High Crowd Research Articles

A Study on Intestinal Parasitic Infections Among Immunocompetent Egyptian Children Attending Al-Hussein University Hospital, Cairo

Background: Parasitic infections are still a dangerous public health problem in the world, especially in developing countries including Egypt representing a major cause of morbidity and mortality mainly among children. Methods: This cross-sectional study included 400 randomly chosen immunocompetent children of both sexes. Their ages ranged from 6 months up to 12 years old. All children were subjected to a structured questionnaire sheet, stool examination using: Direct smear and concentration techniques (formol ether sedimentation and Modified Ziehl–Neelsen stain). The study was approved by the medical ethics committee of Al-Azhar University Hospitals and a written informed consent was obtained from all children's parents or gardeners. Results: Among the examined individuals, parasites were detected in only 139 ones (34.75%) mainly in the first two years of age and more common among males 35% than females 34%. By species, the parasitic prevalence rate was, G.lamblia 49 (12.25%), E.vermicularis 35 (8.75%), E. coli 22 (5.5%), E. histolytica/dispar 7 (1.75%), H. nana 4 (1.0%) and mixed infections 22 (5.5%). Positive results are more common among rural children 38% and low social classes. Low level of parent's education, low family income, high crowding index, and bad hand hygiene were considered highrisk factors of parasitic infections. Conclusion: Rural residency, bad hygiene, and low social class, as well as crowdedness, were the most significant risk factors associated with parasitic infections among children

Iterative Clustering for Energy-Efficient Large-Scale Tracking Systems

A new technique is presented to design energy-efficient large-scale tracking systems based on mobile clustering. The new technique optimizes the formation of mobile clusters to minimize energy consumption in large-scale tracking systems. This technique can be used in large public gatherings with high crowd density and continuous mobility. Utilizing both Bluetooth and Wi-Fi technologies in smart phones, the technique tracks the movement of individuals in a large crowd within a specific area, and monitors their current locations and health conditions. The new system has several advantages, including good positioning accuracy, low energy consumption, short transmission delay, and low signal interference. Two types of interference are reduced: between Bluetooth and Wi-Fi signals, and between different Bluetooth signals. An integer linear programming model is developed to optimize the construction of clusters. In addition, a simulation model is constructed and used to test the new technique under different conditions. The proposed clustering technique shows superior performance according to several evaluation criteria.

Urban footpath analysis and simulation – a case study in Sari – Iran

Urban footpath quality and pedestrian level of service is a popular subject for modelling and simulation in transport engineering. This paper reports an investigation into the capacity of footpaths alongside a city street in Sari, Iran to determine whether the current provision can meet the present and forecast pedestrian demand, or whether improvements are required. To assess the capacity of the footpaths, a database including the location and time, speed and number of pedestrians, as well as determining and identifying points of footpaths with relatively high crowding, was prepared. Finally, the level of service (LOS) was obtained using a US code and proprietary modelling tool. The results indicated that some sections of the route were currently below an acceptable LOS and needed improvement to provide an adequate provision for pedestrians. When factoring in forecast growth, the LOS in these substandard sections was predicted to reduce even further and, without improvement, could undermine future economic growth.

The effect of obstacle layouts on pedestrian flow in corridors: An experimental study

Previous research on the effect of obstacles on crowd dynamics primarily focused on relationships between the scale or position of obstacles and pedestrian movement behavior. However, the influence of different obstacle layouts on pedestrian flow in corridors has not been well investigated. Here, we conducted an experimental study on the effect of three obstacle layouts (i.e., parallel, convex and concave layouts) on pedestrian flow in corridors, creating seven scenarios for unidirectional flow and four scenarios for bidirectional flow at low and high crowd densities. The image processing method is employed to collect pedestrian trajectories. Accordingly, typical phenomena, speed, density and flow rate are obtained. It was found that in comparison with the parallel layout, average speed at high crowd density increases approximately 19% in non-parallel layouts when the distance between obstacles is 1.6 m, while the decrease rate of average passing time reaches 17%. The relationship between group speed and time is U-shaped, and group speed is reduced sharply in the parallel layout. Congestion is the severest in the parallel layout in bidirectional flow, i.e. the largest density in the parallel layout is 16% higher than that in non-parallel layouts when the longitudinal distance between obstacles is 1.6 m. Congestion is alleviated with the increasing longitudinal distance between obstacles in the non-parallel layouts. Flow rate in the non-parallel layouts (especially in the concave layout) is greater than that in the parallel layout. These results suggest that the non-parallel obstacle layouts (especially the concave layout) with larger longitudinal distance between obstacles are more beneficial to pedestrian movement, when there are obstacles in corridors. It is hoped that this study will be helpful in crowd management and pedestrian facility design.

Ethical, legal and professional accountability in emergency nursing practice: An ethnographic observational study

IntroductionAccountability in nursing practice is a concept that influences quality care, decision-making, safety standards and staff values. Therefore, understanding accountability and how it affects nursing practice could improve patient care and nurses’ working conditions. AimThe aim of this study was to find factors that influenced ethical, legal and professional accountability in emergency nursing practice. MethodsA qualitative ethnographic approach using participant observation through convenience sampling was employed as the data collection method, while ethnographic content analysis was used for data analysis. ResultsThe factors linked to nursing accountability found were classified into four main themes: daily dynamics, work environment evolution, customs and routines and bioethics principles’ application. DiscussionThe long-term effect of chronic high workload and crowding, which affects nursing accountability, could promote burnout in a junior ED workforce. Changes in the nurses’ working conditions need to be implemented to limit the workload to which an ED nurse is subjected to. ConclusionED nurses have to manage their accountability in difficult situations regularly, which followed patterns of four main themes across the majority of situations. Nonetheless, all those factors were influenced by nursing workload, an ever-present factor that was always considered by ED nurses during decision-making.

Congestion detection in pedestrian crowds using oscillation in motion trajectories

Identifying crowd congestion in high density pedestrian crowds is a challenging problem, with substantial interest for safety and security applications. We present a method to identify and localize congestion in high density crowd videos, based on the characteristic motion of individuals stuck in congestion. Pedestrians who cannot move freely due to congestion tend to undergo lateral oscillations. Using only motion features, extracted from optical flow and particle advection, we generate sampled trajectories and compute areas which show a pattern of increasing trajectory oscillation. A new and first ever data set including 15 different crowd scenes is introduced to better evaluate the accuracy of our method. Showing results on a diversity of challenging scenarios, we both qualitatively and quantitatively show that this approach provides accurate detection and excellent localization of congestion events.

First study on the male inducing signal in Keratella cochlearis: Crowding is the key

Most monogonont rotifers usually reproduce by cyclical parthenogenesis. For many rotifer species the factor inducing sexual reproduction is high population density (crowding). While Keratella cochlearis is one of the most ubiquitous monogonont freshwater rotifers, little is known about its reproduction. We provide experimental evidence that the switch from parthenogenesis to production of males in K. cochlearis is density-dependent. Single females (F1 generation) were kept in containers of varying volume representing various levels of crowding. The percentage of sexual daughters (F2 generation) producing males was higher in smaller volume treatments (higher crowding) than in larger volume treatments (lower crowding). The lowest population density at which males appeared was 38.5 females L−1 of K. cochlearis as estimated by beta regression. We also present a detailed photograph of a K. cochlearis male which has previously been known only from drawings. Surprisingly, we never observed mating and resting egg production.

The effect of the ventilation retrofit in a school on CO2, airborne particles, and energy consumptions

The energy retrofit of existing buildings is a key strategy to reduce the energy costs of the building sector. Amongst the retrofit solutions, the adoption of mechanical ventilation systems represents a necessary approach for buildings with high crowding index, such as schools.The air quality in schools is a main issue since children spend a significant fraction of the year in such microenvironments. To date, the scientific literature has carried out several studies concerning the air quality in naturally ventilated schools worldwide, nonetheless most of the studies performed a general evaluation of the air quality just using the CO2 as a comprehensive indicator. This is an oversimplified approach since the indoor air quality is affected by several pollutants, including airborne particles, whose behavior cannot be predicted by the CO2 one.The aim of the research is the evaluation of the effect of the ventilation retrofit in a classroom on different indoor air quality parameters and energy consumption. To this end a mechanical ventilation system with a heat recovery unit was installed in a test-classroom and tests with CO2-based demand controlled ventilation were performed. CO2 levels and indoor-to-outdoor particle concentrations were measured and compared to the pre-retrofit ventilation conditions (i.e. manual airing procedures).Results showed that mechanical ventilation systems have simultaneous positive effects on the different pollutants investigated as well as on ventilation heat losses: indeed, lower indoor-to-outdoor concentration ratios, with respect to the airing approach, were detected simultaneously for CO2, sub-micron particles and PM10.

Detecting high indoor crowd density with Wi-Fi localization: a statistical mechanics approach

We address the problem of detecting highly raised crowd density in situations such as indoor dance events. We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi localization of smart phones. Using a probabilistic model inspired by statistical mechanics, and relying only on big data analytics, we tackle three challenges: (1) the ambiguity of Wi-Fi based indoor positioning, which appears regardless of whether the latter is performed with machine learning or with optimization, (2) the MAC address randomization when a device is not connected, and (3) the volatility of packet interarrival times. The main result is that our estimation becomes more—rather than less—accurate when the crowd size increases. This property is crucial for detecting dangerous crowd density.

Abnormal crowd density estimation in aerial images

The unpreceded growth of intelligent surveillance systems has resulted in an urgent need for automatic analysis of the captured scenes. Automatic detection of an abnormal crowd in aerial images can provide useful information to prevent disasters. In fact, aerial images have the advantage of covering a very large view of the people distributed over a scene. Accordingly, we propose a high density crowd detection method in aerial images. In this method, we adapted the bag of words technique using the multiblock local binary pattern as a texture descriptor to extract low-level features. In addition, we also used a three-level classification strategy to reduce confusion between crowd density classes. The experimental results reveal the performance of our method while estimating the crowd density in a challenging context.

Experiment Calibrated Simulation Modeling of Crowding Forces in High Density Crowd

Crowding force is an important index in evaluating the safety of those within high density crowds. However, studies on high density crowd simulation models have not been sufficiently developed, and related experimental studies are not sufficiently detailed to guide modeling research. Models that can reproduce real high density crowds and enable calibration of key parameters are lacking. In this study, we improved the typical social force model to simulate high density crowd motion with the calculation of crowding forces. To simulate high density crowds, pedestrians were modeled using the three-circle model, and an agent-based pedestrian model was formulated that can regulate the psychological force automatically according to crowd density. An individual crowd density calculation method is proposed that is more suitable for high density crowds. To calculate real crowding force, body stiffness was formulated and the corresponding parameters were calibrated by a series of experiments. Field experiments show that passengers bear greater force on their backs than the force on each shoulder in metro carriage. The modified model was verified by comparing the simulation results with observed data. We applied this model to the Beijing subway, and the theoretical maximum crowd densities in different seasons were calculated from the perspective of crowding force to ensure the safety of passengers, which are 7.2 people/m2 in winter and 10.3 people/m2 in summer. Therefore, to ensure passenger safety, the subway operation department should arrange more trains during winter peak hours.

Scale Driven Convolutional Neural Network Model for People Counting and Localization in Crowd Scenes

Counting and localization of people in videos consisting of low density to high density crowds encounter many key challenges including complex backgrounds, scale variations, nonuniform distributions, and occlusions. For this purpose, we propose a scale driven convolutional neural network (SD-CNN) model, which is based on the assumption that heads are the dominant and visible features regardless of the density of crowds. To deal with the problem of different scales of heads in different regions of the videos, we annotate a set of heads in random locations of the videos to develop a scale map representing the mapping of head sizes. We then extract scale aware proposals based on the scale map which are fed to the SD-CNN model acting as a head detector. Our model provides a response matrix rendering accurate head positions via nonmaximal suppression. For experimental evaluations, we consider three standard datasets presenting low density to high density crowd scenes. Our proposed SD-CNN model outperforms the state-of-the-art methods in terms of both frame-level and pixel-level analyses.

Contemporary College Students' Reflections of their High School Peer Crowds.

High school peer crowds are fundamental components of adolescent development with influences on short-and long-term life trajectories. This study provides the perspectives of contemporary college students regarding their recent high school social landscapes, contributing to current research and theory on the social contexts of high school. This study also highlights the experiences of college-bound students who represent a growing segment of the adolescent population. 61 undergraduates attending universities in two states participated in 10 focus groups to reflect on their experiences with high school peer crowds during the late 2010s. Similar to seminal research on peer crowds, we examined crowds and individuals along several focal domains: popularity, extracurricular involvement, academic orientation, fringe media, illicit risk taking, and race-ethnicity. We find that names and characteristics of crowds reflect the current demographic and cultural moment (i.e., growing importance of having a college education, racial-ethnic diversity) and identify peer crowds that appear to be particularly salient for college-bound youth. Overall, this study illuminates how the retrospective accounts of college-bound students offer insight into high school social hierarchies during a time of rapid social change.

Work organization of evacuation hospitals in Saratov during the Battle of Stalingrad

The work organization of evacuation hospitals in Saratov during the Stalingrad battle is analyzed. A brief description of the medical issues of the Stalingrad strategic defensive operation is given. The factors that determined the evacuation of a significant number of wounded and sick Red Army soldiers to the medical facilities of the Local evacuation point-45 are indicated. Statistical data are provided on the number of people taken to treatment and sent to other rear hospitals who suffered from the site of the crucial battle of the Great Patriotic and World War II. The importance of using railway, water and motor vehicles for the evacuation of the wounded and sick was noted. The issues of the organization of sanitary and hygienic and antiepidemic work in Saratov and the region in the period of approaching the front, high crowding of the local population and arriving refugees, as well as the constant arrival of ambulance transports are considered. The enormous role of the Saratov Medical Institute staff in medical and consulting work in evacuation hospitals was emphasized. Their high professional training, constant search of non-standard ways of solving complex problems arising in the course of daily clinical activity, allowed to achieve high results in the work of medical institutions, to save the lives of a large number of wounded soldiers and commanders of the Red Army. The contribution and main directions of medical and scientific activity of leading specialists of the medical institute in the considered historical period of time are highlighted.

Star formation history and metallicity in the Galactic inner bulge revealed by the red giant branch bump

Context. The study of the inner region of the Milky Way bulge is hampered by high interstellar extinction and extreme source crowding. Sensitive high angular resolution near-infrared imaging is needed to study stellar populations and their characteristics in such a dense and complex environment. Aims. We aim at investigating the stellar population in the innermost Galactic bulge, to study the star formation history in this region of the Galaxy. Methods. We used the 0.2″ angular resolution JHKs data from the GALACTICNUCLEUS survey to study the stellar population within two 8.0′×3.4′ fields, about 0.6° and 0.4° to the Galactic north of the Milky Way centre and to compare it with the one in the immediate surroundings of Sagittarius A*. We also characterise the absolute extinction and the extinction curve of the two fields. Results. The average interstellar extinction to the outer and the inner field is AKs ∼ 1.20 ± 0.08 mag and ∼1.48 ± 0.10 mag, respectively. We present Ks luminosity functions that are complete down to at least two magnitudes below the red clump (RC). We detect a feature in the luminosity functions that is fainter than the RC by 0.80 ± 0.03 and 0.79 ± 0.02 mag, respectively, in the Ks band. It runs parallel to the reddening vector. We identify the feature as the red giant branch bump. Fitting α-enhanced BaSTI luminosity functions to our data, we find that a single old stellar population of ∼12.8 ± 0.6 Gyr and Z = 0.040 ± 0.003 provides the best fit. Our findings thus show that the stellar population in the innermost bulge is old, similar to the one at larger distances from the Galactic plane, and that its metallicity is about twice solar at distances as short as about 60 pc from the centre of the Milky Way, similar to what is observed at about 500 pc from the Galactic Centre. Comparing the obtained metallicity with previous known values at larger latitudes (|b| > 2°), our results favour a flattening of the gradient at |b| < 2°. As a secondary result we obtain that the extinction index in the studied regions agrees within the uncertainties with our previous value of α = 2.30 ± 0.08 that was derived for the very Galactic centre.

Exploring the Consequences of Crowd Compression Through Physics-Based Simulation.

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.

Milky Way demographics with the VVV survey

Context. The inner regions of the Galaxy are severely affected by extinction, which limits our capability to study the stellar populations present there. The Vista Variables in the Vía Láctea (VVV) ESO Public Survey has observed this zone at near-infrared wavelengths where reddening is highly diminished. Aims. By exploiting the high resolution and wide field-of-view of the VVV images we aim to produce a deep, homogeneous, and highly complete database of sources that cover the innermost regions of our Galaxy. Methods. To better deal with the high crowding in the surveyed areas, we have used point spread function (PSF)-fitting techniques to obtain a new photometry of the VVV images, in the ZY JHKs near-infrared filters available. Results. Our final catalogs contain close to one billion sources, with precise photometry in up to five near-infrared filters, and they are already being used to provide an unprecedented view of the inner Galactic stellar populations. We make these catalogs publicly available to the community. Our catalogs allow us to build the VVV giga-CMD, a series of color-magnitude diagrams of the inner regions of the Milky Way presented as supplementary videos. We provide a qualitative analysis of some representative CMDs of the inner regions of the Galaxy, and briefly mention some of the studies we have developed with this new dataset so far.

An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions.

In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.

DEEP LEARNING BASED SUPERVISED SEMANTIC SEGMENTATION OF ELECTRON CRYO-SUBTOMOGRAMS.

Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables analyzing the native structures of macromolecular complexes and their spatial organization inside single cells. However, due to the high degree of structural complexity and practical imaging limitations, systematic macromolecular structural recovery inside CECT images remains challenging. Particularly, the recovery of a macromolecule is likely to be biased by its neighbor structures due to the high molecular crowding. To reduce the bias, here we introduce a novel 3D convolutional neural network inspired by Fully Convolutional Network and Encoder-Decoder Architecture for the supervised segmentation of macromolecules of interest in subtomograms. The tests of our models on realistically simulated CECT data demonstrate that our new approach has significantly improved segmentation performance compared to our baseline approach. Also, we demonstrate that the proposed model has generalization ability to segment new structures that do not exist in training data.

A Review on Human Pedestrian Movement System Using Agent-Based Simulation and Discrete Event Simulation

Human pedestrian is a complex behavior which involves various inputs and outputs and requires a lot of decision making process. By understanding fundamentals of Discrete Event Simulation (DES) and Agent-Based Simulation (ABS), it is found that both are suitable to simulate this complex movement. This paper proposed the idea of understanding how, in its basic knowledge, these two simulation models can be combined together to enhance human pedestrian movement in high density crowd areas. Its effectiveness might not be achieved without understanding factors that may affect pedestrian’s traffic flow.