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Статті в журналах з теми "Crowd Analysi"
1
Andriyanto, Sidhiq, M. Suyanto, and Sukoco Sukoco. "Implementasi Metode Reynolds menggunakan Simulasi Kerumunan Bebek." INTENSIF 1, no. 2 (August 21, 2017): 75. http://dx.doi.org/10.29407/intensif.v1i2.788.
Повний текст джерелаАнотація:
"Simulation of Duck Crows Using Reynolds Method" is a study with the aim to find out the behavior of duck breeding crowd. The next goal is to make a crowd simulation using the Reynolds method. Limitations of this research variable is the object of research on adult duck Turi, the method used is Reynolds method. The simulations are made using Unity3D software in the form of 3D and the animation provided is just a running gesture. The method of analysis of this research is using research and development method. The result of the research is the data of duck walking in the crowd to be applied in 3D animation. The end result of the study is a simulation of duck crowds that run on flat fields. Destination directions are affected by mouse input and can avoid obstacles when walking. This simulation uses Reynolds basic rules of cohesion, alignment and separation.The conclusion of the research is that there is a similarity between the simulation of the crowd with the movement of the original duck crowd and the Reynolds method can be applied in the simulation of the duck crowd in 3D. Research produces 3D animation of duck crowds that are given the ability to avoid obstacles and target goals determined by mouse input.
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Bhuiyan, Roman, Junaidi Abdullah, Noramiza Hashim, Fahmid Al Farid, Wan Noorshahida Mohd Isa, Jia Uddin, and Norra Abdullah. "Deep Dilated Convolutional Neural Network for Crowd Density Image Classification with Dataset Augmentation for Hajj Pilgrimage." Sensors 22, no. 14 (July 7, 2022): 5102. http://dx.doi.org/10.3390/s22145102.
Повний текст джерелаАнотація:
Almost two million Muslim pilgrims from all around the globe visit Mecca each year to conduct Hajj. Each year, the number of pilgrims grows, creating worries about how to handle such large crowds and avoid unpleasant accidents or crowd congestion catastrophes. In this paper, we introduced deep Hajj crowd dilated convolutional neural network (DHCDCNNet) for crowd density analysis. This research also presents augmentation technique to create additional dataset based on the hajj pilgrimage scenario. We utilized a single framework to extract both high-level and low-level features. For creating additional dataset we divide the process of images augmentation into two routes. In the first route, we utilized magnitude extraction followed by the polar magnitude. In the second route, we performed morphological operation followed by transforming the image into skeleton. This paper presented a solution to the challenge of measuring crowd density using a surveillance camera pointed at a distance. An FCNN-based technique for crowd analysis is included in the proposed methodology, particularly for classifying crowd density. There are several obstacles in video analysis when there are a large number of pilgrims moving around the tawaf area, with densities of between 7 and 8 per square meter. The proposed DHCDCNNet method has achieved accuracy of 97%, 89% and 100% for the JHU-CROWD dataset, the UCSD dataset and the proposed Hajj-Crowd dataset, respectively. The proposed Hajj-Crowd dataset, the UCSD dataset, and the JHU-CROW dataset all had accuracy of 98%, 97% and 97%, respectively, using the VGGNet approach. Using the ResNet50 approach, the proposed Hajj-Crowd dataset, the UCSD dataset, and the JHU-CROW dataset all had an accuracy of 99%, 91% and 97%, respectively.
3
Aiello, Lucia. "Digital Skill Evolution in an Industrial Relationship." International Journal of R&D Innovation Strategy 1, no. 1 (January 2019): 1–15. http://dx.doi.org/10.4018/ijrdis.2019010101.
Повний текст джерелаАнотація:
Crowdsourcing is a powerful mechanism for doing online work and allows for collaboration. By now, in the media and in business on the Internet, crowdsourcing is recognized as an innovative form of value creation that needs taken seriously. This article provides a framework to propose the relation between crowds and tutorship; it considers the tutor of a crowd as a strategic professional figure in an online community. This is done by the consideration of the different roles, activities and tasks of a tutor through the field analysis of a platform of one company that uses crowdsourcing. This tutor is examined based on the middle-of-the-road theoretical positioned from Porter and Kramer, the value creation, and Suermann and Franzoni, the crows science user contribution patterns. The recently evolution of crowd platforms considers the interaction between companies and crowds based on a “Community of Practice” model of Zucchermaglio and Talamo. Value analysis also considers the differences in roles and tasks in relation to where crowd activity is placed into the value chain of company. In crowdsourcing, “digital people” live in a digital society where every individual has a role and operates in an online community, and those have force points and weakness points. The tutor cans also monitor these points, and push interaction and activities of the crowd. The main theoretical contribution is the looking gap in literature and contributing work to this. Through a qualitative analysis, this article provides evidence of the main activities and the role of digital tutors in an online community. The method utilized is netnography through an online participation and observation of a researcher. In this work, professional figures and new technologies are weighed, and human resource management must consider this as it creates value. This article concludes that a tutor of crowds has a positive behavior, they can stimulate crowds. These positive and active behaviors effect crowd attitudes about the benefits of the community, their expectations, and opinions all of which are fundamental for the growth of online community.
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Husman, Muhammad Afif, Waleed Albattah, Zulkifli Zainal Abidin, Yasir Mohd Mustafah, Kushsairy Kadir, Shabana Habib, Muhammad Islam, and Sheroz Khan. "Unmanned Aerial Vehicles for Crowd Monitoring and Analysis." Electronics 10, no. 23 (November 29, 2021): 2974. http://dx.doi.org/10.3390/electronics10232974.
Повний текст джерелаАнотація:
Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented.
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R, Shaamili. "A Research Perceptive on Deep Learning Framework for Pedestrian Detection in a Crowd." Computational Intelligence and Machine Learning 3, no. 2 (October 14, 2022): 9–14. http://dx.doi.org/10.36647/ciml/03.02.a002.
Повний текст джерелаАнотація:
In populated cities, we often find crowded events like political meetings, religious festivals, music concerts, and events in shopping malls, which have more safety issues. Smart surveillance systems are used in big cities to keep crowds safe and make crowd security less complicated and more accurate. However, the surveillance systems proposed for a crowd are monitored by human agents, which are inefficient, error-prone, and overwhelming. Even with deep learning-based feature engineering in crowds, many variants of crowd analysis still lack attention and are technically unaddressed. Considering this scenario, the smart system requires the most advanced techniques to monitor the security of the crowd. Crowd analysis is commonly divided into crowd statics and behavior analysis. This paper explores more about crowd behaviour analysis, pedestrian and group detection which describes the movements that are noticed in the crowd image. Subsequently, the issues of the current methodology of pedestrian detection, datasets, and evaluation criteria are analyzed. Keyword : Crowd Analysis, Pedestrian and group detection, deep learning, Crowd IoT analysis, Human Activity Recognition.
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Elbishlawi, Sherif, Mohamed H. Abdelpakey, Agwad Eltantawy, Mohamed S. Shehata, and Mostafa M. Mohamed. "Deep Learning-Based Crowd Scene Analysis Survey." Journal of Imaging 6, no. 9 (September 11, 2020): 95. http://dx.doi.org/10.3390/jimaging6090095.
Повний текст джерелаАнотація:
Recently, our world witnessed major events that attracted a lot of attention towards the importance of automatic crowd scene analysis. For example, the COVID-19 breakout and public events require an automatic system to manage, count, secure, and track a crowd that shares the same area. However, analyzing crowd scenes is very challenging due to heavy occlusion, complex behaviors, and posture changes. This paper surveys deep learning-based methods for analyzing crowded scenes. The reviewed methods are categorized as (1) crowd counting and (2) crowd actions recognition. Moreover, crowd scene datasets are surveyed. In additional to the above surveys, this paper proposes an evaluation metric for crowd scene analysis methods. This metric estimates the difference between calculated crowed count and actual count in crowd scene videos.
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Borch, Christian. "Body to Body: On the Political Anatomy of Crowds." Sociological Theory 27, no. 3 (September 2009): 271–90. http://dx.doi.org/10.1111/j.1467-9558.2009.01348.x.
Повний текст джерелаАнотація:
This article challenges the negative image that, since the late 19th century, has been associated with crowds, and it does so by focusing on a number of bodily-anatomic aspects of crowd behavior. I first demonstrate that the work of one of the leading crowd psychologists, Gustave Le Bon, instigated a racist body politics. As a contrast to Le Bon's political program, I examine Walt Whitman's poetry and argue that the crowd may embody a democratic vision that emphasizes the social and political import of sexuality and body-to-body contact. Further, I dispute classical crowd theory's idea of an antagonistic relationship between crowds and individuality. Following Elias Canetti, I claim instead that the bodily compression of crowds in fact liberates individuals and creates a democratic transformation. The analysis results in a rehabilitation of crowds and briefly suggests how a reinterpretation of crowd behavior may inform current debates in social theory.
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Malhotra, Arvind, and Ann Majchrzak. "Greater associative knowledge variety in crowdsourcing platforms leads to generation of novel solutions by crowds." Journal of Knowledge Management 23, no. 8 (October 14, 2019): 1628–51. http://dx.doi.org/10.1108/jkm-02-2019-0094.
Повний текст джерелаАнотація:
Purpose The purpose of this study is to offer implications and future research directions related to new organizational forms like crowds. Organizations are increasingly relying on online crowds to innovate through mechanisms such as crowdsourcing, open innovation, innovation challenges and tournaments. To leverage the "wisdom of crowds", crowdsourcing platforms that enable heterogeneous knowledge sharing in crowds lead to novel solution generation by individuals in the crowd. Based on the associative variety memory model of creativity, the authors hypothesize that when a crowd contributes a heterogeneous knowledge in form of a variety of knowledge associations, individual crowd members tend to generate solutions that are more novel. In contrast to the brainstorming view that focuses on ideas as knowledge, the authors propose, test, find and elaborate on implications of crowd sharing of heterogeneous knowledge for the generation of innovation, i.e. novel ideas. The authors coded and analyzed all the posts in 20 innovation challenges leveraging online temporary crowds that were structured to foster knowledge sharing as part of the idea generation process. The analysis shows a positive relationship between the variety of knowledge associations contributed by the crowd and the generation of novel solutions by individuals in the crowd. Further, the variety of knowledge associations contributed by the crowd has a stronger relationship with novel solution generation than the number of associations generated by the crowd, i.e. variety of knowledge has a greater impact than either the quantity of knowledge or the number of solution-ideas shared. The authors offer four implications and several future directions for research on the new organizational form of online crowds. Design/methodology/approach The authors coded and analyzed all the posts in 20 innovation challenges. They also designed and ran these challenges in collaboration with corporate sponsors. The ideas in the challenge were rated by senior executive at each company using a creative forecasting method. Findings The variety of knowledge associations contributed by the crowd has a stronger relationship with novel solution generation than the number of associations generated by the crowd, i.e. variety of knowledge has a greater impact than either the quantity of knowledge or the number of solution-ideas shared. Research limitations/implications The authors offer four implications and several future directions for research on the new organizational form of online crowds. Practical implications The authors propose several ways in which companies running innovation challenges can moderate and encourage crowd to generate a variety of knowledge. Originality/value The authors believe that we are the first empirical paper to emphasize and show that associative variety of knowledge sharing in crowds has impact on novel idea generation by crowds. This view is counter to "electronic brainstorming" view where crowd is asked to just generate these ideas and often just submit their ideas to the sponsor. Their view also goes beyond knowledge refinement of ideas by crowds to more of knowledge integration by crowds.
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Obbo, Aggrey, Pius Ariho, and Evarist Nabaasa. "Towards People Crowd Detection Using Wireless Sensor Networks." European Journal of Technology 6, no. 2 (June 17, 2022): 32–48. http://dx.doi.org/10.47672/ejt.1071.
Повний текст джерелаАнотація:
Objective: The objective of this study was to examine and propose the use of wireless sensor networks for people crowd detection in resource constrained environments such as developing economies.
Methodology: A systematic review was carried out on current technological trends and application of Wireless Sensor Networks (WSNs) in crowd detection. For this study, focus was on WSN implementation in developing economies, where infrastructure is underdeveloped and people crowds are dynamic and spontaneous. Based on a requirement analysis and knowledge of the inherent challenges of WSNs, a WSN implementation for people crowd detection was proposed.
Findings: Most studies in crowd detection using WSNs, have been in the area of non-people crowds. However issues critical to deployment of WSNs for people crowd detection in developing countries include: the uncontrollable nature of people crowds, under developed physical infrastructure and the inherent challenges of power, computational capacity and broadcast communication characterizing WSNs. Achieving people crowd detection using WSNs therefore, calls for special attention.
Recommendation: To ensure effective people crowd detection, requires taking into consideration connectivity, scalability, performance, security, accuracy and resource utilization of WSNs.
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Yugendar, Poojari, and K. V. R. Ravishankar. "Crowd Behavioural Analysis at a Mass Gathering Event." Journal of KONBiN 46, no. 1 (June 1, 2018): 5–20. http://dx.doi.org/10.2478/jok-2018-0020.
Повний текст джерелаАнотація:
Abstract Religious occasions, gathering at fairs and terminals, are the events of crowd gatherings. Such gatherings act as severe threats for crowds because of high density in less space, which ends up in adverse outcomes resulting in crowd stampedes. The movement of an individual person in a crowd is influenced by the physical factors. In the present study, characteristics like age, gender, group size, child holding, child carrying, people with luggage and without luggage are considered for crowd behaviour analysis. The average speed of the crowd movement was observed as 0.86 m/s. The statistical analysis concluded that there was a significant effect of age, gender, density and luggage on the crowd walking speed. Multi-linear regression (MLR) model was developed between crowd speed and significant factors observed from the statistical analysis. Location 1 data was used for the model development. This developed model was validated using Location 2 data. Gender has more significant effect on speed followed by luggage and age. This study helps in proper dispersal of crowd in a planned manner to that of diversified directional flow that exist during crowd gathering events.
Дисертації з теми "Crowd Analysi"
1
Bisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Повний текст джерелаАнотація:
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.
2
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.
Повний текст джерелаАнотація:
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
3
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.
Повний текст джерелаАнотація:
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.
Повний текст джерелаАнотація:
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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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.
Повний текст джерелаАнотація:
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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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/.
Повний текст джерелаАнотація:
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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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.
Повний текст джерелаАнотація:
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 groupspeople 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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Bisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.
Повний текст джерелаАнотація:
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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Ullah, Habib. "Crowd Motion Analysis: Segmentation, Anomaly Detection, and Behavior Classification." Doctoral thesis, Università degli studi di Trento, 2015. https://hdl.handle.net/11572/369001.
Повний текст джерелаАнотація:
The objective of this doctoral study is to develop efficient techniques for flow segmentation, anomaly detection, and behavior classification in crowd scenes. Considering the complexities of occlusion, we focused our study on gathering the motion information at a higher scale, thus not associating it to single objects, but considering the crowd as a single entity. Firstly,we propose methods for flow segmentation based on correlation features, graph cut, Conditional Random Fields (CRF), enthalpy model, and particle mutual influence model. Secondly, methods based on deviant orientation information, Gaussian Mixture Model (GMM), and MLP neural network combined with GoodFeaturesToTrack are proposed to detect two types of anomalies. The first one detects deviant motion of the pedestrians compared to what has been observed beforehand. The second one detects panic situation by adopting the GMM and MLP to learn the behavior of the motion features extracted from a grid of particles and GoodFeaturesToTrack, respectively. Finally, we propose particle-driven and hybrid appraoches to classify the behaviors of crowd in terms of lane, arch/ring, bottleneck, blocking and fountainhead within a region of interest (ROI). For this purpose, the particle-driven approach extracts and fuses spatio-temporal features together. The spatial features represent the density of neighboring particles in the predefined proximity, whereas the temporal features represent the rendering of trajectories traveled by the particles. The hybrid approach exploits a thermal diffusion process combined with an extended variant of the social force model (SFM).
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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.
Повний текст джерелаАнотація:
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 piétonsThis 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
Книги з теми "Crowd Analysi"
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Ali, Saad, Ko Nishino, Dinesh Manocha, and Mubarak Shah, eds. Modeling, Simulation and Visual Analysis of Crowds. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8483-7.
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N, Pathak P., and Bhabha Atomic Research Centre, eds. Extraction chromatographic studies on a strontium selective crown ether. Mumbai: Bhabha Atomic Research Centre, 1998.
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Associates, Golder, and Canada Centre for Mineral and Energy Technology., eds. Crown pillar stability back-analysis: Report to CANMET. Mississauga, Ont: Golder Associates Ltd., 1990.
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Sunkin, Maurice. The nature of the crown: A legal and political analysis. Oxford: Oxford University Press, 1999.
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Tonasket Ranger District (Wash.), Washington (State). Dept. of Ecology., and TerraMatrix Inc, eds. Crown Jewel Mine, draft environmental impact statement. Steamboat Springs, CO: TerraMatrix, 1995.
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Plummer, Tony. The psychology of technical analysis: Profiting from crowd behavior and the dynamics of price. Chicago: Probus Pub. Co., 1993.
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Crow-Omaha: New light on a classic problem of kinship analysis. Tucson: University of Arizona Press, 2012.
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Ontario. Ministry of Natural Resources. An environmental assessment of timber management on crown lands in the Megisan Lake area. Toronto: The Committee, 1996.
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Sentiment in the Forex market: Indicators and strategies to profit from crowd behavior and market extremes. Hoboken, N.J: John Wiley & Sons, 2008.
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Cerrah, Ibrahim. Crowds and public order policing: An analysis of crowds and interpretations of their behaviour based on observational studies in Turkey, England, and Wales. Aldershot: Ashgate/Dartmouth, 1998.
Знайти повний текст джерелаЧастини книг з теми "Crowd Analysi"
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Still, G. Keith. "RAMP analysis." In Applied Crowd Science, 103–17. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-5.
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Still, G. Keith. "Event egress analysis." In Applied Crowd Science, 159–67. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-10.
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Still, G. Keith. "Crowd risk analysis." In Applied Crowd Science, 149–58. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-9.
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Still, G. Keith. "Strategic and tactical analysis." In Applied Crowd Science, 169–81. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781351053068-11.
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Amsterdamer, Yael, and Tova Milo. "Crowd Mining and Analysis." In Encyclopedia of Database Systems, 1–4. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80657-2.
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Amsterdamer, Yael, and Tova Milo. "Crowd Mining and Analysis." In Encyclopedia of Database Systems, 698–701. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80657.
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Ryan, David, Simon Denman, Sridha Sridharan, and Clinton Fookes. "Scene Invariant Crowd Counting and Crowd Occupancy Analysis." In Studies in Computational Intelligence, 161–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28598-1_6.
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Feliciani, Claudio, Kenichiro Shimura, and Katsuhiro Nishinari. "Analysis of Past Crowd Accidents." In Introduction to Crowd Management, 51–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90012-0_3.
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Wąs, Jarosław, and Krzysztof Kułakowski. "Social Groups in Crowd." In Encyclopedia of Social Network Analysis and Mining, 1–7. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_255-1.
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Wąs, Jarosław, and Krzysztof Kułakowski. "Social Groups in Crowd." In Encyclopedia of Social Network Analysis and Mining, 1784–90. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_255.
Повний текст джерелаТези доповідей конференцій з теми "Crowd Analysi"
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De Luca, Antonio, Scott Lomax, and Marguerite Jeansonne Pinto. "Advanced analysis of a pedestrian bridge and considerations on crowd-structure interaction." In IABSE Symposium, Prague 2022: Challenges for Existing and Oncoming Structures. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2022. http://dx.doi.org/10.2749/prague.2022.1427.
Повний текст джерелаАнотація:
<p>Pedestrian bridges, grandstands, and other long-span structures may be subjected to crowd loading. Crowds have the dual effect to produce large forces and alter the structure’s modal properties and damping. Vibration testing of full-scale structures allows the verification of the modelling assumptions and design criteria.</p><p>This paper discusses the case study of a pedestrian bridge structure subjected to crowd loading. The results of the design finite element model of the bridge and the bridge performance were validated through field testing. The theoretical effects of crowds were analysed and compared to the experimental test data.</p>
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Deshpande, N. P., and R. Gupta. "Crowd management using fuzzy logic and G.I.S." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100281.
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Huang, Hun, Ge Gao, Ziyi Ke, Cheng Peng, and Ming Gu. "A Multi-Scenario Crowd Data Synthesis Based On Building Information Modeling." In The 29th EG-ICE International Workshop on Intelligent Computing in Engineering. EG-ICE, 2022. http://dx.doi.org/10.7146/aul.455.c223.
Повний текст джерелаАнотація:
Deep learning methods have proven to be effective in the field of crowd analysis recently. Nonetheless, the performance of deep learning models is affected by the inadequacy of training datasets. Because of policy implications and privacy restrictions, crowd data is commonly difficult to access. In order to overcome the difficulty of insufficient dataset, the previous work used to synthesize labelled crowd data in outdoor scenes and virtual games. However, these methods perform data synthesis with limited environmental information and inflexible crowd rules, usually in unauthentic environment. In this paper, a tool for synthesizing crowd data in BIM models with multiple scenes is proposed. This tool can make full use of the comprehensive information of real-world buildings, and conduct crowd simulations by setting behavior rules. The synthesized dataset is used for data augmentation for crowd analysis problems and the experimental results clearly confirm the effectiveness of the tool.
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Mahata, Debanjan, and Nitin Agarwal. "Learning from the crowd." In ASONAM '13: Advances in Social Networks Analysis and Mining 2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2492517.2492661.
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Zubrilina, E. M., V. I. Novikov, H. S. Jamalov, and V. S. Kompaniets. "ANALYSIS OF CROWDSOURCING INTERNET PLATFORMS AND THEIR IMPLEMENTATION IN THE EDUCATIONAL ENVIRONMENT." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS Volume 2. DSTU-Print, 2020. http://dx.doi.org/10.23947/interagro.2020.2.588-590.
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the article describes the essence of implementing the project approach using crowd sourcing as an innovative component in higher education institutions. Innovative approaches to teaching disciplines are described, and the idea of creating a crowd platform for higher education institutions (DSTU) is revealed.
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Stuart, Daniel, Keith Christensen, Anthony Chen, Yong Kim, and YangQuan Chen. "Utilizing Augmented Reality Technology for Crowd Pedestrian Analysis Involving Individuals With Disabilities." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12765.
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This research explores how different compositions of Individuals with Disabilities (IwDs) affect the dynamics of crowd movement. In particular, we consider IwDs such as individuals on manual and electric wheelchair, with vision loss and other mobility impairments to better understand the impacts that the compositions of individuals with various types of disabilities will bring on the mobility of the crowd at various structural elements of a built environment such as hall way, door way, and stairwells. While currently available video tracking technologies provide options for primitive macroscopic and microscopic analysis of a crowd, they lack the ability to analyze detailed navigational information of each focused group such as IwDs with varying types of disabilities. This paper provides an approach that exploits ARToolKitPlus libraries and Power-over-Ethernet high speed cameras along with augmented reality elements to track navigational patterns at individual level in a crowd. Preliminary results demonstrate the feasibility of the proposed system to track individual tracking of navigational patterns.
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Cao, Tian, Xinyu Wu, Jinnian Guo, Shiqi Yu, and Yangsheng Xu. "Abnormal crowd motion analysis." In 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.5420408.
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Duyar, Mustafa. "Mass Conserving Elastohydrodynamic Piston Lubrication Model With Incorporated Crown Lands." In ASME 2007 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/icef2007-1710.
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This paper describes a comprehensive model of Elastohydrodynamic piston lubrication, incorporated the crown lands into solution domain to characterize the effect of crown-liner interactions on piston motion. Elastohydrodynamic Lubrication (EHL) analysis of a piston skirt-liner conjunction is in general a useful methodology for design analysis of pistons. The diameters of piston crown lands are much less than those of skirt and liner for typical piston designs. Therefore crown lands normally do not interact with liner under usual operating conditions and hence most of the researchers exclude crown lands from the EHL analysis and mainly focus on piston skirt. However, under some of the engine operating conditions piston crown lands play important role in the secondary dynamics and tribology aspects of pistons. During the thermodynamic cycle when piston is hot and cylinder liner is relatively colder, piston thermal expansion leads to crown-liner interaction, which necessitates EHL, asperity contact and wear considerations of piston crown along with piston skirt. The simulation methodology for piston EHL analysis uses a mass-conserving algorithm for the finite volume method solution of Reynolds equation, which is coupled to elasticity relations and Greenwood-Tripp asperity contact model. Elrod’s mass conserving algorithm enables to model and analyze partially lubricated piston-liner interface by the input of oil supply and moreover rigorously handles cavitated zones, and takes into account piston ring grooves, piston cut-outs and unlubricated areas due to piston geometry. Results are presented from parametric studies that show comparisons between the analyses of the models with piston skirt lubrication only and piston lubrication, which incorporates the crown lands to the EHL domain.
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Dupont, Camille, Luis Tobias, and Bertrand Luvison. "Crowd-11: A Dataset for Fine Grained Crowd Behaviour Analysis." In 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2017. http://dx.doi.org/10.1109/cvprw.2017.271.
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Phu, Quy Nguyen Pham, Vy Nguyen, Tien Do, and Thanh Duc Ngo. "Measuring Crowd Collectiveness with Trajectory Smoothing." In 2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR). IEEE, 2018. http://dx.doi.org/10.1109/mapr.2018.8337520.
Повний текст джерелаЗвіти організацій з теми "Crowd Analysi"
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Petty, Mikel D., Ryland C. Gaskins, and Frederic D. McKenzie. Crowd Modeling in Military Simulations: Requirements Analysis, Survey, and Design Study. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada474641.
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Schomaker, Michael E., Stanley J. Zarnoch, William A. Bechtold, David J. Latelle, William G. Burkman, and Susan M. Cox. Crown-condition classification: a guide to data collection and analysis. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2007. http://dx.doi.org/10.2737/srs-gtr-102.
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Drury, J., S. Arias, T. Au-Yeung, D. Barr, L. Bell, T. Butler, H. Carter, et al. Public behaviour in response to perceived hostile threats: an evidence base and guide for practitioners and policymakers. University of Sussex, 2023. http://dx.doi.org/10.20919/vjvt7448.
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Background: Public behaviour and the new hostile threats • Civil contingencies planning and preparedness for hostile threats requires accurate and up to date knowledge about how the public might behave in relation to such incidents. Inaccurate understandings of public behaviour can lead to dangerous and counterproductive practices and policies. • There is consistent evidence across both hostile threats and other kinds of emergencies and disasters that significant numbers of those affected give each other support, cooperate, and otherwise interact socially within the incident itself. • In emergency incidents, competition among those affected occurs in only limited situations, and loss of behavioural control is rare. • Spontaneous cooperation among the public in emergency incidents, based on either social capital or emergent social identity, is a crucial part of civil contingencies planning. • There has been relatively little research on public behaviour in response to the new hostile threats of the past ten years, however. • The programme of work summarized in this briefing document came about in response to a wave of false alarm flight incidents in the 2010s, linked to the new hostile threats (i.e., marauding terrorist attacks). • By using a combination of archive data for incidents in Great Britain 2010-2019, interviews, video data analysis, and controlled experiments using virtual reality technology, we were able to examine experiences, measure behaviour, and test hypotheses about underlying psychological mechanisms in both false alarms and public interventions against a hostile threat. Re-visiting the relationship between false alarms and crowd disasters • The Bethnal Green tube disaster of 1943, in which 173 people died, has historically been used to suggest that (mis)perceived hostile threats can lead to uncontrolled ‘stampedes’. • Re-analysis of witness statements suggests that public fears of Germany bombs were realistic rather than unreasonable, and that flight behaviour was socially structured rather than uncontrolled. • Evidence for a causal link between the flight of the crowd and the fatal crowd collapse is weak at best. • Altogether, the analysis suggests the importance of examining people’s beliefs about context to understand when they might interpret ambiguous signals as a hostile threat, and that. Tthe concepts of norms and relationships offer better ways to explain such incidents than ‘mass panic’. Why false alarms occur • The wider context of terrorist threat provides a framing for the public’s perception of signals as evidence of hostile threats. In particular, the magnitude of recent psychologically relevant terrorist attacks predicts likelihood of false alarm flight incidents. • False alarms in Great Britain are more likely to occur in those towns and cities that have seen genuine terrorist incidents. • False alarms in Great Britain are more likely to occur in the types of location where terrorist attacks happen, such as shopping areass, transport hubs, and other crowded places. • The urgent or flight behaviour of other people (including the emergency services) influences public perceptions that there is a hostile threat, particularly in situations of greater ambiguity, and particularly when these other people are ingroup. • High profile tweets suggesting a hostile threat, including from the police, have been associated with the size and scale of false alarm responses. • In most cases, it is a combination of factors – context, others’ behaviour, communications – that leads people to flee. A false alarm tends not to be sudden or impulsive, and often follows an initial phase of discounting threat – as with many genuine emergencies. 2.4 How the public behave in false alarm flight incidents • Even in those false alarm incidents where there is urgent flight, there are also other behaviours than running, including ignoring the ‘threat’, and walking away. • Injuries occur but recorded injuries are relatively uncommon. • Hiding is a common behaviour. In our evidence, this was facilitated by orders from police and offers from people staff in shops and other premises. • Supportive behaviours are common, including informational and emotional support. • Members of the public often cooperate with the emergency services and comply with their orders but also question instructions when the rationale is unclear. • Pushing, trampling and other competitive behaviour can occur,s but only in restricted situations and briefly. • At the Oxford Street Black Friday 2017 false alarm, rather than an overall sense of unity across the crowd, camaraderie existed only in pockets. This was likely due to the lack of a sense of common fate or reference point across the incident; the fragmented experience would have hindered the development of a shared social identity across the crowd. • Large and high profile false alarm incidents may be associated with significant levels of distress and even humiliation among those members of the public affected, both at the time and in the aftermath, as the rest of society reflects and comments on the incident. Public behaviour in response to visible marauding attackers • Spontaneous, coordinated public responses to marauding bladed attacks have been observed on a number of occasions. • Close examination of marauding bladed attacks suggests that members of the public engage in a wide variety of behaviours, not just flight. • Members of the public responding to marauding bladed attacks adopt a variety of complementary roles. These, that may include defending, communicating, first aid, recruiting others, marshalling, negotiating, risk assessment, and evidence gathering. Recommendations for practitioners and policymakers • Embed the psychology of public behaviour in emergencies in your training and guidance. • Continue to inform the public and promote public awareness where there is an increased threat. • Build long-term relations with the public to achieve trust and influence in emergency preparedness. • Use a unifying language and supportive forms of communication to enhance unity both within the crowd and between the crowd and the authorities. • Authorities and responders should take a reflexive approach to their responses to possible hostile threats, by reflecting upon how their actions might be perceived by the public and impact (positively and negatively) upon public behaviour. • To give emotional support, prioritize informative and actionable risk and crisis communication over emotional reassurances. • Provide first aid kits in transport infrastructures to enable some members of the public more effectively to act as zero responders.
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Anilkumar, Rahul, Benjamin Melone, Michael Patsula, Christopher Tran, Christopher Wang, Kevin Dick, Hoda Khalil, and G. A. Wainer. Canadian jobs amid a pandemic : examining the relationship between professional industry and salary to regional key performance indicators. Department of Systems and Computer Engineering, Carleton University, June 2022. http://dx.doi.org/10.22215/dsce/220608.
Повний текст джерелаАнотація:
The COVID-19 pandemic has contributed to massive rates of unemployment and greater uncertainty in the job market. There is a growing need for data-driven tools and analyses to better inform the public on trends within the job market. In particular, obtaining a “snapshot” of available employment opportunities mid-pandemic promises insights to inform policy and support retraining programs. In this work, we combine data scraped from the Canadian Job Bank and Numbeo globally crowd-sourced repository to explore the relationship between job postings during a global pandemic and Key Performance Indicators (e.g. quality of life index, cost of living) for major cities across Canada. This analysis aims to help Canadians make informed career decisions, collect a “snapshot” of the Canadian employment opportunities amid a pandemic, and inform job seekers in identifying the correct fit between the desired lifestyle of a city and their career. We collected a new high-quality dataset of job postings from jobbank.gc.ca obtained with the use of ethical web scraping and performed exploratory data analysis on this dataset to identify job opportunity trends. When optimizing for average salary of job openings with quality of life, affordability, cost of living, and traffic indices, it was found that Edmonton, AB consistently scores higher than the mean, and is therefore an attractive place to move. Furthermore, we identified optimal provinces to relocate to with respect to individual skill levels. It was determined that Ajax, Marathon, and Chapleau, ON are each attractive cities for IT professionals, construction workers, and healthcare workers respectively when maximizing average salary. Finally, we publicly release our scraped dataset as a mid-pandemic snapshot of Canadian employment opportunities and present a public web application that provides an interactive visual interface that summarizes our findings for the general public and the broader research community.
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Randolph, KaDonna C. Descriptive statistics of tree crown condition in the Southern United States and impacts on data analysis and interpretation. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2006. http://dx.doi.org/10.2737/srs-gtr-94.
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Randolph, KaDonna C. Descriptive statistics of tree crown condition in the Southern United States and impacts on data analysis and interpretation. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2006. http://dx.doi.org/10.2737/srs-gtr-94.
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Chen, Li, Yu Ji, QiPeng Wang, and Peng Chen. Effects of traditional Chinese exercise on the treatment of COVID-19: a protocol for a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, January 2022. http://dx.doi.org/10.37766/inplasy2022.1.0089.
Повний текст джерелаАнотація:
Review question / Objective: Since the end of December 2019, COVID-19 has caused a huge impact in many countries and has attracted great attention from countries around the world. In fact, many studies have shown that during the fight against the COVID-19 epidemic. Chinese traditional exercise play an active role in promoting human health. The main purpose of this study is to provide a reliable method and credible evidence to improve the prognosis of patients with COVID-19 through traditional Chinese exercise. Condition being studied: In recent years, a large number of studies have shown that traditional Chinese sports, as the traditional culture of the Chinese nation, have played a huge role in this new crown epidemic. Therefore, we will study the effect of traditional Chinese exercise on the prognosis and treatment effect of COVID-19 patients in a systematic review and analysis.
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Arce, Eliécer, and Edgar A. Robles. Fiscal Rules and the Behavior of Public Investment in Costa Rica and Panama: Towards Growth-Friendly Fiscal Policy? Inter-American Development Bank, March 2021. http://dx.doi.org/10.18235/0003071.
Повний текст джерелаАнотація:
This paper aims to provide evidence on the effects of fiscal rules on public investment, fiscal results and growth in Costa Rica and Panama. First, we find that the budget formulation process and the political economy behind the adoption and compliance of fiscal rules explain that Panama has a bias to create and sequentially pile up rules, while Costa Rica has a tendency not to comply with them. Second, a retrospective analysis of the 2018 fiscal rules in both nations finds asymmetric effects on the fiscal results. In Panama it is difficult to separate the effect of fiscal rule designs on public investment; and, in Costa Rica, the application of the fiscal rule will decrease public investment, if the debt to GDP ratio exceeds 60 percent and current expenditure crowds out capital expenditure. Two lessons emerge. First, an effective fiscal rule compliance requires time consistent institutions, solid monitoring, enforcement schemes and improving the quality of public financial management systems. Second, it is necessary to review the design of fiscal rules in both countries to ensure they are investment and growth friendly.
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Lu, Tianjun, Jian-yu Ke, Fynnwin Prager, and Jose N. Martinez. “TELE-commuting” During the COVID-19 Pandemic and Beyond: Unveiling State-wide Patterns and Trends of Telecommuting in Relation to Transportation, Employment, Land Use, and Emissions in Calif. Mineta Transportation Institute, August 2022. http://dx.doi.org/10.31979/mti.2022.2147.
Повний текст джерелаАнотація:
Telecommuting, the practice of working remotely at home, increased significantly (25% to 35%) early in the COVID-19 pandemic. This shift represented a major societal change that reshaped the family, work, and social lives of many Californians. These changes also raise important questions about what factors influenced telecommuting before, during, and after COVID-19, and to what extent changes in telecommuting have influenced transportation patterns across commute modes, employment, land use, and environment. The research team conducted state-level telecommuting surveys using a crowd-sourced platform (i.e., Amazon Mechanical Turk) to obtain valid samples across California (n=1,985) and conducted state-level interviews among stakeholders (n=28) across ten major industries in California. The study leveraged secondary datasets and developed regression and time-series models. Our surveys found that, compared to pre-pandemic levels, more people had a dedicated workspace at home and had received adequate training and support for telecommuting, became more flexible to choose their own schedules, and had improved their working performance—but felt isolated and found it difficult to separate home and work life. Our interviews suggested that telecommuting policies were not commonly designed and implemented until COVID-19. Additionally, regression analyses showed that telecommuting practices have been influenced by COVID-19 related policies, public risk perception, home prices, broadband rates, and government employment. This study reveals advantages and disadvantages of telecommuting and unveils the complex relationships among the COVID-19 outbreak, transportation systems, employment, land use, and emissions as well as public risk perception and economic factors. The study informs statewide and regional policies to adapt to the new patterns of telecommuting.
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Ron, Eliora, and Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, March 2009. http://dx.doi.org/10.32747/2009.7695860.bard.
Повний текст джерелаАнотація:
The aim of this study was to carry out a global functional genomics analysis of plant cell transformation by Agrobacterium in order to define and characterize the physiology of Agrobacterium in the acidic environment of a wounded plant. We planed to study the proteome and transcriptome of Agrobacterium in response to a change in pH, from 7.2 to 5.5 and identify genes and circuits directly involved in this change. Bacteria-plant interactions involve a large number of global regulatory systems, which are essential for protection against new stressful conditions. The interaction of bacteria with their hosts has been previously studied by genetic-physiological methods. We wanted to make use of the new capabilities to study these interactions on a global scale, using transcription analysis (transcriptomics, microarrays) and proteomics (2D gel electrophoresis and mass spectrometry). The results provided extensive data on the functional genomics under conditions that partially mimic plant infection and – in addition - revealed some surprising and significant data. Thus, we identified the genes whose expression is modulated when Agrobacterium is grown under the acidic conditions found in the rhizosphere (pH 5.5), an essential environmental factor in Agrobacterium – plant interactions essential for induction of the virulence program by plant signal molecules. Among the 45 genes whose expression was significantly elevated, of special interest is the two-component chromosomally encoded system, ChvG/I which is involved in regulating acid inducible genes. A second exciting system under acid and ChvG/Icontrol is a secretion system for proteins, T6SS, encoded by 14 genes which appears to be important for Rhizobium leguminosarum nodule formation and nitrogen fixation and for virulence of Agrobacterium. The proteome analysis revealed that gamma aminobutyric acid (GABA), a metabolite secreted by wounded plants, induces the synthesis of an Agrobacterium lactonase which degrades the quorum sensing signal, N-acyl homoserine lactone (AHL), resulting in attenuation of virulence. In addition, through a transcriptomic analysis of Agrobacterium growing at the pH of the rhizosphere (pH=5.5), we demonstrated that salicylic acid (SA) a well-studied plant signal molecule important in plant defense, attenuates Agrobacterium virulence in two distinct ways - by down regulating the synthesis of the virulence (vir) genes required for the processing and transfer of the T-DNA and by inducing the same lactonase, which in turn degrades the AHL. Thus, GABA and SA with different molecular structures, induce the expression of these same genes. The identification of genes whose expression is modulated by conditions that mimic plant infection, as well as the identification of regulatory molecules that help control the early stages of infection, advance our understanding of this complex bacterial-plant interaction and has immediate potential applications to modify it. We expect that the data generated by our research will be used to develop novel strategies for the control of crown gall disease. Moreover, these results will also provide the basis for future biotechnological approaches that will use genetic manipulations to improve bacterial-plant interactions, leading to more efficient DNA transfer to recalcitrant plants and robust symbiosis. These advances will, in turn, contribute to plant protection by introducing genes for resistance against other bacteria, pests and environmental stress.