitivity is small enough that oversampling for the mean trend has to be considered or ignore backup-roll altogether. Strip entry velocity is a new independent variable, unless the response surface is built from the derived variable, strip exit crown. A problem found is that the sensitivity of strip entry crown and work-roll crown requires a larger than typical incremental change to get a reliable measure of the change strip exit crown. A narrow choice of high and low strip entry crowns limits the usefulness of the final response surface. A recommendation is to consider the use of the strip cross-section as an exit crown predictor. Master of Science

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Fontaine, Keysha Ann. "Comparative Analysis of Ecological and Cultural Protection Schemes within a Transboundary Complex: The Crown of the Continent." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470753710.

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45

Crowe, Paul Richard. "The marmoset periodontal ligament : a T.E.M. morphometric analysis following incisor crown fracture, root canal therapy and orthodontic extrusion /." Title page, contents and summary only, 1989. http://web4.library.adelaide.edu.au/theses/09DM/09dmc953.pdf.

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Thesis (M.D.S.)--Dept. of Dentistry, Faculty of Dentistry, University of Adelaide, 1990. Spine title: A T.E.M. investigation of extrusion and R.C.T. on the marmoset periodontal ligament. Typescript (Photocopy). Includes bibliographical references (leaves 163-191).

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46

Smith, Nakeischea Loi. "Whose land is it anyway? : an analysis of the management and distribution of Crown Land in the Bahamas." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39941.

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Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2007. Includes bibliographical references (p. 133-138). Like many islands throughout the Caribbean, The Bahamas are now experiencing rapid growth and development in the form of large-scale luxury resorts and second homes. Consistent with a long history going back to the colonial era, these development trends are being driven by external factors - including the aging of the Baby Boomer generation, a scarcity of affordable waterfront land in North America, and shifting travel preferences post-9/11. But major policy decisions, now hotly debated, have also played an important role in shaping these development trends and their impacts. Through an economic development strategy known as the Anchor Projects, the Bahamian Government has tapped foreign demand for prime Bahamian land with the aim of reducing crowding on the capital island-city of Nassau, boosting the economies of the sparsely populated Family Islands, and providing residents of those islands with much-needed employment and infrastructure. (cont.) As a key concession to spur the Anchor Projects, Government has granted large tracts of publicly owned "Crown Land" at favorable prices to developers; but in a nation where natives are tied closely to Crown Land and where there is lack of a comprehensive land use framework that includes environmental management and public participation in development, this policy has triggered significant conflict among Government, developers, and Bahamians. resent Crown Land disposition policies that seem to benefit foreign investors and visitors at great expense to current and future generations of Bahamians; particularly where such policies are seemingly threatening to make housing unaffordable, overwhelm small-island cultures with newcomer needs, privatize cherished community commons, and generate conflicts over labor shortage. Using information gleaned from interviews with key informants, newspapers and journal articles, and data gathered from various Government agencies, this study examines the history of Crown Land management in The Bahamas, as well as the current valuation, pricing, and allocation of this vital public resource. (cont.) The thesis explores the risks in a non-sustainable development model where land tenure, tracking, and planning traditions are either missing or weak. Based on my findings, I offer several major recommendations: Create and implement a National Development and Land Use Plan, improve agency integration, clarify land tenures, implement and legislate programs for environmental protection and management, improve fiscal management of land resources, deepen the democracy, and address issues of sovereignty and changing social structure. by Nakeischea Loi Smith. M.C.P.

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Garza, Mario Nicholas. "Biophysical and Climate Analysis of the Mountain Pine Beetle (Dendroctonus ponderosae) Infestations in the Crown of the Continent, 1962 to 2014." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/75134.

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Mountain pine beetles (Dendroctonus ponderosae) are native insects that have decimated millions of hectares of mature pine (Pinaceae) forests in western North America. The purpose of this study is to investigate biophysical and climatic correlates of Mountain Pine Beetle (MPB) insect outbreaks in the Crown of the Continent Ecosystem (CCE) from 1962 to 2014 using Aerial Detection Survey (ADS) and climate data. Specific objectives were: 1) to develop statistical models to determine how selected biophysical correlates (slope, aspect, elevation, and latitude) and 2) to understand how local and global climate variables relate to the extent of the MPB infestations in the CCE, and 3) to contextualize the results of the models with historical climate data. Overall, the major findings of this study are: 1) despite its limitations, the ADS data seems suitable for analysis of beetle damage with respect to climate and topographic factors, on a regional scale, 2) there appears to be a link between local biophysical factors and winter precipitation and TPA within the CCE, and 3) a combination of a negative-phase PDO and La Niña is important in forecasting a decline in MPB spread, during a given year. This study is the first, to our knowledge, to explore spatio-temporal patterns of MPB outbreaks using biophysical factors, and both local and global climate variables, over a fifty-year timespan in the CCE. In the future, additional geospatial analyses may enable a landscape assessment of factors contributing to variability of MPB infestation and damage as this insect continues to spread. Master of Science

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Enechi, Theophilus Chukwuemeka. "The taper of clinical crown preparations done by dental students and dentists in two African countries: a comparative analysis." Thesis, University of the Western Cape, 2004. http://etd.uwc.ac.za/index.php?module=etd&amp.

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Crowns have been used since the 5th century AD to improve both the form and function of teeth in the mouth. A great proportion of the total expenditure on dental care is spent on the provision and replacement of crowns and bridges and the number is increasing every year. A full coverage crown is a restoration placed over a single prepared tooth or it acts as an abutment in a bridge for the restoration of a missing tooth or teeth. Crowns are considered successful only when they meet both the aesthetic and functional requirements of the patient. For these to be met, certain principles for the preparation of the abutment tooth must be adhered to such principles include features that are incorporated in the tooth preparation that enable it to withstand the forces of dislodgement that the tooth is exposed to both at rest and function. These features are described as the retention and resistance form of the preparation and the important aspect of these is taper. The taper of a tooth preparation is inversely proportional to the retention provided by the preparation. Volumes have been written on the difficulties encountered in making crowns with an adequate taper. Training, experience and operating conditions are among the many determinants of taper obtained by clinicians. Taper values of 2&ordm to 5&ordm were recommended initially for successful crown restorations but over time it was realized that these values were difficult to achieve under clinical conditions without creating undercuts in the preparation. Besides it was shown that even higher taper values might provide adequate retention for crowns. In addition, extra-retentive features such as axial grooves and boxes have been shown to improve retention of crowns. Many of the new luting cements also have adhesive properties that contribute to better retention of crowns and bridges. Various studies have established the prevalent taper obtained by dental students, general practice dentists, residents and prosthodontists while some of these studies have compared the prevalent taper among the different categories of clinicians. None of the studies so far reported has shown the prevalent taper in this environment all without exception have investigated conditions in Europe, North America and Asia. Aim: This study therefore investigated the prevalent taper obtained routinely under clinical conditions by dental students, general dental practitioners and prosthodontists in two African countries and compared them with the recommended range of 10&ordm to 22&ordm . Method: 432 dies of teeth prepared by students, general practice dentists, resident and practicing prosthodontists were collected and analysed for taper using the double silicone technique. This involved making silicone replicas of the dies, sectioning these at various points and using photographs of the sections to measure their taper. Comparisons of the tapers obtained were carried out between the students, general practitioners and prosthodontists as well as between taper obtained on the different tooth types. Results: Taper ranging from 2&ordm to 100&ordm was obtained on the various tooth types. A mean mesio-distal (MD) and bucco-lingual (BL) taper of 22.5&ordm (SD 11.2) and 26.2&ordm (SD 11.1) respectively and a mean overall taper of 24.3&ordm (SD 9.2) were obtained. Prosthodontists obtained the lowest taper (MD = 20.5&ordm (SD 10.6)), BL = 24. 5&ordm (SD 10.1) and a mean overall taper of 22.5&ordm (SD 8.4). Students were second with a mean MD taper of 23.8&ordm (SD 10.1), BL taper of 26.1&ordm (SD 10.9) and a mean overall taper of 25.0&ordm (SD 8.4). The general practice dentists obtained a mean MD and BL taper of 24.5&ordm (SD 12.4) and 29.1&ordm (SD 12.1) respectively and a mean overall taper of 26.8&ordm (SD 10.6). The lowest taper was seen on premolars while the highest was on molars. Conclusion and recommendation: Most of the preparations analysed had a taper outside the recommended range of 10&ordm to 22&ordm . However, these tapers were similar to those found in other studies. Routinely incorporating extra-retentive features into crown preparation designs will improve success of crown restorations and adhesive cements should be used whenever conditions that allow for adequate retention are not met. The importance of taper should be emphasized more in dental schools and tooth preparation support systems should be used for teaching wherever possible. The need for regular refresher courses for practicing dentists and prosthodontists cannot be over-emphasized.

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Fullen, Matthew Christopher. "“Gray Hair is a Crown of Glory”: A Multivariate Analysis of Wellness, Resilience, and Internalized Ageism in Older Adulthood." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1477987561803291.

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Reynolds, Mark (Mark V. ). Carleton University Dissertation Chemistry. "Conformational analysis of some model crown ethers and analogues via 1H and 13C NMR spectroscopy and X-ray crystallography." Ottawa, 1994.

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Dissertations / Theses on the topic 'Analysis crowd'

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