Relevant bibliographies by topics / Crowd Flow

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Crowd Flow'

Author: Grafiati
Published: 11 December 2022
Last updated: 26 January 2023

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Journal articles on the topic "Crowd Flow"

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Lin, Ziqian, Jie Feng, Ziyang Lu, Yong Li, and Depeng Jin. "DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1020–27. http://dx.doi.org/10.1609/aaai.v33i01.33011020.

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Crowd flow prediction is of great importance in a wide range of applications from urban planning, traffic control to public safety. It aims to predict the inflow (the traffic of crowds entering a region in a given time interval) and outflow (the traffic of crowds leaving a region for other places) of each region in the city with knowing the historical flow data. In this paper, we propose DeepSTN+, a deep learning-based convolutional model, to predict crowd flows in the metropolis. First, DeepSTN+ employs the ConvPlus structure to model the longrange spatial dependence among crowd flows in different regions. Further, PoI distributions and time factor are combined to express the effect of location attributes to introduce prior knowledge of the crowd movements. Finally, we propose an effective fusion mechanism to stabilize the training process, which further improves the performance. Extensive experimental results based on two real-life datasets demonstrate the superiority of our model, i.e., DeepSTN+ reduces the error of the crowd flow prediction by approximately 8%∼13% compared with the state-of-the-art baselines.
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Feng, Jie, Yong Li, Ziqian Lin, Can Rong, Funing Sun, Diansheng Guo, and Depeng Jin. "Context-aware Spatial-Temporal Neural Network for Citywide Crowd Flow Prediction via Modeling Long-range Spatial Dependency." ACM Transactions on Knowledge Discovery from Data 16, no. 3 (June 30, 2022): 1–21. http://dx.doi.org/10.1145/3477577.

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Crowd flow prediction is of great importance in a wide range of applications from urban planning, traffic control to public safety. It aims at predicting the inflow (the traffic of crowds entering a region in a given time interval) and outflow (the traffic of crowds leaving a region for other places) of each region in the city with knowing the historical flow data. In this article, we propose DeepSTN+, a deep learning-based convolutional model, to predict crowd flows in the metropolis. First, DeepSTN+ employs the ConvPlus structure to model the long-range spatial dependence among crowd flows in different regions. Further, PoI distributions and time factor are combined to express the effect of location attributes to introduce prior knowledge of the crowd movements. Finally, we propose a temporal attention-based fusion mechanism to stabilize the training process, which further improves the performance. Extensive experimental results based on four real-life datasets demonstrate the superiority of our model, i.e., DeepSTN+ reduces the error of the crowd flow prediction by approximately 10%–21% compared with the state-of-the-art baselines.
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JOHANSSON, ANDERS, DIRK HELBING, HABIB Z. AL-ABIDEEN, and SALIM AL-BOSTA. "FROM CROWD DYNAMICS TO CROWD SAFETY: A VIDEO-BASED ANALYSIS." Advances in Complex Systems 11, no. 04 (August 2008): 497–527. http://dx.doi.org/10.1142/s0219525908001854.

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The study of crowd dynamics is interesting because of the various self-organization phenomena resulting from the interactions of many pedestrians, which may improve or obstruct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate densities, it was recently discovered that stop-and-go waves [D. Helbing et al., Phys. Rev. Lett.97 (2006) 168001] and a phenomenon called "crowd turbulence" can occur at high pedestrian densities [D. Helbing et al., Phys. Rev. E75 (2007) 046109]. Although the behavior of pedestrian crowds under extreme conditions is decisive for the safety of crowds during the access to or egress from mass events as well as for situations of emergency evacuation, there is still a lack of empirical studies of extreme crowding. Therefore, this paper discusses how one may study high-density conditions based on suitable video data. This is illustrated at the example of pilgrim flows entering the previous Jamarat Bridge in Mina, 5 kilometers from the Holy Mosque in Makkah, Saudi-Arabia. Our results reveal previously unexpected pattern formation phenomena and show that the average individual speed does not go to zero even at local densities of 10 persons per square meter. Since the maximum density and flow are different from measurements in other countries, this has implications for the capacity assessment and dimensioning of facilities for mass events. When conditions become congested, the flow drops significantly, which can cause stop-and-go waves and a further increase of the density until critical crowd conditions are reached. Then, "crowd turbulence" sets in, which may trigger crowd disasters. For this reason, it is important to operate pedestrian facilities sufficiently below their maximum capacity and to take measures to improve crowd safety, some of which are discussed in the end.
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He Wu, Li Qi, and Yunbo Rao. "Crowd Flow-Based Information for Crowd Simulation." International Journal of Digital Content Technology and its Applications 6, no. 23 (December 31, 2012): 145–52. http://dx.doi.org/10.4156/jdcta.vol6.issue23.17.

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Han, Bing, Daoye Zhu, Chengqi Cheng, Jiawen Pan, and Weixin Zhai. "Patterns of Nighttime Crowd Flows in Tourism Cities Based on Taxi Data—Take Haikou Prefecture as an Example." Remote Sensing 14, no. 6 (March 15, 2022): 1413. http://dx.doi.org/10.3390/rs14061413.

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The study of patterns of crowd flows represents an emerging and expanding research field. The most straightforward and efficient approach to investigate the patterns of crowd flows is to concentrate on traffic flow. However, assessments of simple point-to-point movement frequently lack universal validity, and little research has been conducted on the regularity of nighttime movement. Due to the suspension of public transportation at night, taxi orders are critical in capturing the features of nighttime crowd flows in a tourism city. Using Haikou as an example, this paper proposes a mixed Geogrid Spatio-temporal model (MG-STM) for the tourism city in order to address the challenges. Firstly, by collecting the pick-up/drop-off/in-out flow of crowds, this research uses DCNMF dimensionality reduction to extract semi-supervised spatio-temporal variation features and the K-Means clustering method to determine the cluster types of nighttime crowd flows’ changes in each geogrid. Secondly, by constructing a mixed-evaluation model based on LJ1-01 nighttime light data, crowd flows’ clusters, and land use data in geogrid-based regions, the pattern of nighttime crowd flows in urban land use areas is successfully determined. The results suggest that MG-STM can estimate changes in the number of collective flows in various regions of Haikou effectively and appropriately. Moreover, population density of land use areas shows a high positive correlation with the lag of crowd flows. Each 5% increase in population density results in a 30-min delay in the peak of crowd flows. The MG-STM will be extremely beneficial in developing and implementing systems for criminal tracking and pandemic prevention.
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Zang, Tianzi, Yanmin Zhu, Yanan Xu, and Jiadi Yu. "Jointly Modeling Spatio–Temporal Dependencies and Daily Flow Correlations for Crowd Flow Prediction." ACM Transactions on Knowledge Discovery from Data 15, no. 4 (June 2021): 1–20. http://dx.doi.org/10.1145/3439346.

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Crowd flow prediction is a vital problem for an intelligent transportation system construction in a smart city. It plays a crucial role in traffic management and behavioral analysis, thus it has raised great attention from many researchers. However, predicting crowd flows timely and accurately is a challenging task that is affected by many complex factors such as the dependencies of adjacent regions or recent crowd flows. Existing models mainly focus on capturing such dependencies in spatial or temporal domains and fail to model relations between crowd flows of distant regions. We notice that each region has a relatively fixed daily flow and some regions (even very far away from each other) may share similar flow patterns which show strong correlations among them. In this article, we propose a novel model named Double-Encoder which follows a general encoder–decoder framework for multi-step citywide crowd flow prediction. The model consists of two encoder modules named ST-Encoder and FR-Encoder to model spatial-temporal dependencies and daily flow correlations, respectively. We conduct extensive experiments on two real-world datasets to evaluate the performance of the proposed model and show that our model consistently outperforms state-of-the-art methods.
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Zuo, Zhongyi, Wei Yin, Guangchuan Yang, Yunqi Zhang, Jiawen Yin, and Hongsheng Ge. "Determination of Bus Crowding Coefficient Based on Passenger Flow Forecasting." Journal of Advanced Transportation 2019 (April 1, 2019): 1–12. http://dx.doi.org/10.1155/2019/2751916.

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To improve bus passengers’ degree of comfort, it is necessary to determine the real-time crowd coefficient in the bus. With this concern, this paper employed the RBF Neural Networks approach to predict the number of passengers in the bus based on historical data. To minimize the impact of the randomness of passenger flow on the determination of bus crowd coefficient, a cloud model-based bus crowd coefficient identification method was proposed. This paper first selected the performance measurements for determining bus crowd coefficient and calculated the digital characteristics of the cloud model based on the boundary values of the selected performance measures under six Levels-of-Service (LOSs). Then the subclouds obtained under the six LOSs were synthesized into a standard cloud. According to the predicted number of passengers in the bus, the passenger density and loading frequency were calculated, which were imported into the cloud generator to set up the bus crowd coefficient identification model. By calculating the crowd degrees of identification cloud and template cloud at each site, this paper determined the crowed coefficient of each bus station. Finally, this paper took the bus line No. 10 in Dalian city as case study to verify the proposed model. It was found that the crowd coefficients of the selected route ranged from 60.265 to 109.825, and the corresponding LOSs ranged between C and F. The method of discriminating bus crowding coefficient can not only effectively determine the congestion coefficient, but also effectively avoid the fuzziness and randomness of the crowding coefficient judgment in the bus, which has strong theoretical and practical significance.
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Zhou, Yirong, Hao Chen, Jun Li, Ye Wu, Jiangjiang Wu, and Luo Chen. "Large-Scale Station-Level Crowd Flow Forecast with ST-Unet." ISPRS International Journal of Geo-Information 8, no. 3 (March 13, 2019): 140. http://dx.doi.org/10.3390/ijgi8030140.

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High crowd mobility is a characteristic of transportation hubs such as metro/bus/bike stations in cities worldwide. Forecasting the crowd flow for such places, known as station-level crowd flow forecast (SLCFF) in this paper, would have many benefits, for example traffic management and public safety. Concretely, SLCFF predicts the number of people that will arrive at or depart from stations in a given period. However, one challenge is that the crowd flows across hundreds of stations irregularly scattered throughout a city are affected by complicated spatio-temporal events. Additionally, some external factors such as weather conditions or holidays may change the crowd flow tremendously. In this paper, a spatio-temporal U-shape network model (ST-Unet) for SLCFF is proposed. It is a neural network-based multi-output regression model, handling hundreds of target variables, i.e., all stations’ in and out flows. ST-Unet emphasizes stations’ spatial dependence by integrating the crowd flow information from neighboring stations and the cluster it belongs to after hierarchical clustering. It learns the temporal dependence by modeling the temporal closeness, period, and trend of crowd flows. With proper modifications on the network structure, ST-Unet is easily trained and has reliable convergency. Experiments on four real-world datasets were carried out to verify the proposed method’s performance and the results show that ST-Unet outperforms seven baselines in terms of SLCFF.
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Muhammed Anees, V., and G. Santhosh Kumar. "Identification of crowd behaviour patterns using stability analysis." Journal of Intelligent & Fuzzy Systems 42, no. 4 (March 4, 2022): 2829–43. http://dx.doi.org/10.3233/jifs-200667.

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Crowd behaviour analysis and management have become a significant research problem for the last few years because of the substantial growth in the world population and their security requirements. There are numerous unsolved problems like crowd flow modelling and crowd behaviour detection, which are still open in this area, seeking great attention from the research community. Crowd flow modelling is one of such problems, and it is also an integral part of an intelligent surveillance system. Modelling of crowd flow has now become a vital concern in the development of intelligent surveillance systems. Real-time analysis of crowd behavior needs accurate models that represent crowded scenarios. An intelligent surveillance system supporting a good crowd flow model will help identify the risks in a wide range of emergencies and facilitate human safety. Mathematical models of crowd flow developed from real-time video sequences enable further analysis and decision making. A novel method identifying eight possible crowd flow behaviours commonly seen in the crowd video sequences is explained in this paper. The proposed method uses crowd flow localisation using the Gunnar-Farneback optical flow method. The Jacobian and Hessian matrix analysis along with corresponding eigenvalues helps to find stability points identifying the flow patterns. This work is carried out on 80 videos taken from UCF crowd and CUHK video datasets. Comparison with existing works from the literature proves our method yields better results.
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Xia, Tong, Junjie Lin, Yong Li, Jie Feng, Pan Hui, Funing Sun, Diansheng Guo, and Depeng Jin. "3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction." ACM Transactions on Knowledge Discovery from Data 15, no. 6 (June 28, 2021): 1–21. http://dx.doi.org/10.1145/3451394.

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Crowd flow prediction is an essential task benefiting a wide range of applications for the transportation system and public safety. However, it is a challenging problem due to the complex spatio-temporal dependence and the complicated impact of urban structure on the crowd flow patterns. In this article, we propose a novel framework, 3- D imensional G raph C onvolution N etwork (3DGCN), to predict citywide crowd flow. We first model it as a dynamic spatio-temporal graph prediction problem, where each node represents a region with time-varying flows, and each edge represents the origin–destination (OD) flow between its corresponding regions. As such, OD flows among regions are treated as a proxy for the spatial interactions among regions. To tackle the complex spatio-temporal dependence, our proposed 3DGCN can model the correlation among graph spatial and temporal neighbors simultaneously. To learn and incorporate urban structures in crowd flow prediction, we design the GCN aggregator to be learned from both crowd flow prediction and region function inference at the same time. Extensive experiments with real-world datasets in two cities demonstrate that our model outperforms state-of-the-art baselines by 9.6%∼19.5% for the next-time-interval prediction.
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Dissertations / Theses on the topic "Crowd Flow"

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Enge, Leo, and Felix Liu. "Crowd Simulation Using Flow Tiles." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231025.

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Crowd simulations are being used in an increasing number of different applications, like evacuation scenarios, video games and movie special effects This creates a demand for crowd simulators that are simple to use and accessible to users of varying backgrounds. We will study the flow tile method proposed by Chenney [1], which provides an intuitive way of interactively designing divergence free velocity fields for various applications. A reimplementation of Chenney's method will be given and the implementation will be evaluated in terms of user-friendliness and how well the use of static spatially defined velocity fields suits crowd simulation. Furthermore the possibility of using the velocity fields for other related applications such as mobile robotics will be touched on as well.
Simuleringar av folkmassor används i ett ökande antal olika tillämpningar, som evakueringsscenarion, datorspel och speciale­ffekter för film. Detta skapar en efterfrågan efter simulatorer som är enkla att använda och tillgängliga för användare från olika ämnesområden och bakgrunder. Vi kommer att studera flow tile-metoden som Chenney [1] föreslår. Metoden är ett intuitivt och interaktivt sätt att skapa divergensfria hastighetsfält för olika tillämpningar. En omimplementation av Chenneys metod kommer att ges och implementationen kommer att evalueras i termer av användarvänlighet och hur väl användningen av hastighetsfält som är statiska och definierade i rummet passar för simulering av folkmassor. Vidare kommer möjligheten att använda hastighetsfälten för andra liknande tillämpningar, som robotik, att diskuteras också.
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Jargård, Anna, and Robert Kindwall. "Improving Flow Rate with Funnel-shaped Space Design using Crowd Simulation for Large Crowds." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259008.

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Crowd simulation is a technique used to model real people as agents in a computer-generated environment. Generating simulated crowds can help the research process of testing with agents in multiple scenarios without having to use real people. The flow of large crowds in different space-designs vary and this thesis will examine flow rates in funnel-shaped constructions and bottleneck constructions with the help of computer-generated crowd simulations. These flows can impact individuals to the extent where they are hurt by misdirected forces. Two different variables are defined for the funnel-shaped construction: corridor width and funnel-angle. For the bottleneck construction, there is only a corridor width property. Agents moving through an environment only move in one direction with no possibilities of a headon collision. Timing the agents that walk through the environments and looking at the forces they form shows that the funnels had a better flow and took less time than the bottlenecks. When looking at the different widths of the corridor the wider constructions was faster than all of the narrower constructions except the case with the narrow 15-degree funnel that was faster than the wide bottleneck. Introducing a funnel-shaped construction shows an improvement of the flow rate where you get better results the lower the angles. Applications of the funnel-shaped construction can include urban planning and architecture for spaces that have a capacity for large crowds, where an improvement in flow rate can make the space safer in an evacuation.
Simulation av folkmassor är en teknik som används för att modellera riktiga personer i en datorgenererad miljö som agenter. Att generera simulerade folkmassor kan hjälpa till med forskningsprocessen för testning av agenter i flertal scenarion utan att behöva använda riktiga personer. Flödet för folkmassor kan i hög grad variera för olika rumskonstruktioner. I den här avhandlingen undersöks flödeshastigheten i flaskhals- och trattformadekonstruktioner med hjälp av datorgenererade simulationer. Flödena kan påverka individer till den grad så att de skadas av missriktade krafter. Två variabler för de trattformade konstruktionerna är definerade, där den ena är bredden på öppningen till korridoren och den andra är vinkeln på tratten. För flaskhalskonstruktionerna används endast variabeln för bredden. Agenter i konstruktionen rör sig i samma riktning så det finns inte någon risk för frontalkollision. Resultat från tidtagning och kraftpilarnas riktning när agenterna går igenom konstruktionerna visar att en trattformad konstruktion ger ett bättre flöde samt tar mindre tid. En flaskhalskonstruktion med en bredare öppning ger bättre resultat än alla konstruktioner med en smalare öppning förutom den med 15-gradig vinkel på tratten. Att introducera en trattform till konstruktionen visar på en förbättrad flödeshastighet där lägre trattvinklar ger bättre resultat. Applikationer av den trattformade konstruktionen kan inkludera stadsplanering och arkitektur för rum som har en kapacitet för stora folkmassor, där en förbättring av flödeshastighet kan göra rummen sakrare i en evakuering.
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Ryan, David Andrew. "Crowd monitoring using computer vision." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/65652/1/David_Ryan_Thesis.pdf.

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Novel computer vision techniques have been developed for automatic monitoring of crowed environments such as airports, railway stations and shopping malls. Using video feeds from multiple cameras, the techniques enable crowd counting, crowd flow monitoring, queue monitoring and abnormal event detection. The outcome of the research is useful for surveillance applications and for obtaining operational metrics to improve business efficiency.
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Elbadramany, Iman K. "Towards calibration of optical flow of crowd videos using observed trajectories." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4889.

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The Particle Image Velocimetry optical flow algorithm had better correspondence with the velocity vectors of manually tracked crowd members than results obtained using the Lukas-Kanade method. Here, also, it was found that 40x40 pixel cells were better than 15x15. A second attempt at quantifying the correlation between optical flow and actual crowd member velocities was studied using simulations. Two processes were researched, which utilized geometrical correction of the perspective distortion of the crowd videos. One process geometrically corrects the video, and then obtains optical flow data. The other obtains optical flow data from video, and then geometrically corrects the data. The results indicate that the first process worked better. Correlation was calculated between sets of data obtained from the average of twenty frames. This was found to be higher than calculating correlations between the velocities of cells in each pair of frames. An experiment was carried out to predict crowd tracks using optical flow and a calculated parameter, beta, seems to give promising results.; The need exists for finding a quantitative method for validating crowd simulations. One approach is to use optical flow of videos of real crowds to obtain velocities that can be used for comparison to simulations. Optical flow, in turn, needs to be calibrated to be useful. It is essential to show that optical flow velocities obtained from crowd videos can be mapped into the spatially averaged velocities of the observed trajectories of crowd members, and to quantify the extent of the correlation of the results. This research investigates methods to uncover the best conditions for a good correlation between optical flow and the average motion of individuals in crowd videos, with the aim that this will help in the quantitative validation of simulations. The first approach was to use a simple linear proportionality relation, with a single coefficient, alpha, between velocity vector of the optical flow and observed velocity of crowd members in a video or simulation. Since there are many variables that affect alpha, an attempt was made to find the best possible conditions for determining alpha, by varying experimental and optical flow settings. The measure of a good alpha was chosen to be that alpha does not vary excessively over a number of video frames. Best conditions of low coefficient of variation of alpha using the Lucas-Kanade optical flow algorithm were found to be when a larger aperture of 15x15 pixels was used, combined with a smaller threshold. Adequate results were found at cell size 40x40 pixels; the improvement in detecting details when smaller cells are used did not reduce the variability of alpha, and required much more computing power. Reduction in variability of alpha can be obtained by spreading the tracked location of a crowd member from a pixel into a rectangle.
ID: 030423090; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.)--University of Central Florida, 2011.; Includes bibliographical references (p. 104-108).
M.S.
Masters
Sciences
Modeling and Simulation
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Brocklehurst, David. "People flow modelling : benefits and applications within industry." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/795.

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Within the design of any building, there is a requirement for designers to understand the intended purposes of the building and the elements that influence performance. These elements can be as tangible as providing a lecture hall within a university or relatively intangible such as the environmental temperatures of the rooms. The elements involved are generally recognised within the design industry and a combined force of engineers, architects, and specialist advisors work together to ensure all of the elements are in place for each new design. However, one element affecting performance that has not yet been comprehensively covered (at least for many building types) is that relating to occupant movement and the influence this has on experience and hence performance. For example, the number of times people have to negotiate cross-flow environments in a train station before becoming agitated is unknown. Also, the average distance people will walk through a shopping centre before becoming tired and ending the activity is unknown. Even so, they will both be impacted upon by the design and they will both reflect back on the performance of the design. Before starting this research, it was realised by the research engineer that there was only a limited understanding and application of people flow analyses within industry and, where it existed, it was solely related to transport terminals, pedestrian walkways/crossings, sports stadia arrivals/egress, and evacuation analyses.
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Roudneff, Aude. "Modelisation macroscopique de mouvements de foule." Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00678596.

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Nous étudions dans ce travail les mouvements de foule intervenant dans les situa- tions d'urgence. Nous proposons un modèle macroscopique (la foule est représentée par une densité de personnes) obéissant à deux principes très simples. Tout d'abord, chaque personne possède une vitesse souhaitée (typiquement celle qui la mène vers la sortie), qu'elle adopterait en l'absence des autres. Ensuite, la foule doit respecter une contrainte de congestion, et la densité de personnes doit rester inférieure à une valeur fixée. Cette contrainte impose une vitesse de déplacement différente de la vitesse souhaitée. Nous choisissons de prendre comme vitesse réelle celle qui est la plus proche, au sens des moindres carrés, de la vitesse souhaitée, parmi les champs de vitesses admissibles, au sens où ils respectent la contrainte de densité maximale. Le modèle obtenu s'écrit sous la forme d'une équation de transport impliquant une vitesse peu régulière a priori, et qui ne peut être étudiée par des méthodes classiques. Nous démontrons un résultat d'existence grâce à la théorie du transport optimal, tout d'abord dans le cas d'une vitesse donnée comme le gradient d'une fonction, puis dans le cas général. Nous mettons également en œuvre un schéma numérique de type catching-up : à chaque pas de temps, la densité est déplacée selon le champ de vitesse souhaitée, puis est projetée sur l'ensemble des densités admissibles. Les résultats obtenus fournissent des temps d'évacuation dont l'ordre de grandeur est proche de la réalité.
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Malla, Tika Kumari. "Case Studies to Learn Human Mapping Strategies in a Variety of Coarse-Grained Reconfigurable Architectures." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984195/.

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Computer hardware and algorithm design have seen significant progress over the years. It is also seen that there are several domains in which humans are more efficient than computers. For example in image recognition, image tagging, natural language understanding and processing, humans often find complicated algorithms quite easy to grasp. This thesis presents the different case studies to learn human mapping strategy to solve the mapping problem in the area of coarse-grained reconfigurable architectures (CGRAs). To achieve optimum level performance and consume less energy in CGRAs, place and route problem has always been a major concern. Making use of human characteristics can be helpful in problems as such, through pattern recognition and experience. Therefore to conduct the case studies a computer mapping game called UNTANGLED was analyzed as a medium to convey insights of human mapping strategies in a variety of architectures. The purpose of this research was to learn from humans so that we can come up with better algorithms to outperform the existing algorithms. We observed how human strategies vary as we present them with different architectures, different architectures with constraints, different visualization as well as how the quality of solution changes with experience. In this work all the case studies obtained from exploiting human strategies provide useful feedback that can improve upon existing algorithms. These insights can be adapted to find the best architectural solution for a particular domain and for future research directions for mapping onto mesh-and- stripe based CGRAs.
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Wild, Peter Gareth. "The use of immobilised crown ethers as in-situ protecting groups for organic synthesis within flow reactors." Thesis, University of Hull, 2008. http://hydra.hull.ac.uk/resources/hull:1180.

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Organic synthesis often requires one functional group of a bifunctionalised compound to be rendered temporarily inert to allow the selective reaction of another moiety. While protecting groups are used to remove the problem of the functional group incompatibility, they also raise other issues such as increasing the length of the synthetic pathway (by at least two steps – protection and deprotection), generally leading to an increase in cost and a decrease in yield. The protecting group is often selected based upon the deprotection conditions, leading to the requirement for orthogonal protecting groups. Crown ethers are commonly associated with the complexation of metal ions, but the 18-crown-6 species also readily bind ammonium ions with complexation occurring via hydrogen bonding. As discussed in Chapter 1, crown ethers have previously been employed for N-protection in this way, to successfully facilitate the reaction of bifunctional compounds, though they have exhibited very little selectivity and reaction control. Isolation of the desired product from the resulting reaction mixture has also proven to be problematic.Over recent years there has been a large increase in the volume of organic protocols conducted in micro and continuous flow reactors. Utilising the high surface to volume ratio obtained under these reaction conditions, greater reaction control of many common and specialised organic syntheses has been reported. Building upon literature precedent, the work herein reports the immobilisation of an 18-crown-6 ether derivativeonto a solid-support and its incorporation into a continuous flow reactor to enable sequestration of the primary amine salt of a bi-functionalised compound. This effectively affords a non-covalent N-protection strategy allowing the selective reaction of the remaining moiety. The desired product is subsequently recovered as the free amine by a simple process of decomplexation using an organic base.
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Coelho, Renato Schattan Pereira 1987. "Simulação de multidões e planejamento probabilístico para otimização dos tempos de semáforos." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275643.

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Orientadores: Siome Klein Goldenstein, Jacques Wainer
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação
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Resumo: O trânsito é um problema cada vez maior nas cidades, consumindo recursos e agravando a poluição; em São Paulo perdem-se cerca de R$33 bilhões por ano por causa do trânsito. Neste trabalho de mestrado desenvolvemos um sistema que une as áreas de simulação de multidões e planejamento probabilístico para otimizar semáforos de tempo fixo. Essas duas áreas apresentam algoritmos que permitem soluções eficientes para os problemas, mas a sua aplicação ainda depende largamente da intervenção de especialistas no problema a ser estudado, seja descrevendo o problema de planejamento probabilístico, seja interpretando os dados devolvidos pelo simulador. Nosso sistema diminui essa dependência ao utilizar autômatos celulares para simular o tráfego e gerar informações que são então utilizadas para descrever o problema de planejamento probabilístico. Com isso podemos: (i) reduzir a necessidade de coleta de dados, que passam a ser gerados pelo simulador e (ii) produzir bons planos para o controle de semáforos de tempo fixo sem que seja necessária a intervenção de especialistas para a análise dos dados. Nos dois testes realizados a solução proposta pelo sistema diminuiu o tempo médio de percurso em 18:51% e 13:51%, respectivamente
Abstract: Traffic is an ever increasing problem, draining resources and aggravating pollution. In Sao Paulo, for instance, financial losses caused by traffic represent a sum of about R$33 billions a year. In this work we've developed a system that puts together the areas of Crowd Simulation and Probabilistic Planning to optimize fixed time traffic lights. Although both areas present good algorithms their use is limited by their reliance on specialists, whether to describe the probabilistic planning problem or to analyze the data produced by the simulations. Our approach contributes to minimize this dependence by using cellular automata simulations to generate the data that is used to describe the probabilistic planning problem. This allows us to: (i) reduce the amount of data collection, since the data is now generated by the simulator and (ii) produce good policies for fixed time traffic light control without the intervention of specialists to analyze the data. In the two tests performed the solution proposed by the system was able to reduce travel times by 18:51% and 13:51%, respectively
Mestrado
Ciência da Computação
Mestre em Ciência da Computação
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Reda, Fatima Al. "Modélisation de mouvement de foules avec contraintes variées." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS235/document.

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Dans cette thèse, nous nous intéressons à la modélisation de mouvements de foules. Nous proposons un modèle microscopique basé sur la théorie des jeux. Chaque individu a une certaine vitesse souhaitée, celle qu'il adopterait en l'absence des autres. Une personne est influencée par certains de ses voisins, pratiquement ceux qu'elle voit devant elle. Une vitesse réelle est considérée comme possible si elle réalise un équilibre de Nash instantané: chaque individu fait son mieux par rapport à un objectif personnel (vitesse souhaitée), en tenant compte du comportement des voisins qui l'influencent. Nous abordons des questions relatives à la modélisation ainsi que les aspects théoriques du problème dans diverses situations, en particulier dans le cas où chaque individu est influencé par tous les autres, et le cas où les relations d'influence entre les individus présentent une structure hiérarchique. Un schéma numérique est développé pour résoudre le problème dans le second cas (modèle hiérarchique) et des simulations numériques sont proposées pour illustrer le comportement du modèle. Les résultats numériques sont confrontés avec des expériences réelles de mouvements de foules pour montrer la capacité du modèle à reproduire certains effets.Nous proposons une version macroscopique du modèle hiérarchique en utilisant les mêmes principes de modélisation au niveau macroscopique, et nous présentons une étude préliminaire des difficultés posées par cette approche.La dernière problématique qu'on aborde dans cette thèse est liée aux cadres flot gradient dans les espaces de Wasserstein aux niveaux continu et discret. Il est connu que l'équation de Fokker-Planck peut s'interpréter comme un flot gradient pour la distance de Wasserstein continue. Nous établissons un lien entre une discrétisation spatiale du type Volume Finis pour l'équation de Fokker-Planck sur une tesselation de Voronoï et les flots gradient sur le réseau sous-jacent, pour une distance de type Wasserstein récemment introduite sur l'espace de mesures portées par les sommets d'un réseaux
We are interested in the modeling of crowd motion. We propose a microscopic model based on game theoretic principles. Each individual is supposed to have a desired velocity, it is the one he would like to have in the absence of others. We consider that each individual is influenced by some of his neighbors, practically the ones that he sees. A possible actual velocity is an instantaneous Nash equilibrium: each individual does its best with respect to a personal objective (desired velocity), considering the behavior of the neighbors that influence him. We address theoretical and modeling issues in various situations, in particular when each individual is influenced by all the others, and in the case where the influence relations between individuals are hierarchical. We develop a numerical strategy to solve the problem in the second case (hierarchical model) and propose numerical simulations to illustrate the behavior of the model. We confront our numerical results with real experiments and prove the ability of the hierarchical model to reproduce some phenomena.We also propose to write a macroscopic counterpart of the hierarchical model by translating the same modeling principles to the macroscopic level and make the first steps towards writing such model.The last problem tackled in this thesis is related to gradient flow frameworks in the continuous and discrete Wasserstein spaces. It is known that the Fokker-Planck equation can be interpreted as a gradient flow for the continuous Wasserstein distance. We establish a link between some space discretization strategies of the Finite Volume type for the Fokker- Planck equation in general meshes (Voronoï tesselations) and gradient flows on the underlying networks of cells, in the framework of discrete Wasserstein-like distance on graphs recently introduced
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Books on the topic "Crowd Flow"

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Rosini, Massimiliano Daniele. Macroscopic Models for Vehicular Flows and Crowd Dynamics: Theory and Applications: Classical and Non–Classical Advanced Mathematics for Real Life Applications. Heidelberg: Springer International Publishing, 2013.

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Razin, Assaf. Do debt flows crowd out equity flows or the other way round? Cambridge, MA: National Bureau of Economic Research, 2000.

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Mercereau, Benoît. FDI flows to Asia: Did the dragon crowd out the tigers? Washington, D.C: International Monetary Fund, Asia Pacific Dept., 2005.

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Rosini, Massimiliano Daniele. Macroscopic Models for Vehicular Flows and Crowd Dynamics: Theory and Applications. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00155-5.

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Association, Reader's Digest. Reader's Digest Condensed Books: Containing The eagle has flown, Shadow into sunlight, As the crow flies, The winter of the fisher. London: Reader's Digest Association, 1991.

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Rosini, Massimiliano Daniele. Macroscopic Models for Vehicular Flows and Crowd Dynamics : Theory and Applications: Classical and Non–Classical Advanced Mathematics for Real Life Applications. Springer, 2013.

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Rosini, Massimiliano Daniele. Macroscopic Models for Vehicular Flows and Crowd Dynamics : Theory and Applications: Classical and Non-Classical Advanced Mathematics for Real Life Applications. Springer International Publishing AG, 2015.

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As This Crow Flew. Authorhouse, 2001.

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Spinks, Thomas L. Development of new continuous flow techniques and investigations of crown ether coordination chemistry. 1992.

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Akyüz, Yilmaz. Foreign Direct Investment. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198797173.003.0006.

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Recent years have also seen increased openness of EDEs to foreign direct investment (FDI) in search for faster growth and greater stability. However, FDI is one of the most ambiguous and least understood concepts in international economics. Common debate is confounded by several myths regarding its nature and impact. It is often portrayed as a stable, cross-border flow of capital that adds to productive capacity and meets foreign exchange shortfalls. However, the reality is far more complex. FDI does not always involve inflows of financial or real capital. Greenfield investment, unlike mergers and acquisitions, makes a direct contribution to productive capacity, but can crowd out domestic investors. FDI can induce significant instability in currency and financial markets. Its immediate contribution to balance-of-payments may be positive, but its longer-term impact is often negative because of high-profit remittances and import contents.
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Book chapters on the topic "Crowd Flow"

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Pellegrini, Stefano, Jürgen Gall, Leonid Sigal, and Luc Van Gool. "Destination Flow for Crowd Simulation." In Computer Vision – ECCV 2012. Workshops and Demonstrations, 162–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33885-4_17.

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Bamberger, Johanna, Anna-Lena Geßler, Peter Heitzelmann, Sara Korn, Rene Kahlmeyer, Xue Hao Lu, Qi Hao Sang, et al. "Crowd Research at School: Crossing Flows." In Traffic and Granular Flow '13, 137–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_16.

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Maury, Bertrand, and Juliette Venel. "Handling of Contacts in Crowd Motion Simulations." In Traffic and Granular Flow ’07, 171–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-77074-9_15.

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Borsche, Raul, Axel Klar, and Florian Schneider. "Numerical Methods for Mean-Field and Moment Models for Pedestrian Flow." In Crowd Dynamics, Volume 1, 167–209. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05129-7_7.

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Gorrini, Andrea, Stefania Bandini, and Giuseppe Vizzari. "Empirical Investigation on Pedestrian Crowd Dynamics and Grouping." In Traffic and Granular Flow '13, 83–91. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_10.

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Ma, Jian, Weiguo Song, and Siuming Lo. "Simulation of Crowd-Quakes with Heterogeneous Contact Model." In Traffic and Granular Flow '13, 103–10. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_12.

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Ali, Saad, and Mubarak Shah. "Crowd Flow Segmentation Using Lagrangian Particle Dynamics." In Modeling, Simulation and Visual Analysis of Crowds, 213–36. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8483-7_9.

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Sumon, Shakil Ahmed, MD Tanzil Shahria, MD Raihan Goni, Nazmul Hasan, A. M. Almarufuzzaman, and Rashedur M. Rahman. "Violent Crowd Flow Detection Using Deep Learning." In Intelligent Information and Database Systems, 613–25. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14799-0_53.

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He, Xiaoxi, Leiting Chen, and Qingxin Zhu. "A Novel Method for Large Crowd Flow." In Transactions on Edutainment VI, 67–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22639-7_8.

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Allain, Pierre, Nicolas Courty, and Thomas Corpetti. "Crowd Flow Characterization with Optimal Control Theory." In Computer Vision – ACCV 2009, 279–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12304-7_27.

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Conference papers on the topic "Crowd Flow"

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Liu, Lingbo, Ruimao Zhang, Jiefeng Peng, Guanbin Li, Bowen Du, and Liang Lin. "Attentive Crowd Flow Machines." In MM '18: ACM Multimedia Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3240508.3240681.

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Goh, Gary, Jing Yu Koh, and Yue Zhang. "Twitter-Informed Crowd Flow Prediction." In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018. http://dx.doi.org/10.1109/icdmw.2018.00097.

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Stanciu, Valeriu-Daniel, Maarten van Steen, Ciprian Dobre, and Andreas Peter. "k-Anonymous Crowd Flow Analytics." In MobiQuitous '20: Computing, Networking and Services. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3448891.3448903.

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Bajhmoum, Aseel, Muath Alghamdi, Saud Alboqami, Mohammad Alasmari, Tarik Alafif, and Abdulaziz Alshaer. "Crowd Flow Collisions Simulation (Student Consortium)." In 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). IEEE, 2020. http://dx.doi.org/10.1109/bigmm50055.2020.00055.

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Xing, Junliang, Haizhou Ai, Liwei Liu, and Shihong Lao. "Robust crowd counting using detection flow." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6115886.

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He, Jun, Jingyuan Wang, and Yizhi Luo. "Deep Architectures for Crowd Flow Prediction." In DSIT 2019: 2019 2nd International Conference on Data Science and Information Technology. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3352411.3352448.

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Al-Sulami, Saif, Raad Raad, and Mohamad Raad. "Crowd flow analysis using catastrophe theory." In 2015 Fifth International Conference on Digital Information and Communication Technology and its Applications (DICTAP). IEEE, 2015. http://dx.doi.org/10.1109/dictap.2015.7113195.

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Ribera, Javier, Khalid Tahboub, and Edward J. Delp. "Automated crowd flow estimation enhanced by crowdsourcing." In NAECON 2014 - IEEE National Aerospace and Electronics Conference. IEEE, 2014. http://dx.doi.org/10.1109/naecon.2014.7045798.

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Wang, Chengxin, Yuxuan Liang, and Gary Tan. "Periodic residual learning for crowd flow forecasting." In SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3557915.3560947.

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Srivastava, Satyam, Ka Ki Ng, and Edward J. Delp. "Crowd flow estimation using multiple visual features for scenes with changing crowd densities." In 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE, 2011. http://dx.doi.org/10.1109/avss.2011.6027295.

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Reports on the topic "Crowd Flow"

1

Razin, Assaf, Efraim Sadka, and Chi-Wa Yuen. Do Debt Flows Crowd Out Equity Flows Or the Other Way Round? Cambridge, MA: National Bureau of Economic Research, June 2000. http://dx.doi.org/10.3386/w7736.

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Orloff, D. I., B. Hojjatie, and F. Bloom. High-intensity drying processes: Impulse drying modeling of fluid flow and heat transfer in a crown compensated impulse drying press roll, The lubrication problem. Annual report. Office of Scientific and Technical Information (OSTI), August 1994. http://dx.doi.org/10.2172/278193.

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Orloff, D., B. Hojjatie, and F. Bloom. High-intensity drying process: Impulse drying. Progress report on modeling of fluid flow and heat transfer in a crown compensated impulse drying roll: The heat transfer problem. Office of Scientific and Technical Information (OSTI), July 1995. http://dx.doi.org/10.2172/183137.

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