Journal articles on the topic 'Crowd Analysi'
To see the other types of publications on this topic, follow the link: Crowd Analysi.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Crowd Analysi.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
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.
Full textAbstract:
"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.
2
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.
Full textAbstract:
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.
Full textAbstract:
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.
4
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.
Full textAbstract:
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.
5
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.
Full textAbstract:
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.
6
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.
Full textAbstract:
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.
7
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.
Full textAbstract:
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.
8
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.
Full textAbstract:
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.
9
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.
Full textAbstract:
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.
10
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.
Full textAbstract:
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.
11
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.
Full textAbstract:
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.
12
BHUIYAN, MD ROMAN, Dr Junaidi Abdullah, Dr Noramiza Hashim, Fahmid Al Farid, Dr Jia Uddin, Norra Abdullah, and Dr Mohd Ali Samsudin. "Crowd density estimation using deep learning for Hajj pilgrimage video analytics." F1000Research 10 (January 14, 2022): 1190. http://dx.doi.org/10.12688/f1000research.73156.2.
Full textAbstract:
Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This research proposes an algorithm based on a Convolutional Neural Networks model specifically for Hajj applications. Additionally, the work introduces a system for counting and then estimating the crowd density. Methods: The model adopts an architecture which detects each person in the crowd, spots head location with a bounding box and does the counting in our own novel dataset (HAJJ-Crowd). Results: Our algorithm outperforms the state-of-the-art method, and attains a remarkable Mean Absolute Error result of 200 (average of 82.0 improvement) and Mean Square Error of 240 (average of 135.54 improvement). Conclusions: In our new HAJJ-Crowd dataset for evaluation and testing, we have a density map and prediction results of some standard methods.
13
Denis, Stijn, Ben Bellekens, Abdil Kaya, Rafael Berkvens, and Maarten Weyn. "Large-Scale Crowd Analysis through the Use of Passive Radio Sensing Networks." Sensors 20, no. 9 (May 4, 2020): 2624. http://dx.doi.org/10.3390/s20092624.
Full textAbstract:
The creation of an automatic crowd estimation system capable of providing reliable, real-time estimates of human crowd sizes would be an invaluable tool for organizers of large-scale events, particularly so in the context of safety management. We describe a set of experiments in which we installed a passive Radio Frequency (RF) sensor network in different environments containing thousands of human individuals and discuss the accuracy with which the resulting measurements can be used to estimate the sizes of these crowds. Depending on the selected training approach, a median crowd estimation error of 184 people could be obtained for a large scale environment which contained 3227 people at its peak. Additionally, we look into the potential benefits of dividing one of our experimental environments into multiple subregions and open up a potentially interesting new topic of research regarding the estimation of crowd flows. Finally, we investigate the combination of our measurements with another sources of crowd-related data: sales data from drink stands within the environment. In doing so, we aim to integrate the concept of an automatic RF-based crowd estimation system into the broader domain of crowd analysis.
14
Shukla, Shivang, Bernard Tiddeman, and Helen C. Miles. "A Wide Area Multiview Static Crowd Estimation System Using UAV and 3D Training Simulator." Remote Sensing 13, no. 14 (July 15, 2021): 2780. http://dx.doi.org/10.3390/rs13142780.
Full textAbstract:
Crowd size estimation is a challenging problem, especially when the crowd is spread over a significant geographical area. It has applications in monitoring of rallies and demonstrations and in calculating the assistance requirements in humanitarian disasters. Therefore, accomplishing a crowd surveillance system for large crowds constitutes a significant issue. UAV-based techniques are an appealing choice for crowd estimation over a large region, but they present a variety of interesting challenges, such as integrating per-frame estimates through a video without counting individuals twice. Large quantities of annotated training data are required to design, train, and test such a system. In this paper, we have first reviewed several crowd estimation techniques, existing crowd simulators and data sets available for crowd analysis. Later, we have described a simulation system to provide such data, avoiding the need for tedious and error-prone manual annotation. Then, we have evaluated synthetic video from the simulator using various existing single-frame crowd estimation techniques. Our findings show that the simulated data can be used to train and test crowd estimation, thereby providing a suitable platform to develop such techniques. We also propose an automated UAV-based 3D crowd estimation system that can be used for approximately static or slow-moving crowds, such as public events, political rallies, and natural or man-made disasters. We evaluate the results by applying our new framework to a variety of scenarios with varying crowd sizes. The proposed system gives promising results using widely accepted metrics including MAE, RMSE, Precision, Recall, and F1 score to validate the results.
15
Korbut, Andrei M. "Social Order and Practical Wisdom of Walking in a Crowd." Sociological Journal 24, no. 4 (2018): 8–29. http://dx.doi.org/10.19181/socjour.2018.24.4.6095.
Full textAbstract:
The article suggests returning to the “crowd” as an object of sociological analysis. Crowds have attracted early sociologists because crowds were visual embodiments of social forces that surpass individuals and also served as a symbol of the profound social transformations which were taking place in the late 19th and early 20th centuries. Analyzing crowds allowed for the first sociologists (G. Simmel, R. Park, M. Weber, E. Durkheim) to oppose the psychological interpretation of mass social phenomena with a purely sociological approach. However, in the second half of the 20th century sociologists had lost almost all interest in the crowd, as it did not meet the interests of researchers of “large” social structures, nor the interests of the proponents of interactionist approaches. This article shows that the crowd can again be made interesting for sociology if we were to consider it from the point of view of the everyday practices of the participants. In these everyday practices a specific form of phronesis, i.e. practical wisdom, technical skill coupled with moral judgment about which action is good and which is not, is implemented. It is shown here that the study of the practical wisdom of walking in a crowd requires special concepts and methods that can be found in phenomenology and ethnomethodology. The article suggests using three such concepts for the analysis of crowds: phenomenal field, oriented object, and figuration of details. With the help of these concepts, the methods of the crowd’s situated social order production are analyzed in relation to the management of speed and trajectories of movement, following one another, walkers’ stopping and slowing down, and joining the crowd. This analysis shows that the joint production of the crowd’s social order by its participants is a situated practice, i.e. it consists of making the local scenes of everyday life familiar and accountable, and of assessing the local adequacy of the actions performed.
16
BHUIYAN, MD ROMAN, Dr Junaidi Abdullah, Dr Noramiza Hashim, Fahmid Al Farid, Dr Jia Uddin, Norra Abdullah, and Dr Mohd Ali Samsudin. "Crowd density estimation using deep learning for Hajj pilgrimage video analytics." F1000Research 10 (November 24, 2021): 1190. http://dx.doi.org/10.12688/f1000research.73156.1.
Full textAbstract:
Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This paper aims to propose an algorithm based on a Convolutional Neural Networks model specifically for Hajj applications. Additionally, the work introduces a system for counting and then estimating the crowd density. Methods: The model adopts an architecture which detects each person in the crowd, spots head location with a bounding box and does the counting in our own novel dataset (HAJJ-Crowd). Results: Our algorithm outperforms the state-of-the-art method, and attains a remarkable Mean Absolute Error result of 200 (average of 82.0 improvement) and Mean Square Error of 240 (average of 135.54 improvement). Conclusions: In our new HAJJ-Crowd dataset for evaluation and testing, we have a density map and prediction results of some standard methods.
17
Chen, Jun, Huan Tan, Katrien Van Nimmen, and Peter Van den Broeck. "Data-Driven Synchronization Analysis of a Bouncing Crowd." Shock and Vibration 2019 (June 11, 2019): 1–23. http://dx.doi.org/10.1155/2019/8528763.
Full textAbstract:
Vibration serviceability problems concerning lightweight, flexible long-span floors and cantilever structures such as grandstands generally arise from crowd-induced loading, in particular due to bouncing or jumping activities. Predicting the dynamic responses of these structures induced by bouncing and jumping crowds has therefore become a critical aspect of vibration serviceability design. Although accurate models describing the load induced by a single person are available, essential information on the level of synchronization within the crowd is missing. In answer to this lack of information, this paper experimentally investigates the inter- and intraperson variability as well as the global crowd behavior in bouncing crowds. A group size of 48 persons is considered in the experiment whereby the individual body motions are registered synchronously by means of a 3D motion capture system. Preliminary tests verified a new approach to characterize the bouncing motion via markers on the clavicle. Subsequently, the full-scale experimental study considered various crowd spacing parameters, auditory stimuli, and bouncing frequencies. Moreover, special test cases were performed whereby each participant was wearing an eyepatch to exclude visual effects. Through the analysis of 330 test cases, the interperson variability at the bouncing frequency is identified. In addition, the cross-correlation and coherence between participants are analyzed. The coherence coefficients between each pair of participants in the same row or column are calculated and can be described by a lognormal distribution function. The influence of the spatial configurations and visual and auditory stimuli is analyzed. For the considered spatial configurations, no relevant impact on the inter- and intraperson variability in the bouncing motion nor in the global crowd behavior is observed. Visual stimuli are found to enhance the coordination and synchronization. Without eyesight, the participants are feeling uncertain about their bouncing behavior. The results evaluating the auditory cues indicate that significantly higher levels of synchronization and a lower degree of the intraperson variability are attained when a metronome cue is used in comparison to songs where the tempo often varies.
18
Negied, Nermin Kamal Abdel-Wahab, Elsayed B. Hemayed, and Magda Fayek. "HSBS: A Human’s Heat Signature and Background Subtraction Hybrid Approach for Crowd Counting and Analysis." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 08 (July 17, 2016): 1655025. http://dx.doi.org/10.1142/s0218001416550259.
Full textAbstract:
This work presents a new approach for crowd counting and classification based upon human thermal and motion features. The technique is efficient for automatic crowd density estimation and type of motion determination. Crowd density is measured without any need for camera calibration or assumption of prior knowledge about the input videos. It does not need any human intervention so it can be used successfully in a fully automated crowd control systems. Two new features are introduced for crowd counting purpose: the first represents thermal characteristics of humans and is expressed by the ratio between their temperature and their ambient environment temperature. The second describes humans motion characteristics and is measured by the ratio between humans motion velocity and the ambient environment rigidity. Each ratio should exceed a certain predetermined threshold for human beings. These features have been investigated and proved to give accurate crowd counting performance in real time. Moreover, the two features are combined and used together for crowd classification into one of the three main types, which are: fully mobile, fully static, or mix of both types. Last but not least, the proposed system offers several advantages such as being a privacy preserving crowd counting system, reliable for homogeneous and inhomogeneous crowds, does not depend on a certain direction in motion detection, has no restriction on crowd size. The experimental results demonstrate the effectiveness of the approach.
19
Cecaj, Alket, Marco Lippi, Marco Mamei, and Franco Zambonelli. "Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches." IoT 2, no. 1 (January 8, 2021): 33–49. http://dx.doi.org/10.3390/iot2010003.
Full textAbstract:
The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. The objective of this survey is to overview: (i) the many potential application areas of crowd sensing and prediction; (ii) the technologies that can be exploited to sense crowd along with their potentials and limitations; (iii) the data analysis techniques that can be effectively used to forecast crowd distribution. Finally, the article tries to identify open and promising research challenges.
20
Cecaj, Alket, Marco Lippi, Marco Mamei, and Franco Zambonelli. "Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches." IoT 2, no. 1 (January 8, 2021): 33–49. http://dx.doi.org/10.3390/iot2010003.
Full textAbstract:
The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. The objective of this survey is to overview: (i) the many potential application areas of crowd sensing and prediction; (ii) the technologies that can be exploited to sense crowd along with their potentials and limitations; (iii) the data analysis techniques that can be effectively used to forecast crowd distribution. Finally, the article tries to identify open and promising research challenges.
21
Stalgaitis, Carolyn Ann, Mayo Djakaria, and Jeffrey Washington Jordan. "The Vaping Teenager: Understanding the Psychographics and Interests of Adolescent Vape Users to Inform Health Communication Campaigns." Tobacco Use Insights 13 (January 2020): 1179173X2094569. http://dx.doi.org/10.1177/1179173x20945695.
Full textAbstract:
Background: Adolescent vaping continues to rise, yet little is known about teen vape users beyond demographics. Effective intervention requires a deeper understanding of the psychographics and interests of adolescent vape users to facilitate targeted communication campaigns. Methods: We analyzed the 2017-2018 weighted cross-sectional online survey data from Virginia high school students (N = 1594) to identify and describe subgroups of adolescents who vaped. Participants reported 30-day vape use, identification with 5 peer crowds (Alternative, Country, Hip Hop, Mainstream, Popular), social prioritization, agreement with personal values statements, social media and smartphone use, and television and event preferences. We compared vaping rates and frequency by peer crowd using a chi-square analysis with follow-up testing to identify higher-risk crowds and confirmed associations using binary and multinomial logistic regression models with peer crowd scores predicting vaping, controlling for demographics. We then used chi-square and t tests to describe the psychographics, media use, and interests of higher-risk peer crowds and current vape users within those crowds. Results: Any current vaping was the highest among those with Hip Hop peer crowd identification (25.4%), then Popular (21.3%). Stronger peer crowd identification was associated with increased odds of any current vaping for both crowds, vaping on 1 to 19 days for both crowds, and vaping on 20 to 30 days for Hip Hop only. Compared with other peer crowds and non-users, Hip Hop and Popular youth and current vape users reported greater social prioritization and agreement with values related to being social and fashionable. Hip Hop and Popular youth and current vape users reported heavy Instagram and Snapchat use, as well as unique television show and event preferences. Conclusions: Hip Hop and Popular adolescents are most likely to vape and should be priority audiences for vaping prevention campaigns. Findings should guide the development of targeted health communication campaigns delivered via carefully designed media strategies.
22
Nishiyama, Hidefumi. "Crowd surveillance: The (in)securitization of the urban body." Security Dialogue 49, no. 3 (January 4, 2018): 200–216. http://dx.doi.org/10.1177/0967010617741436.
Full textAbstract:
The recent proliferation of the securitization of crowded places has led to a growth in the development of technologies of crowd behaviour analysis. However, despite the emerging prominence of crowd surveillance in emergency planning, its impacts on our understanding of security and surveillance have received little discussion. Using the case of crowd surveillance in Tokyo, this article examines the ways in which crowds are simulated, monitored and secured through the technology of crowd behaviour analysis, and discusses the implications on the politics of security. It argues that crowd surveillance constitutes a unique form of the biopolitics of security that targets not the individual body or the social body of population, but the urban body of crowd. The power of normalization in crowd surveillance operates in a preemptive manner through the codification of crowd behaviour that is spatially and temporarily specific. The article also interrogates the introduction of crowd surveillance in relation to racialized logics of suspicion and argues that, despite its appearance as non-discriminatory and ‘a-racial’, crowd surveillance entails the racial coding of crowd behaviour and urban space. The article concludes with the introduction of crowd surveillance as a border control technology, which reorients existing modalities of (in)securitization at airports.
23
Sonkar, Riddhi, Sadhana Rathod, Renuka Jadhav, and Deepali Patil. "CROWD ABNORMAL BEHAVIOUR DETECTION USING DEEP LEARNING." ITM Web of Conferences 32 (2020): 03040. http://dx.doi.org/10.1051/itmconf/20203203040.
Full textAbstract:
Crowd analysis has become an extremely famous research point in the territory of computer vision. Computerized examination of group exercises utilizing reconnaissance recordings is a significant issue for public security since it permits the identification of hazardous groups and where they’re going. We all see how many problems are faced because of the crowd. In our country, many terrorists are there. They plant a bomb in a crowded area which causes a lot of injuries. Thieves are mostly found or always leave in crowded areas so they can easily get an advantage of the crowd. In that situation, crowd analysis is very important. This paper presents the design of the deep learning architecture that provides control over the crowd behavior that will help to avoid violence or any other act which occurs because of the crowd which causes harmful effects to the society. So we are proposing a system that detects abnormal behavior of crowds using deep learning techniques.
24
Bielsa, Esperança. "From ‘the people’ to the crowd: The push for independence in Catalonia." Social Science Information 60, no. 3 (June 17, 2021): 395–412. http://dx.doi.org/10.1177/05390184211021354.
Full textAbstract:
This article examines the sociological value of Elias Canetti’s work on crowds and power. It explores crowd action and imagery in the push for Catalan independence through the analysis of materials published on Twitter by Tsunami Democràtic, which emerged to coordinate the response to the sentencing of Catalan political leaders after the unilateral declaration of independence. It then goes on to discuss how a crowd-based approach offers a supplementary perspective to contemporary studies of populism, on the one hand, and to accounts that primarily focus on the role of social media in organizing political protest movements, on the other. An analysis of crowds not only avoids both methodological holism and methodological individualism. It also helps to understand why so many people were mobilized beyond the power of concepts, ideologies and discourse.
25
Xue, Yiran, Peng Liu, Ye Tao, and Xianglong Tang. "Abnormal Prediction of Dense Crowd Videos by a Purpose–Driven Lattice Boltzmann Model." International Journal of Applied Mathematics and Computer Science 27, no. 1 (March 28, 2017): 181–94. http://dx.doi.org/10.1515/amcs-2017-0013.
Full textAbstract:
Abstract In the field of intelligent crowd video analysis, the prediction of abnormal events in dense crowds is a well-known and challenging problem. By analysing crowd particle collisions and characteristics of individuals in a crowd to follow the general trend of motion, a purpose-driven lattice Boltzmann model (LBM) is proposed. The collision effect in the proposed method is measured according to the variation in crowd particle numbers in the image nodes; characteristics of the crowd following a general trend are incorporated by adjusting the particle directions. The model predicts dense crowd abnormal events in different intervals through iterations of simultaneous streaming and collision steps. Few initial frames of a video are needed to initialize the proposed model and no training procedure is required. Experimental results show that our purpose-driven LBM performs better than most state-of-the-art methods.
26
Alamri, Abdullah. "Cloud of Things in Crowd Engineering: A Tile-Map-Based Method for Intelligent Monitoring of Outdoor Crowd Density." Sensors 22, no. 9 (April 26, 2022): 3328. http://dx.doi.org/10.3390/s22093328.
Full textAbstract:
Managing citizen and community safety is one of the most essential services that future cities will require. Crowd analysis and monitoring are also a high priority in the current COVID-19 pandemic scenario, especially because large-scale gatherings can significantly increase the risk of infection transmission. However, crowd tracking presents several complex technical challenges, including accurate people counting and privacy preservation. In this study, using a tile-map-based method, a new intelligent method is proposed which is integrated with the cloud of things and data analytics to provide intelligent monitoring of outdoor crowd density. The proposed system can detect and intelligently analyze the pattern of crowd activity to implement contingency plans, reducing accidents, ensuring public safety, and establishing a smart city. The experimental results demonstrate the feasibility of the proposed model in detecting crowd density status in real-time. It can effectively assist with crowd management tasks such as monitoring, guiding, and managing crowds to ensure safety. In addition, the proposed algorithm provides acceptable performance.
27
Üsten, Ezel, Helena Lügering, and Anna Sieben. "Pushing and Non-pushing Forward Motion in Crowds: A Systematic Psychological Observation Method for Rating Individual Behavior in Pedestrian Dynamics." Collective Dynamics 7 (August 5, 2022): 1–16. http://dx.doi.org/10.17815/cd.2022.138.
Full textAbstract:
Pushing behavior impairs people’s sense of well-being in a crowd and represents a significant safety risk. There are nevertheless still a lot of unanswered questions about who behaves how in a crowded situation, and when, where, and why pushing behavior occurs. Beginning from the supposition that a crowd is not thoroughly homogenous and that behavior can change over time, we developed a method to observe and rate forward motion. Based on the guidelines of quantitative content analysis, we came up with four categories: (1) falling behind, (2) just walking, (3) mild pushing, and (4) strong pushing. These categories allow for the classification of the behavior of any person at any time in a video, and thereby the method allows for a comprehensive systematization of individuals’ actions alongside temporal crowd dynamics. The application of this method involves videos of moving crowds including trajectories. The initial results show a very good inter-coder reliability between two trained raters demonstrating the general suitability of the system to describe forward motion in crowds systematically and quantify it for further analysis. In this way, pushing behavior can be better understood and, prospectively, risks better identified. This article offers a comprehensive presentation of this method of observation.
28
Xu, Han, Xiangxia Ren, Weiguo Song, Jun Zhang, and Rayyan Saidahmed. "Spatial and temporal analysis of the bottleneck flow under different walking states with a moving obstacle." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 1 (January 1, 2023): 013401. http://dx.doi.org/10.1088/1742-5468/aca2a2.
Full textAbstract:
Abstract The regulation of a moving obstacle on crowd movement offers the possibility to enhance evacuation efficiency in emergency situations. In this paper, a series of controlled experiments are conducted to study the effect of the moving obstacle on crowd dynamics for pedestrians in three different competitive levels, which respectively correspond to three different walking states. The enhancement effects of the moving obstacle on evacuation efficiency for the crowd in the dual-task and high-motivated walking states are confirmed, and the positions of the moving obstacle are crucial. It is found that the moving obstacle diminishes the order of the trajectories for the crowd in the dual-task and normal walking states, while it boosts near the exit for the crowd in the high-motivated walking state. And the moving obstacle makes the linear backward propagations of stop-and-go wave disappear for the crowd in the dual-task and high-motivated walking states, but the frequency of stop behavior increases for the crowd in the dual-task and normal walking states. The profiles of evacuation time show that the moving obstacle impedes the pedestrian flow from the front of the exit and increases evacuation efficiency for the pedestrians near the walls of the exit. The analysis of time headway suggests that the moving obstacle with a gap of 1.0 m or 1.2 m to the exit can reduce the number of the pedestrians waiting near the exit for the crowd in the dual-task and high-motivated walking states. Besides, the gap of 0.8 m between the moving obstacle and the exit makes the conflicts at the exit is increased, but the gap of 1.0 m or 1.2 m makes the number of conflicts at the exit be reduced. This study helps the evacuation management of dense crowds and improves the design of facilities to facilitate pedestrian traffic.
29
Sun, Libo, and Norman Badler. "Exploring the Consequences of Crowd Compression Through Physics-Based Simulation." Sensors 18, no. 12 (November 27, 2018): 4149. http://dx.doi.org/10.3390/s18124149.
Full textAbstract:
Statistical analysis of accidents in recent years shows that crowd crushes have become significant non-combat, non-environmental public disasters. Unlike common accidents such as fires, crowd crushes may occur without obvious external causes, and may arise quickly and unexpectedly in otherwise normal surroundings. We use physics-based simulations to understand the processes and consequences of compressive forces on high density static crowds consisting of up to 400 agents in a restricted space characterized by barriers to free movement. According to empirical observation and experimentation by others, we know that local high packing density is an important factor leading to crowd crushes and consequent injuries. We computationally verify our hypothesis that compressive forces create high local crowd densities which exceed human tolerance. Affected agents may thus be unable to move or escape and will present additional movement obstacles to others. Any high density crowd simulation should therefore take into account these possible negative effects on crowd mobility and behavior. Such physics-based simulations may therefore assist in the design of crowded spaces that could reduce the possibility of crushes and their consequences.
30
Zeitz, Kathryn, Pari Delir Haghighi, Frada Burstein, and Jeffrey Williams. "Understanding the drivers on medical workloads: an analysis of spectators at the Australian Football League." Australian Health Review 37, no. 3 (2013): 402. http://dx.doi.org/10.1071/ah13032.
Full textAbstract:
Objective. The present study was designed to further understand the psychosocial drivers of crowds impacting on the demand for healthcare. This involved analysing different spectator crowds for medical usage at mass gatherings; more specifically, did different football team spectators (of the Australian Football League) generate different medical usage rates. Methods. In total, 317 games were analysed from 10 venues over 2 years. Data were analysed by the ANOVA and Pearson correlation tests. Results. Spectators who supported different football teams generated statistically significant differences in patient presentation rates (PPR) (F15, 618 = 1.998, P = 0.014). The present study confirmed previous findings that there is a positive correlation between the crowd size and PPR at mass gatherings but found a negative correlation between density and PPR (r = –0.206, n = 317, P < 0.0005). Conclusions. The present study has attempted to scientifically explore psychosocial elements of crowd behaviour as a driver of demand for emergency medical care. In measuring demand for emergency medical services there is a need to develop a more sophisticated understanding of a variety of drivers in addition to traditional metrics such as temperature, crowd size and other physical elements. In this study we saw that spectators who supported different football teams generated statistically significant differences in PPR. What is known about this topic? Understanding the drivers of emergency medical care is most important in the mass gathering setting. There has been minimal analysis of psychological ‘crowd’ variables. What does this paper add? This study explores the psychosocial impact of supporting a different team on the PPR of spectators at Australian Football League matches. The value of collecting and analysing these types of data sets is to support more balanced planning, better decision support and knowledge management, and more effective emergency medical demand management. What are the implications for practitioners? This information further expands the body of evidence being created to understand the drivers of emergency medical demand and usage. In addition, it supports the planning and management of emergency medical and health-related requirements by increasing our understanding of the effect of elements of ‘crowd’ that impact on medical usage and emergency healthcare.
31
Mladenow, Andreas, Christine Bauer, and Christine Strauss. "“Crowd logistics”: the contribution of social crowds in logistics activities." International Journal of Web Information Systems 12, no. 3 (August 15, 2016): 379–96. http://dx.doi.org/10.1108/ijwis-04-2016-0020.
Full textAbstract:
Purpose The paper aims to provide the necessary basis for a novel interdisciplinary research field. Various types and implementations of crowdsourcing have emerged in the market; many of them are related to logistics. While we can identify plenty of crowd logistics applications using information technology capabilities and information sharing in practice, theories behind this phenomenon have received only limited attention. This paper accounts for filling this research gap by analyzing the crowd’s contributions in logistics of goods and information. Design/methodology/approach This paper is part of an ongoing research endeavor in the field of location-based crowdsourcing. It represents conceptual work that builds on a literature review enriched with an in-depth analysis of real-world examples in the field of crowd logistics. Using a scoring method, we provide an example how a company may evaluate the alternatives of crowd logistics. The main approach is an analysis of variants of how the social crowd may be integrated in logistics processes. The work is conceptual in its core. Thereby, we use real-world examples of crowdsourcing applications to underpin the evaluated variants of crowd logistics. Findings The paper presents relevant theoretical background on crowd logistics. The authors differentiate between variants of crowd logistics with their flow of materials, goods and information. Thereby they zoom in the type, significance and process flow of the crowd’s contributions. They discuss potential advantages and challenges of logistics with the performing crowd and deeply discuss opportunities and challenges from a business and from an individual’s perspective. Finally, they highlight a route map for future research directions in this novel interdisciplinary research field. Research limitations/implications As this work is conceptual in its core, generalizations may be drawn only with great care. Still, we are in a position to propose a route map for further research in this area in this paper. Also the integration of an analysis of a scale of real-world applications allows us to highlight our research’s practical relevance and implications. Originality/value The main contribution of this paper is an in-depth analysis and consolidation of innovative crowd logistics applications to provide an overview on recent implementations. The authors propose a categorization scheme and contribute with a route map for further research in the field of crowd logistics.
32
Wax, Amy, Andrea Hopmeyer, Paschal N. Dulay, and Tal Medovoy. "Commuter College Student Adjustment: Peer Crowd Affiliation as a Driver of Loneliness, Belongingness, and Risk Behaviors." Emerging Adulthood 7, no. 5 (June 11, 2018): 363–69. http://dx.doi.org/10.1177/2167696818781128.
Full textAbstract:
Although previous research has clearly demonstrated the impact that peer crowd affiliation has on socioemotional and risk-related outcomes, very few studies have investigated this relation in samples of emerging adults, and even fewer have focused specifically on commuter college students. Accordingly, the current study aimed to fill this gap in the literature by exploring the relationship between peer crowds and college adjustment at a commuter school. Participants were 663 students at a large public university in Southern California (campus population of 92% commuters). Factor analytic results indicated the presence of four crowd dimensions on campus: (a) social/partiers, (b) creatives and activists, (c) campus active, and (d) international students. Furthermore, path analysis results indicated that these crowd dimensions predict loneliness, college belongingness, and risk behaviors. Overall, the results of this study indicate the presence of a peer crowd landscape unique to commuter schools that has important implications for student adjustment.
33
Livshits, Benjamin, and Todd Mytkowicz. "Saving Money While Polling with InterPoll Using Power Analysis." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 159–70. http://dx.doi.org/10.1609/hcomp.v2i1.13168.
Full textAbstract:
Crowd-sourcing is increasingly being used for providing responses to polls and surveys on a large scale. Companies such as SurveyMonkey and Instant.ly are attempting to make crowd-sourced surveys commonplace, by making it easy to pose survey questions using an easy-to-use UI and retrieve results with a relatively low latency by having dedicated crowds at their disposal. In this paper we argue that the ease with which polls can be created conceals an inherent difficulty: the survey maker does not know how many workers to hire for their survey. Asking too few may lead to samples sizes that `"do not look impressive enough." Asking too many clearly involves spending extra money, which can quickly become costly. Existing crowd-sourcing platforms do not provide help with this, neither, one can argue, do they have any incentive to do so. We present a systematic approach to determining how many samples (i.e. workers) are required to achieve a certain level of statistical significance by showing how to automatically perform power analysis on questions of interest. Using a range of queries we demonstrate that power analysis can save significant amounts of money and time by concluding that frequently, only a handful of results is required to arrive at a certain decision. We have implemented our approach within InterPoll, aprogrammable developer-driven polling system that uses a generic crowd (Mechanical Turk) as a back-end. Power analysis is automatically performed given both the structure of the query and the data that is being polled from the crowd. In all of our studies we are able to obtain statistically significant answers for under $30, with most costing less than $10. Our approach saves both time and money for the survey maker.
34
Lu, Jiaqi, Shijun Liu, Lizhen Cui, Li Pan, and Lei Wu. "Crowd wisdom drives intelligent manufacturing." International Journal of Crowd Science 1, no. 1 (March 6, 2017): 39–47. http://dx.doi.org/10.1108/ijcs-01-2017-0002.
Full textAbstract:
Purpose A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process. Design/methodology/approach Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing. Findings This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process. Originality/value The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.
35
Warren, William H. "Collective Motion in Human Crowds." Current Directions in Psychological Science 27, no. 4 (July 11, 2018): 232–40. http://dx.doi.org/10.1177/0963721417746743.
Full textAbstract:
The balletic motion of bird flocks, fish schools, and human crowds is believed to emerge from local interactions between individuals in a process of self-organization. The key to explaining such collective behavior thus lies in understanding these local interactions. After decades of theoretical modeling, experiments using virtual crowds and analysis of real crowd data are enabling us to decipher the “rules of engagement” governing these interactions. On the basis of such results, my students and I built a dynamical model of how a pedestrian aligns his or her motion with that of a neighbor and how these binary interactions are combined within a neighborhood of interaction. Computer simulations of the model generate coherent motion at the global level and reproduce individual trajectories at the local level. This approach has yielded the first experiment-driven, bottom-up model of collective motion, providing a basis for understanding more complex patterns of crowd behavior in both everyday and emergency situations.
36
Macsotay, Tomas. "Sacred Forms and the Crowd's Guilt in Late Seventeenth- and Eighteenth-Century Execution Imagery." Cultural History 8, no. 1 (April 2019): 43–69. http://dx.doi.org/10.3366/cult.2019.0186.
Full textAbstract:
As new histories of the public execution are published, cultural perceptions of crowds are again enjoying scholarly interest. This contribution evaluates the role to be played by visual culture in crowd culture, weaving an account that draws from a closer analysis of live visual relations to explain both crowd impulses and its afterimages. A visually structured history can be navigated in order to examine the murder on 20 August 1672 of Jan and Cornelis de Wit at the hands of a street crowd, a determining event in the Dutch ‘disaster year’ of 1672. Giving close examination to contemporary prints, a drawing and a play, the contribution makes two overarching observations: first, that a Christological reading of the execution site strongly informed all of the after-images of the murders. Moreover, sacredness worked as a schema for the mob's own part during the tragedy. Second, the crowd's behaviour followed a pattern of structured theatricality and merriment that is best understood in the context of historical disturbance culture. The Dutch crowds of 1672 offered a double bill of religious and secular visual logics, blurring the limits of a judicially ordered punishment and producing in the tacit testimonies examined here a marked affective response.
37
Zimaroyeva, А. А., and О. V. Matsyura. "ОСОБЛИВОСТІ ГНІЗДОВОЇ ЕКОЛОГІЇ ПОПУЛЯЦІЙ СІРИХ ВОРОН (CORVUS CORNIX L.) В УМОВАХ ТРАНСФОРМОВАНИХ ЛАНДШАФТІВ." Biological Bulletin of Bogdan Chmelnitskiy Melitopol State Pedagogical University 1, no. 3 (December 25, 2011): 26. http://dx.doi.org/10.15421/20111_31.
Full textAbstract:
<p>The comparative analysis of hooded crow breeding ecology was performed for Zhitomir region in 2010-2011 in terms of rural and urban distinctions. Height of trees, tree species diversity in breeding biotopes, nest size, and breeding success of hooded crows were considered for agricultural and urban landscapes. Definite patterns of breeding ecology were estimated for urban and rural populations of hooded crows. On average, the breeding density of hooded crows was 7-8 individuals/km<sup>2</sup> in Zhitomir region.</p> <p>Positive correlation was found between the breeding density of hooded crows and degree of transformation and urbanization of landscape of Zhytomyr region. The main breeding habitats of hooded crows in the Zhitomir region were the wetland sites. Communities of urban birds were characterized by earlier terms of nest building, more higher position of nests in the trees and high diversity of tree breeding habitats. In urbanized landscape we determined high proportion of large (6 eggs) and small clutches of hooded crow (3 eggs).</p> <p>On average the breeding success of crows in Zhytomyr region is 51.1%. We suggested that the main factor was high level of elimination of embryos and chicks of hooded crow. In urbanized landscapes the breeding success (50%) is somewhat higher than that in rural areas (43.5%). This can be explained by specific features of ecological niches - in cities the bird communities have few natural predators that kill chicks and destroy clutches, and potentially have more available food resources.</p> <p><em>Kew words: hooded crow, breeding ecology, Zhitomir region, comparative analysis</em></p>
38
Lauto, Giancarlo, and Finn Valentin. "How preference markets assist new product idea screening." Industrial Management & Data Systems 116, no. 3 (April 11, 2016): 603–19. http://dx.doi.org/10.1108/imds-07-2015-0320.
Full textAbstract:
Purpose – The purpose of this paper is to examine the different heuristics adopted by a crowd and a management committee to evaluate new product proposals, and whether, in assessing the value of proposals, they emphasize different features. Design/methodology/approach – The study takes a quantitative analysis approach to study an internal innovation contest held by the biotechnology company Novozymes. The contest generated 201 proposals that were evaluated by 109 research and development professionals by means of a virtual preference market, and by a management committee. Findings – The crowd and the committees’ assessments of the value of the proposals were based on different features. The committee emphasized experience and inventors’ seniority; the crowd set more store on informative idea descriptions but penalized overly complex and lengthy proposals. Research limitations/implications – The design of the innovation contest does not allow full comparison of the preference functions of crowd and committee. The findings from this case study cannot be generalized. The early stage of new product development seems fruitful for investigating crowdsourcing and knowledge management. Practical implications – Firms should consider adopting preference markets for idea screening and evaluation since they appraise ideas from different angles compared to managers. However, they complement, rather than substitute managerial evaluation, especially in the case of more detailed proposals. Originality/value – This is one of the first attempts to identify differences in the decision-making processes of crowds and committees. The paper identifies their strengths as evaluators of new product ideas and finds that the “wisdom of crowds” has some limitations in relation to the ability to process complex information.
39
Liu, Linfan, Huajun Zhang, Jupeng Xie, and Qin Zhao. "Dynamic Evacuation Planning on Cruise Ships Based on an Improved Ant Colony System (IACS)." Journal of Marine Science and Engineering 9, no. 2 (February 19, 2021): 220. http://dx.doi.org/10.3390/jmse9020220.
Full textAbstract:
The emergency evacuation route planning of cruise ships directly affects the safety of all crew members and passengers during emergencies. Research on the planning of emergency evacuation routes for cruise ships is a frontier subject of maritime safety. This study proposes an improved ant colony system (IACS) to solve the evacuation route planning of crowds on cruise ships. The IACS, which is different from common single-path ant colony system (ACS) evacuation algorithms, is used to solve the multipath planning problem of crowd evacuation from cruise ships by considering crowd density and speed in the model. An increasing flow method is introduced into the IACS to improve the efficiency of the proposed algorithm. Numerical experiments show that this method meets the requirements of evacuation analysis guidelines for new and existing passenger ships (MSC.1/Circ.1533)and can effectively and efficiently plan the emergency evacuation path for cruise ship crowd.
40
Dawson, Stephanie E., and Garth Davies. "Gender differences in understanding police perspectives on crowd disorder." Policing: An International Journal of Police Strategies & Management 40, no. 2 (May 15, 2017): 228–43. http://dx.doi.org/10.1108/pijpsm-06-2016-0080.
Full textAbstract:
Purpose The purpose of this paper is to examine the nature and dynamics of crowd disorder from the perspective of the police in a Canadian context, as well as to extend this perspective to include the opinions of female police officers. Design/methodology/approach A total of 460 Vancouver police officers participated in this study. Following the 2011 Stanley Cup riot, police officers received mail-based questionnaires focussed on gathering information concerning police perceptions of the crowd and the police response in riot situations. A total of 15 response items were analysed using descriptive approaches and confirmatory factor analyses. Findings The study findings revealed that, in addition to being multidimensional, the police perspective of crowd disorder may be contingent upon certain officer characteristics. Although, the police perspective can generally be categorized by four overarching constructs: dichotomous crowd, homogeneous threat, strict policing and tactical response; it becomes more complex once the officers’ gender is taken into consideration. The results suggest that the male and female police officers may have some differing views about the nature of crowds and the type of police response required to manage disorderly crowd situations. Originality/value In addition to being the first study to analyse police perceptions of crowd disorder in a Canadian context, this research is the first to include the points of view of female officers.
41
Maeda, Isamu, Mohammad Shohel Rana Siddiki, Tsutomu Nozawa-Takeda, Naoki Tsukahara, Yuri Tani, Taki Naito, and Shoei Sugita. "Population Abundance of Potentially Pathogenic Organisms in Intestinal Microbiome of Jungle Crow (Corvus macrorhynchos) Shown with 16S rRNA Gene-Based Microbial Community Analysis." BioMed Research International 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/438956.
Full textAbstract:
Jungle Crows (Corvus macrorhynchos) prefer human habitats because of their versatility in feeding accompanied with human food consumption. Therefore, it is important from a public health viewpoint to characterize their intestinal microbiota. However, no studies have been involved in molecular characterization of the microbiota based on huge and reliable number of data acquisition. In this study, 16S rRNA gene-based microbial community analysis coupled with the next-generation DNA sequencing techniques was applied to the taxonomic classification of intestinal microbiome for three jungle crows. Clustering of the reads into 130 operational taxonomic units showed that at least 70% of analyzed sequences for each crow were highly homologous toEimeriasp., which belongs to the protozoan phylumApicomplexa. The microbiotas of three crows also contained potentially pathogenic bacteria with significant percentages, such as the generaCampylobacterandBrachyspira. Thus, the profiling of a large number of 16S rRNA gene sequences in crow intestinal microbiomes revealed the high-frequency existence or vestige of potentially pathogenic microorganisms.
42
Yuan, Jian, Lin He, Feng Fan, and Cong Liu. "THE DYNAMIC PARAMETERS OF PASSIVE HUMAN AT TEMPORARY DEMOUNTABLE GRANDSTANDS DURING EXPOSURE TO LATERAL VIBRATION." Journal of Civil Engineering and Management 24, no. 4 (June 29, 2018): 265–83. http://dx.doi.org/10.3846/jcem.2018.3073.
Full textAbstract:
Modelling the interaction between crowds and temporary demountable grandstands with identifying the human dynamic properties are challenges for structure optimal design. In this paper, for investigating and understanding the human and structural lateral dynamic features. A demountable grandstand was tested to obtain its model parameters firstly. Then it is tested at amplitudes between 0.16 m/s2 to 1.54 m/s2 with 75 random waves through a shaking table when occupied by twenty persons. Afterword a simplified two-degree of freedom lumped dynamic model of the joint human-structure system is reinterpreted. Utilizing the state-space model, the passive crowd dynamic parameters are obtained, based on root mean square accumulation error analysis. Statistical analysis of the predictive results concludes that seated crowd model damping ratio is 0.5, and the probable natural frequency is 2.0 Hz with the model mass ratio 0.7. For standing crowd model, the probable natural frequency is 1.5 Hz with the model mass damping ratio 0.4, and the model mass ratio is 0.7. It may have ability to serve as a reference value that can be utilized in vibration safety and serviceability assessment of TDGs, to estimate realistically the vibration response on the occasions when crowd are seated or standing.
43
French, Tim, Nik Bessis, Carsten Maple, and Eleana Asimakopoulou. "Trust Issues on Crowd-Sourcing Methods for Urban Environmental Monitoring." International Journal of Distributed Systems and Technologies 3, no. 1 (January 2012): 35–47. http://dx.doi.org/10.4018/jdst.2012010103.
Full textAbstract:
This paper explores trust related issues arising from the use of a crowd-sourcing method. Crowd-sourcing is a relatively new method that utilises modern technologies to gather, analyse and visualise specific “on-the-fly” data. The data is typically acquired through the employment of mobile technology, with each device running a bespoke application that captures the desired information. The resulting “crowd sourced” data is readily available and the corresponding maps produced can in turn, be used to support strategic planning and to facilitate overall, more informed decision-making. The purpose is to provide insights into this novel approach to data collection, aggregation and subsequent visualisation. Specifically, the focus centres upon issues of trust and security that are inherent not merely to the use of crowd sourced data capture itself, but also crucially, to the stewardship and usage of the resultant data sets within e-government settings. A novel community centric usage scenario is presented that seeks to show how issues of trust pervade the technology. Hence, both rewards and risks are revealed and we go on to outline a preliminary approach intended to support a trusted and reputable “crowdy” data architecture.
44
FUJIMOTO, KAYO, PENG WANG, and THOMAS W. VALENTE. "The decomposed affiliation exposure model: A network approach to segregating peer influences from crowds and organized sports." Network Science 1, no. 2 (July 30, 2013): 154–69. http://dx.doi.org/10.1017/nws.2013.7.
Full textAbstract:
AbstractSelf-identification with peer crowds (jocks, popular kids, druggies, etc.) has an important influence on adolescent substance use behavior. However, little is known about the impact of the shared nature of crowd identification on different stages of adolescent drinking behavior, or the way crowd identification interacts with participation in school-sponsored sports activities. This study examines drinking influences from (1) peers with shared crowd identities, and (2) peers who jointly participate in organized sports at their school (activity members). This study introduces a new network analytic approach that can disentangle the effects of crowd identification and sports participation on individual behavior. Using survey data from adolescents in five high schools in a predominantly Hispanic/Latino district (N = 1,707), this paper examines the association between social influences and each stage of drinking behavior (intention to drink, lifetime, past-month, and binge drinking) by conducting an ordinal regression analysis. The results show that both shared identities and joint participation were associated with all stages of drinking, controlling for friends' influence. Additionally, shared identification overlapped with joint participation was associated with more frequent drinking. Related policy implications are discussed.
45
Polyakova, Yu M. "Human Resource Management Based on Modern Crowd Technologies: Crowd Staffing, Crowd Recruiting and Crowd Training." Scientific Research of Faculty of Economics. Electronic Journal 12, no. 3 (September 28, 2020): 16–30. http://dx.doi.org/10.38050/2078-3809-2020-12-3-16-30.
Full textAbstract:
The rapidly changing conditions of the struggle for talented personnel in the context of mass digitalization require a revision of the methods of personnel management in modern organizations. The aim of the study is to determine the role of crowd-technologies in increasing the efficiency of search, selection and development of personnel in Russian organizations, as well as to develop a system of criteria and indicators for assessing the effectiveness of this type technologies. The scientific works of domestic and foreign scientists, reports of international organizations, the Ministry of Economic Development of the Russian Federation, companies specializing in crowd-technologies were studied. The work used the methods of induction, comparative analysis, benchmarking of the best foreign and Russian practices of using crow- technologies in the field of HR-management and the method of conceptual and methodological modeling. The research conducted by the author made it possible to identify the socio-economic effects of the use of crowd staffing and crowd recruiting in the field of personnel search and selection, crowd training as a method of training employees, and also to propose a number of criteria and indicators for assessing the effectiveness of using these technologies in order to make effective decisions by management personnel.
46
Sim, Jackie, Anthony Blakeborough, and Martin Williams. "Modelling of Joint Crowd-Structure System Using Equivalent Reduced-DOF System." Shock and Vibration 14, no. 4 (2007): 261–70. http://dx.doi.org/10.1155/2007/498081.
Full textAbstract:
For human assembly structures in which the mass of the crowd is significant compared to that of the structure, it is necessary to model the passive crowd as a dynamic system added to the main structural system. Earlier work by the authors has analysed the frequency response of a joint crowd-structure system in which the structure is treated as a single degree-of-freedom (SDOF) system and the seated and standing crowds are each modelled as a two degree-of-freedom (2DOF) system. It was found that the occupied structure has dynamic properties different to the empty structure. This paper investigates representing the joint crowd-structure system as an equivalent reduced-DOF system that would have the advantage of simplifying the analysis. The modal properties of the equivalent reduced-DOF system, if known, can give a useful indication of how the passive crowd affects the modal properties of the occupied structure. Two equivalent reduced-DOF systems are investigated – SDOF and 3DOF systems. The errors between the responses of the equivalent systems and the full model are calculated and presented in the paper. The results show that the full model exhibits the behaviour of a SDOF system for structures with natural frequencies less than 4 Hz (when empty), whereas for structures with natural frequencies above 4 Hz the equivalent 3DOF system gives a better fit to the full model.
47
Abalkhail, Asma Abdulaziz Abdullah, and Sumiah Mashraf Abdullah Al Amri. "Saudi Arabia’s Management of the Hajj Season through Artificial Intelligence and Sustainability." Sustainability 14, no. 21 (October 29, 2022): 14142. http://dx.doi.org/10.3390/su142114142.
Full textAbstract:
High-density gatherings have the potential to turn from a peaceful mass into a human disaster unless they are managed in an organized manner. Saudi Arabia’s Ministry of Hajj implemented an integrated system based on artificial intelligence. The Kingdom of Saudi Arabia (KSA) was eager to take advantage of the techniques of artificial intelligence to conduct its strategic plan, considering limited pilgrims who would be allowed to perform the Hajj rites during these exceptional circumstances. In this study, the experience of the KSA in crowd management using artificial intelligence during the Hajj was examined to create a model for similar circumstances. This study employed the descriptive analytical method. The program Arc Gis Pro 2.9.2 was used to produce maps related to the study. A strategic analysis was also conducted regarding the experience of the KSA in crowd management using SWOT analysis concerning the study area. This study found that the KSA has become a leader in crowd management and a reference and role model in managing crowds through an expanded use of artificial intelligence during the COVID-19 pandemic. It undertook all necessary precautionary measures to protect the pilgrims, and no injuries were reported.
48
Clark, Benjamin Y., Nicholas Zingale, and Joseph Logan. "Intelligence and Information Gathering Through Deliberative Crowdsourcing." Journal of Public and Nonprofit Affairs 3, no. 1 (March 31, 2017): 55. http://dx.doi.org/10.20899/jpna.3.1.55-78.
Full textAbstract:
The hollowing of the state has added new challenges for administrators attending to the competing values of the administration. This article examines how the wisdom of the crowds can be used in a deliberative manner to extract new knowledge through crowdsourcing. We will specifically examine cases of intelligence and information gathering through the analysis of a suspected nuclear reactor in Syria and the use of the crowd in mapping unknown or rapidly changing environments. Through case analysis, this article seeks to understand if crowdsourcing can offer a potential opportunity for public managers to reduce transactions costs while engaging the crowd in a form of deliberative governance to understand and potentially solve public problems. Our approach involves applying the seven lessons of deliberative governance (Scott, Adams, & Wechsler, 2004) to our cases in order to produce five administrative concepts for creating mini-publics for deliberative crowdsourcing.
49
Ngeendepi, Eslon, and Andrew Phiri. "Do FDI and Public Investment Crowd in/out Domestic Private Investment in the SADC Region." Managing Global Transitions 19, no. 1 (March 2021): 3–25. http://dx.doi.org/10.26493/1854-6935.19.3-25.
Full textAbstract:
Our study examines the crowding-in/out effect of foreign direct investment and government expenditure on private domestic investment for 15 members of the Southern African Development Community (SADC) for the period 1991–2019. The study employed the panel Pool Mean Group (PMG)/ARDL technique in estimating the short-run and long-run cointegration relationships between FDI, government capital expenditure and domestic private investment and adds three more variables for control purposes (interest rate, GDP growth rate and trade openness). For the full sample, FDI crowds-in domestic investment whilst government crowds-out domestic investment. However, in performing a sensitivity analysis, in which the sample was segregated into low and high income economies, both FDI and government investment crowd-in domestic investment whilst government expenditure crowds-out domestic investment in lower income SADC countries with no effect of FDI on domestic investment. Policy implications are discussed.
50
Gong, Vincent X., Winnie Daamen, Alessandro Bozzon, and Serge P. Hoogendoorn. "Estimate Sentiment of Crowds from Social Media during City Events." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 11 (June 21, 2019): 836–50. http://dx.doi.org/10.1177/0361198119846461.
Full textAbstract:
City events are being organized more frequently, and with larger crowds, in urban areas. There is an increased need for novel methods and tools that can provide information on the sentiments of crowds as an input for crowd management. Previous work has explored sentiment analysis and a large number of methods have been proposed relating to various contexts. None of them, however, aimed at deriving the sentiments of crowds using social media in city events, and no existing event-based dataset is available for such studies. This paper investigates how social media can be used to estimate the sentiments of crowds in city events. First, some lexicon-based and machine learning-based methods were selected to perform sentiment analyses, then an event-based sentiment annotated dataset was constructed. The performance of the selected methods was trained and tested in an experiment using common and event-based datasets. Results show that the machine learning method LinearSVC achieves the lowest estimation error for sentiment analysis on social media in city events. The proposed event-based dataset is essential for training methods to reduce estimation error in such contexts.