Lightweight Res-Connection Multi-Branch Network for Highly Accurate Crowd Counting and Localization

Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.

CCM-FL:Covert communication mechanisms for federated learning in crowd sensing IoT

The past decades have witnessed a wide application of federated learning in crowd sensing,to handle the numerous data collected by the sensors and provide the users with precise and customized services.Meanwhile,how to protect the private information of users in federated learning has become an important research topic.Compared with the differential privacy(DP)technique and secure multiparty computation(SMC)strategy,the covert communication mechanism in federated learning is more efficient and energy-saving in training the ma-chine learning models.In this paper,we study the covert communication problem for federated learning in crowd sensing Internet-of-Things networks.Different from the previous works about covert communication in federated learning,most of which are considered in a centralized framework and experimental-based,we firstly proposes a centralized covert communication mechanism for federated learning among n learning agents,the time complexity of which is O(log n),approximating to the optimal solution.Secondly,for the federated learning without parameter server,which is a harder case,we show that solving such a problem is NP-hard and prove the existence of a distributed covert communication mechanism with O(log logΔlog n)times,approximating to the optimal solution.Δis the maximum distance between any pair of learning agents.Theoretical analysis and nu-merical simulations are presented to show the performance of our covert communication mechanisms.We hope that our covert communication work can shed some light on how to protect the privacy of federated learning in crowd sensing from the view of communications.

A Game-Theoretic Approach to Safe Crowd Evacuation in Emergencies

Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, manyresearchers proposed game theoreticmodels to avoid and remove obstacles for crowd evacuation. Game theoreticalmodels aim to study and analyze the strategic behaviors of individuals within a crowd and their interactionsduring the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. Thesemodels consider a group of individuals as homogeneous objects with the same goals, involve complex mathematicalformulation, and cannot model real-world scenarios such as panic, environmental information, crowds that movedynamically, etc. The proposed work presents a game theoretic model integrating an agent-based model to removethe obstacles from exits. The proposed model considered the parameters named: (1) obstacle size, length, andwidth, (2) removal time, (3) evacuation time, (4) crowd density, (5) obstacle identification, and (6) route selection.The proposed work conducts various experiments considering different conditions, such as obstacle types, obstacleremoval, and several obstacles. Evaluation results show the proposed model’s effectiveness compared with existingliterature in reducing the overall evacuation time, cell selection, and obstacle removal. The study is potentially usefulfor public safety situations such as emergency evacuations during disasters and calamities.

A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

Deep Learning Based Efficient Crowd Counting System

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different events.It is challenging to determine the approximate crowd size from an image of the crowd’s density.Therefore in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the crowd.We employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s performance.To analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd counting.The results show the superiority of the proposed system.

Automated evaluation of parapapillary choroidal microvasculature in crowded optic discs:a controlled,optical coherence tomography angiography study

AIM:To compare superficial and deep vascular properties of optic discs between crowded discs and controls using optical coherence tomography angiography(OCT-A).METHODS:Thirty patients with crowded discs,and 47 control subjects were enrolled in the study.One eye of each individual was included and OCT-A scans of optic discs were obtained in a 4.5×4.5 mm^(2) rectangular area.Radial peripapillary capillary(RPC)density,peripapillary retinal nerve fiber layer(pRNFL)thickness,cup volume,rim area,disc area,cup-to-disc(c/d)area ratio,and vertical c/d ratio were obtained automatically using device software.Automated parapapillary choroidal microvasculature(PPCMv)density was calculated using MATLAB software.When the vertical c/d ratio of the optic disc was absent or small cup,it was considered as a crowded disc.RESULTS:The mean signal strength index of OCT-A images was similar between the crowded discs and control eyes(P=0.740).There was no difference in pRNFL between the two groups(P=0.102).There were no differences in RPC density in whole image(P=0.826)and peripapillary region(P=0.923),but inside disc RPC density was higher in crowded optic discs(P=0.003).The PPCMv density in the inner-hemisuperior region was also lower in crowded discs(P=0.026).The pRNFL thickness was positively correlated with peripapillary RPC density(r=0.498,P<0.001).The inside disc RPC density was negatively correlated with c/d area ratio(r=-0.341,P=0.002).CONCLUSION:The higher inside disc RPC density and lower inner-hemisuperior PPCMv density are found in eyes with crowded optic discs.

Design of Barrier-free Evacuation for Diverse Crowd on Campus Based on Evacuation Simulation: A Case Study of North China University of Technology

By using evacuation simulation technology and taking North China University of Technology as an example,the barrier-free evacuation design scheme for groups with different needs in campus environment was deeply discussed.Based on the data of building layout,population composition,road system and distribution of shelters in the school,a detailed evacuation model was constructed in the Pathfinder emergency evacuation simulation system.By the simulation during the daytime and at night,the total evacuation time of the whole school,evacuation completion time of each building,selection of evacuation paths and shelter utilization were analyzed in detail.The simulation results show that the distribution of shelters on campus is uneven,and their capacity is limited.As a result,the evacuation paths of the disabled,the elderly and children need to be adjusted frequently,which affects the overall evacuation efficiency.In view of this,the optimization strategies of road renovation and entrances of shelters and buildings were put forward from the perspective of space planning.From the perspective of emergency management,it is suggested to improve the campus evacuation infrastructure and strengthen the evacuation drill for teachers and students.These results provide a solid theoretical support for enhancing the construction of campus barrier-free environment and improving the level of emergency management.

基于时延的Flash Crowd控制模型

提出了一种session级别的flash crowd控制策略SGAC(session-granularity admission control),将session控制粒度和request控制粒度相结合,采用请求平均返回时延作为检测和控制的依据.对session采取一旦接受就完成的策略,在实现对服务器过载控制的同时,保护用户session的完整性,并能自动调节新session的准入速率,以提高服务器利用率.采用真实HTTP Log进行模拟,结果表明,SGAC方法能够有效控制服务器过载,保护session的完整性,提高服务器利用率,降低接入端路由器计算开销,保护有价值的交易session.

CrowdTracker:一种基于移动群智感知的目标跟踪方法

面向目标跟踪问题提出一种基于移动群智感知的解决方案CrowdTracker.不同于基于视频监控的目标跟踪方法,通过基于群智的多人协作拍照方式实现对移动目标的轨迹预测和跟踪,其优化目标为在保证准确实时地对目标进行跟踪的同时尽可能地减少用户激励的成本(假设激励与完成任务的参与者人数和参与者完成任务所移动的距离成正比).为实现该目标,提出了目标移动性预测的方法MPRE和任务分配的方法T-centric,P-centric.T-centric是以任务为中心的参与者选择方法,而P-centric是以人为中心的任务选择方法.MPRE通过分析大量的车辆历史轨迹建立城市里车辆的移动模型以预测目标下一步的位置.在预测的区域内通过T-centric或P-centric方法进行跟踪任务分配.通过一个大规模的真实数据集对移动性预测方法MPRE和2种任务分配算法进行实验评估,实验结果表明:CrowdTracker能有效地在实现目标实时跟踪的同时降低激励成本.

转发概率递减的改进Crowds系统

Crowds匿名浏览系统中可以在不影响匿名度水平的前提下,通过递减转发概率减小重路由路径长度,提高系统性能。提出利用路径长度期望值递减规律确定转发概率递减比例系数的方法,仿真实验表明,新方案可以在保持原有匿名度的基础上,有效减小重路由路径长度,提高Crowds系统的通信性能。

Crowds系统中新的前驱攻击模型研究

对前驱攻击模型攻击成功的概率和攻击轮数的原理和机制进行了详细的分析,在此基础上,提出了新的统计前驱攻击模型,该模型在每一轮重路由路径建立完毕后,对路径上所有泄密节点的直接前驱进行统计,减少了攻击的重建路径次数.仿真实验表明,与前驱攻击相比,新的统计前驱攻击可以有效地提高攻击的成功概率.

一种基于Crowds的改进匿名通信系统

提出一种基于Crowds的改进匿名通信系统,通过结合mix匿名通信技术和填充流量技术,使改进的匿名通信系统能抵御两种攻击.此外,对改进的匿名系统在前驱攻击下的匿名性能进行了分析,推导出改进系统在前驱攻击下能提供更好的匿名保护.

Translation and Comments on Bulrush in the Crowd

Nida’s functional equivalence enjoys a great popularity among translation theories,which plays an indispensable role in the practices of translation.Bulrush in the Crowds is a lyric prose cloaked in melancholy atmosphere.This prose is written in simple but lively,vivid language.It is also highly readable,with flexible structures and various writing techniques.Short and condensed casual sentences are widely employed in this prose.Furthermore,it is good at using figure of speech.Thus,when translation is conducted,mood,structure,style and rhetorical devices should be taken into consideration.

Guided Crowd Evacuation:Approaches and Challenges

Evacuation leaders and/or equipment provide route and exit information for people and guide them to the expected destinations, which could make crowd evacuation more efficient in case of emergency. The purpose of this paper is to provide an overview of recent advances in guided crowd evacuation. Different guided crowd evacuation approaches are classified according to guidance approaches and technologies. A comprehensive analysis and comparison of crowd evacuation with static signage, dynamic signage, trained leader, mobile devices, mobile robot and wireless sensor networks are presented based on a single guidance mode perspective. In addition, the different evacuation guidance systems that use high-tech means such as advanced intelligent monitoring techniques, AI techniques, computer technology and intelligent inducing algorithms are reviewed from a system’s perspective. Future researches in the area of crowd evacuation are also discussed.

Discrete element crowd model for pedestrian evacuation through an exit

A series of accidents caused by crowds within the last decades evoked a lot of scientific interest in modeling the movement of pedestrian crowds. Based on the discrete element method, a granular dynamic model, in which the human body is simplified as a self-driven sphere, is proposed to simulate the characteristics of crowd flow through an exit. In this model, the repulsive force among people is considered to have an anisotropic feature, and the physical contact force due to body deformation is quantified by the Hertz contact model. The movement of the human body is simulated by applying the second Newton＇s law. The crowd flow through an exit at different desired velocities is studied and simulation results indicated that crowd flow exhibits three distinct states, i.e., smooth state, transition state and phase separation state. In the simulation, the clogging phenomenon occurs more easily when the desired velocity is high and the exit may as a result be totally blocked at a desired velocity of 1.6 m/s or above, leading to faster-to-frozen effect.

PERSISTENCE AND THE GLOBAL DYNAMICS OF THE POSITIVE SOLUTIONS FOR A RATIODEPENDENT PREDATOR-PREY SYSTEM WITH A CROWDING TERM IN THE PREY EQUATION

This paper deals with the global dynamical behaviors of the positive solutions for a parabolic type ratio-dependent predator-prey system with a crowding term in the prey equation, where it is assumed that the coefficient of the functional response is less than the coefficient of the intrinsic growth rates of the prey species. We demonstrated some special dynamical behaviors of the positive solutions of this system which the persistence of the coexistence of two species can be obtained when the crowding region in the prey equation only is designed suitably. Furthermore, we can obtain that under some conditions, the unique positive steady state solution of the system is globally asymptotically stable.

Covalent Assembly of Penicillin Acylase in Mesoporous Silica Based on Macromolecular Crowding Theory

To improve the covalent immobilization of penicillin acylase （PA）, macromolecular crowding theory was applied to its immobilization. Influence of mass ratio of enzyme to the silica, as well as, activation time with glutaraldehyde on the activity of assembled PA, was studied. In the mesopores, the effect of fl-cyclodextrin （β-CD） on the immobilization of the enzyme was also investigated. It was remarkable that the coupled yield and relative activity reached 99.5% and 92.3%, respectively, when penicillin acylase assembled covalently in the mesopores. The results here indicate that mimicked macromolecule crowding could significantly ameliorate the performance of covalently immobilized PA.

GLOBAL OPTIMIZATION OF PUMP CONFIGURATION PROBLEM USING EXTENDED CROWDING GENETIC ALGORITHM

An extended crowding genetic algorithm (ECGA) is introduced for solvingoptimal pump configuration problem, which was presented by T. Westerlund in 1994. This problem hasbeen found to be non-convex, and the objective function contained several local optima and globaloptimality could not be ensured by all the traditional MINLP optimization method. The concepts ofspecies conserving and composite encoding are introduced to crowding genetic algorithm (CGA) formaintain the diversity of population more effectively and coping with the continuous and/or discretevariables in MINLP problem. The solution of three-levels pump configuration got from DICOPT++software (OA algorithm) is also given. By comparing with the solutions obtained from DICOPT++, ECPmethod, and MIN-MIN method, the ECGA algorithm proved to be very effective in finding the globaloptimal solution of multi-levels pump configuration via using the problem-specific information.

Effects of Shape of Crowders on Dynamics of a Polymer Chain Closure

Using 3D Langevin dynamics simulations, we investigate the effects of the shape of crowders on the dynamics of a polymer chain closure. The chain closure in spherical crowders is dominated by the increased medium viscosity so that it gets slower with the increasing volume fraction of crowders. By contrast, the dynamics of chain closure becomes very complicated with increasing volume fraction of crowders in spherocylindrical crowders. Notably, the mean closure time is found to have a dramatic decrease at a range of volume fraction of crowders 0.36-0.44. We then elucidate that an isotropic to nematic transition of spherocylindrical crowders at this range of volume fraction of crowders is responsible for the unexpected dramatic decrease in the mean closure time.

Flash Crowd与DDoS攻击区分方法研究综述

由于Web服务器的DDoS攻击行为与Flash Crowd非常接近,Flash Crowd与DDoS攻击的区分问题成为网络安全领域新的研究热点。首先概述了Flash Crowd的基本概念与分类,比较了Flash Crowd与DDoS攻击的相似性与差异性;随后详细介绍了目前区分Flash Crowd与DDoS攻击的3类方法:基于流量特征的方法、基于用户行为的方法和基于主机测试的方法;然后介绍了几个目前使用最广泛的数据集;最后对该领域的研究方向进行了预测。