Applicability and Behavior Patterns of Road Space from the Perspective of Young Women:A Case Study of Wangjing South Station

In order to understand the travel characteristics and behavior patterns of women in Wangjing area and explore whether the existing situation can meet women's needs for the use of street space,the area around Wangjing South Station of Metro Line 14 was taken as an example for analysis and research.Wangjing area was classified to the following six use attributes:company enterprise,transportation hub,education and culture,residential area,municipal facilities,leisure and entertainment.The proportion of each use attribute was evaluated according to four levels:A 25%and above(including 25%),B 15%-25%,C 15%-5%,D 5%and below(including 5%).Finally,whether the plot had composite functions was judged,and the spatio-temporal laws and behavior patterns of surrounding women were analyzed from the perspectives of time and space.

Tourist behavior patterns in the ecotourism destination in the west of China: A case study of Gannan Tibetan Autonomous Prefecture

This study takes Gannan Tibetan Autonomous Prefecture as the place of case study and tourists as research objects. From the perspectives of geographical distribution of source tourist markets, Tourist activity behavioral and spatial patterns of Tourists, this study looks into the geographical structure of the source tourists and spatial patterns by geography. The analysis of 341 questionnaires on tourists shows that:(1) The tourism cycle of Gannan is in the development phase, competing with adjacent Aba, and greatly impacted by the substitution effect and shadow effect of Aba.(2) The spatial distribution of tourist sources is concentrated, indicating that Gannan is a regional tourism destination. The temporal distance of tourists is mainly concentrated within the 6-hour traffi c circle.(3) Gannan Tibetan Autonomous Prefecture has already become the composite tourist destination dominated by leisure vacation. The minority folkcustom and special landscape are the most attractive tourism resources. Due to the impact of man-land harmonious lifestyle in the tourist areas, the environmental attitude of tourists is improved, and the transportation and shopping are the most vulnerable links in tourism service in Gannan Tibetan Autonomous Prefecture.(4) The spatial behavior of tourists in Gannan is mainly of single-destination style(52%), Transit leg and circle tour style(7%) as well as circle tour style(41%). The spatial distribution of tourist fl ow in Gannan shows a signifi cant feature "more in the north, less in the south and dependent on National Road". Tourism resources, transport facilities, regional competition and lack of route connecting different ecological units are important causes of the spatial distribution of self-help tourists.

Behavior pattern extraction by trajectory analysis

Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance （DTMD）, a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory＇s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.

Behavior pattern mining based on spatiotemporal trajectory multidimensional information fusion

Trajectory data mining is widely used in military and civil applications,such as early warning and surveillance system,intelligent traffic system and so on.Through trajectory similarity measurement and clustering,target behavior patterns can be found from massive spatiotemporal trajectory data.In order to mine frequent behaviors of targets from complex historical trajectory data,a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper.Firstly,spatial–temporal Hausdorff distance is pro-posed to measure multidimensional information differences of spatiotemporal trajectories,which can distinguish the behaviors with similar location but different course and velocity.On this basis,by combining the idea of k-nearest neighbor and density peak clustering,a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribu-tion.Finally,we implement the proposed algorithm in simulated and radar measured trajectory data respectively.The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately com-pared to the existing methods,which has a good application prospect in intelligent monitoring tasks.

Database Search Behaviors: Insight from a Survey of Information Retrieval Practices

This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.

Investigating the Effect of Sidewalk Flooring on the Behavioral Pattern (Walking) of Citizens in Urban Spaces (Case Study: Vali asr St., Tehran)

The present study has evaluated the effect of architectural forms on the walking activity of citizens as a behavioral model in urban physical spaces.The research hypothesis claims that by designing purposeful and appropriate architectural forms,the behavior and actions of users in urban physical spaces can be to some extent,it designed or controlled,and that the pattern and domains of human behavior in urban streets are the result of the components of environmental quality that are included in the design of that street.The present theoretical proposition has been tested in two sequences from Valiasr Street in Tehran.At the theoretical level,the research method is descriptive-analytical and at the experimental level,it is a survey that has been done using the behavioral research method.The results show that the floor form and street form are the most influential architectural forms in urban physical spaces on the activity of users walking from space in the study sample.Also,some environmental factors have a direct effect on human reactions;The research findings show that people’s speed is directly related to the dimensions of sidewalk carpets and a person tries to take a step according to the senses he receives from the sidewalk flooring form and as a result his speed changes according to those forms.

Identification of Socio-Demographic, Behavioral Patterns and Their Relationship with HIV Status among Female Sex Workers

The prevalence of HIV in high risk population is influenced significantly the behavioral and sociodemographic characteristics. However, considering the complexity of behavior among female sex workers, the relationship between a particular behavioral pattern and the HIV status of this “at risk” population assumes significance. Data generated in a community-based cross-sectional study earlier carried out to assess the prevalence estimates, at district level, of HIV status in eight districts of State of Andhra Pradesh, India was used to carry out factor analysis to explore the role of demographic and behavioral pattern and their relationship with the HIV status among female sex workers. Data on 3083 female sex workers in the study revealed that there existed nine patterns among demographic and behavioral characteristics, which explained 62% of the total variation through factor analysis. Further, cluster analysis was performed to identify the groups of individuals having similar characteristics. Two of those clusters had sizeable numbers having similar characteristics. FSWs belonging to cluster 2 had significantly high risk factors compared with Cluster 1. The overall prevalence of HIV was 11.4% (10.6% in cluster 1 and 15.9% in cluster 2) among high risk population. There exists a strong relationship between behavioral patterns and HIV positive.

Mobile Robot Combination Autonomous Behavior Strategy to Inspect Hazardous Gases in Relatively Narrow Man–Machine Environment

Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.

A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior

With technology constantly becoming present in people’s lives, smart homes are increasing in popularity. A smart home system controls lighting, temperature, security camera systems, and appliances. These devices and sensors are connected to the internet, and these devices can easily become the target of attacks. To mitigate the risk of using smart home devices, the security and privacy thereof must be artificially smart so they can adapt based on user behavior and environments. The security and privacy systems must accurately analyze all actions and predict future actions to protect the smart home system. We propose a Hybrid Intrusion Detection (HID) system using machine learning algorithms, including random forest, X gboost, decision tree, K -nearest neighbors, and misuse detection technique.

Driving Style Recognition Based on Driver Behavior Questionnaire

The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. The present study aims to research driver pattern and classification feature. Driver behavior self-reported investigation was conducted with standardized driver behavior questionnaire (DBQ) by 225 nonprofessional drivers on the internet in Beijing. Questionnaire’s reliability was verified by statistics analysis. Confirmatory factor analysis (CFA) was used to analyze the underlying factor structure. Speed advantage, space occupation, the contend right of way and the contend space advantage were extracted from the ques-tionnaire results to quantify driver characteristics. Based on fuzzy C-means (FCM) algorithm and taking the four factors as pattern features, the number of driver classification distribution was discussed. Then the number of driver classification was determined by statistical indices. The comparison of classification results with the survey finding on whether the driver occurred in traffic accidents within five years shows that the classification result is the same as the actual driving conditions. Finally, correlation between the demographic and types of driving behavior has been analyzed. Female were more likely than male to careful driving, and the older the driver and the less driving experience, the more careful and moderate driving behavior is.

Analysis of deformation and internal flow patterns for rising single bubbles in different liquids

Gas–liquid multiphase flow is a significant phenomenon in chemical processes. The rising behaviors of single bubbles in the quiescent liquids have been investigated but the internal flow patterns and deformation rules of bubbles, which influence the mass transfer efficiency to a large extent, have received much less attention. In this paper, the volume of fluid method was used to calculate the bubble shapes, pressure, velocity distributions,and the flow patterns inside the bubbles. The rising behavior of the bubbles with four different initial diameters,i.e., 3 mm, 5 mm, 7 mm and 9 mm was investigated in four various liquids including water, 61.23% glycerol,86.73% glycerol and 100% glycerol. The results show that the liquid properties and bubble initial diameters have great impacts on bubble shapes. Moreover, flow patterns inside the bubbles with different initial diameters were analyzed and classified into three types under the condition of different bubble shapes. Three correlations for predicting the maximum internal circulation inside the bubbles in 86.73% glycerol were presented and the R-square values were all bigger than 0.98. Through analyzing the pressure and velocity distributions around the bubbles, four rules of bubble deformation were also obtained to explain and predict the shapes.

The Role of Beliefs, Perception, and Behavioral Patterns in the Evolution of Psychophysical Disorders

In accounts of the development and progression of psychophysical disorders such as Hereditary Spastic Paraplegia (HSP) and Facioscapulohumeral Muscular Dystrophy (FSHD), the role of beliefs, perceptions, and behavioral patterns has often been overlooked in favor of a genetically determinist paradigm. This paper explores the impact of NeuroPhysics Treatment (NPT) on patients with HSP and FSHD. Through a series of clinical case reports, I demonstrate how intensive four-day NPT sessions can lead to rapid restoration of lost functions, challenging the conventional view of these disorders. I hypothesize that, by modulating the patient’s perceptual and behavioral frameworks, NPT facilitates the emergence of healthier patterns, suggesting that environmental and psychological factors significantly influence the manifestation and management of these conditions. These findings indicate that the role of genetic inheritance may be overstated and that beliefs and perceptions could play a crucial role in the evolution of psychophysical disorders. The implications of this research extend beyond the traditional treatment paradigms, advocating for a more holistic approach that integrates the psychophysical dimensions of health and challenges the deterministic perspective of genetic inheritance.

Multifactorial study of mobile phone dependence in medical students: Relationship to health-related lifestyle, Type A behavior, and depressive state

We investigated factors contributing to mobile phone dependence. To 139 medical students, we administered a self-reporting questionnaire designed to evaluate mobile phone dependence, health-related lifestyle, patterns of behavior, and depressive state. Multivariate logistic regression analysis revealed that scores for poor health-related lifestyle, Type A behavior pattern, and presence of depression are independently associated with degree of mobile phone dependency. These findings suggest that persons with an unhealthy lifestyle, Type A behavior traits, or depression might benefit from mobile phone use guidance.

A Fast Multi-Pattern Matching Algorithm for Mining Big Network Data

The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.

基于用户画像的暖通空调智能调控

目前,建筑物中的暖通中央空调系统基本上是根据行业准则设置的,然而,多项研究表明,由于用户的偏好、姿态和需求各异,这种传统做法不太可能满足大多数用户的热量需求。为了更精准地满足用户热量需求,使得基于用户行为模式来针对性提高热舒适性成为可能。文中采用深度强化学习的方法实现智能化暖通空调智能送风策略,该策略能够根据环境和用户行为模式动态地确定最佳暖通空调设置(温度设置和送风设置),从而极大提高用户的热舒适度,同时,实验结果还表明该智能调控策略相比传统固定值控制策略具有一定的节能效果。

“潜水”还是“学习”:在线协作学习中“在线倾听”行为再审视

学习者“在线倾听”行为是一种复杂的社会化活动,是在线协作学习对话的前提和基础,但并未引起正视和积极理解。基于对话教学理论视角,研究采用滞后序列分析、内容分析、社会网络分析等研究方法,分析学习者“在线倾听”行为模式特征,及其对学习者认知过程、批判性思维和学习绩效的潜在影响。研究发现,学习者“在线倾听”行为是在线协作学习的常态行为,存在显著性差异,在时间结构上呈现周期性和阵发性;专注的“在线倾听”,高频次的回顾/反思倾听,有益于学习者高水平知识建构和批判性思维发展;高、低绩效学习者群体的“在线倾听”行为模式存在显著差异,高绩效组“在线倾听”行为更专注、行为路径更完整。这些发现为理解和解释数字教育场景下在线学习发生的内隐规律和内在机制提供理论支撑和实践参考。

Influence of Family Status on the Dietary Patterns and Nutritional Levels of Children

A diversity of socio economic and cultural factors contributes towards maintenance and changes in dietary patterns of people. Therefore People around the world have adapted different types of dietary patterns for their survival. Aim of this study was to investigate the most relevant factors influencing human dietary patterns. Sample for the study was selected by using the Stratified sampling technique, which consists of 390 families residing around the Abatenna estate, Bandarawela municipal council, Sri Lanka. Principal component analysis techniques and correlation analysis were employed to identify the most relevant factors which affect human dietary patterns. Results of the study indicate that socio economic conditions, monthly income, number of children in a family, dietary patterns and weight-related behaviors are highly co-related with each other. These findings suggest that education and awareness programs on nutrition should target low income groups to enhance their knowledge on dietary patterns.

两场局部冲突中黑客群落行为与动因研究

随着信息化的发展,网络空间与社会空间深度交融,黑客攻击呈现出频次高、破坏强、覆盖广和链条长的趋势。在俄乌冲突、巴以冲突的两场混合战争中,黑客组织的结构与行为更加多元、复杂并在时间、空间维度出现了新模式、新特征。黑客群体的组织严密、协同行动、媒介传播和精神干预等特征,对网络空间的安全保障、网络空间的有序治理构成了全新的威胁与挑战。通过分析网络空间价值冲突场域中不同黑客群落现象和行为动因,形成黑客团体的特征画像,进而探讨黑客群落的分化、实践与变迁动力学机制,并在黑客分化“选边站队”的历史实践中,研提对黑客风险控制与引导治理的启示建议。

基于信息知识信念行为模式的健康教育对脑梗死后遗症期患者失眠状况及生活质量的影响研究

目的研究基于信息知识信念行为模式的健康教育运用于脑梗死后遗症期患者中的价值。方法选择我院2020年6月-2021年9月纳入的脑梗死后遗症期患者94例,按随机数字表法分成两组各47例,研究组开展基于信息知识信念行为模式的健康教育,对照组实施常规健康教育,干预后评价两组依从性,干预前后测评两组睡眠质量、简易智力状态(MMSE)、运动功能(FMA)、神经功能缺损(NIHSS)、语言功能、生活质量(SF-36),比较两组干预结果。结果研究组依从性91.49%高出对照组72.34%(P<0.05)。干预前两组睡眠质量无差异(P>0.05),干预后研究组睡眠质量、睡眠时间、睡眠障碍、睡眠效率评分低于对照组(P<0.05)。干预前两组MMSE、FMA、NIHSS、语言功能无差异(P>0.05),干预后研究组MMSE、FMA、语言功能高出对照组,但NIHSS低于对照组(P<0.05)。干预前两组SF-36无差异(P>0.05),干预后研究组评分均高出对照组(P<0.05)。结论基于信息知识信念行为模式的健康教育效果更为显著,能够提升患者依从性,增强其认知能力以及语言功能,促进运动能力恢复,同时改善睡眠质量,生活质量明显提升。

Design of a Landscape Device for Children from the Perspective of Embodied Cognition in the New Era

In recent years,embodied cognition has ushered in a new research upsurge in the academic field,and has become a hot topic in the field of cognitive psychology.In this paper,from the perspective of embodied cognition,the interaction ways of a landscape device for children were discussed to achieve a more real and harmonious interaction between children and scenes.The research data of embodied cognition used by children was analyzed,and the drawbacks and breakthrough points of current landscape devices for children were discussed.The core characteristics of children’s growth period were extracted to establish children’s interaction model and summarize the interactive design methods of landscape devices for children.Embodied cognition has become the most intuitive way for children to know and understand the environment,and plays a pivotal role in children’s growth.Based on embodied cognition principle and interactive behavior mode,the interactive design of a landscape device for children was studied,and three interactive design modes,including simple and convenient interaction mode,multi-sensory interaction mode and game natural interaction mode were summarized.On the basis of this research,relevant design practice and research were carried out to bring a new vision to the design of children’s landscape.