The Research on E-mail Users' Behavior of Participating in Subjects Based on Social Network Analysis

The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.

Evaluation of Microblog Users’ Influence Based on PageRank and Users Behavior Analysis

This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and followed phenomenon of microblog users. Informed by the microblog user behavior analysis, the paper also addresses a model for calculating weights of users’ influence. It proposes a U-R model, using which we can evaluate users’ influence based on PageRank algorithms and analyzes user behaviors. In the U-R model, the effect of user behaviors is explored and PageRank is applied to evaluate the importance and the influence of every user in a microblog network by repeatedly iterating their own U-R value. The users’ influences in a microblog network can be ranked by the U-R value. Finally, the validity of U-R model is proved with a real-life numerical example.

User Behaviors Analysis in Website Identification Registration

Nowadays, an increasing number of web applications require identification registration. However, the behavior of website registration has not ever been thoroughly studied. We use the database provided by the Chinese Software Develop Net (CSDN) to provide a complete perspective on this research point. We concentrate on the following three aspects: complexity, correlation, and preference. From these analyses, we draw the following conclusions: firstly, a considerable number of users have not realized the importance of identification and are using very simple identifications that can be attacked very easily. Secondly, there is a strong complexity correlation among the three parts of identification. Thirdly, the top three passwords that users like are 123456789, 12345678 and 11111111, and the top three email providers that they prefer are NETEASE, qq and sina. Further, we provide some suggestions to improve the quality of user passwords.

User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

Evaluation of the seismic behavior of reinforced concrete structures with flat slab-column gravity frame and shear walls through nonlinear analysis methods

This paper presents an investigation of the seismic behavior of reinforced concrete(RC)structures in which shear walls are the main lateral load-resisting elements and the participation of flat slab floor systems is not considered in the seismic design procedure.In this regard,the behavior of six prototype structures(with different heights and plan layouts)is investigated through nonlinear static and time history analyses,implemented in the OpenSees platform.The results of the analyses are presented in terms of the behavior of the slab-column connections and their mode of failure at different loading stages.Moreover,the global response of the buildings is discussed in terms of some parameters,such as lateral overstrength due to the gravity flat slab-column frames.According to the nonlinear static analyses,in structures in which the slab-column connections were designed only for gravity loads,the slab-column connections exhibited a punching mode of failure even in the early stages of loading.However,the punching failure was eliminated in structures in which a minimum transverse reinforcement recommended in ACI 318(2019)was provided in the slabs at joint regions.Furthermore,despite neglecting the contribution of gravity flat slab-column frames in the lateral load resistance of the structures,a relatively significant overstrength was imposed on the structures by the gravity frames.

Corrosion behavior of 2A97 Al-Cu-Li alloys in different thermomechanical conditions by quasi-in-situ analysis

As a promising material in the aircraft industry,2A97 Al-Cu-Li alloy exhibits high corrosion susceptibility that may limit its application.In the present work,to illustrate the influences of precipitate and grain-stored energy on localized corrosion evolution in 2A97 Al-Cu-Li alloy,cold working and artificial aging were carried out to produce 2A97 Al-Cu-Li alloys under different thermomechanical conditions.Quasi-in-situ analysis,traditional immersion test and electrochemical measurement were then conducted to examine the corrosion behavior of 2A97 alloys.It is revealed that precipitate significantly affects Cu enrichment at corrosion fronts,which determines corrosion susceptibility of alloys,whereas grain-stored energy distribution is closely associated with localized corrosion propagation.It is also indicated that quasi-in-situ analysis exhibits a consistent corrosion evolution with traditional immersion tests,which is regarded as a proper method to explore localized corrosion mechanisms by providing local microstructural information with enhanced time and spatial resolutions.

Container Networking Performance Analysis for Large-Scale User Behavior Simulation

Accurately simulating large-scale user behavior is important to improve the similarity between the cyber range and the real network environment. The Linux Container provides a method to simulate the behavior of large-scale users under the constraints of limited physical resources. In a container-based virtualization environment, container networking is an important component. To evaluate the impact of different networking methods between the containers on the simulation performance, the typical container networking methods such as none, bridge, macvlan were analyzed, and the performance of different networking methods was evaluated according to the throughput and latency metrics. The experiments show that under the same physical resource constraints, the macvlan networking method has the best network performance, while the bridge method has the worst performance. This result provides a reference for selecting the appropriate networking method in the user behavior simulation process.

The Intersection of Privacy by Design and Behavioral Economics: Nudging Users towards Privacy-Friendly Choices

This paper conducts a comprehensive review of existing research on Privacy by Design (PbD) and behavioral economics, explores the intersection of Privacy by Design (PbD) and behavioral economics, and how designers can leverage “nudges” to encourage users towards privacy-friendly choices. We analyze the limitations of rational choice in the context of privacy decision-making and identify key opportunities for integrating behavioral economics into PbD. We propose a user-centered design framework for integrating behavioral economics into PbD, which includes strategies for simplifying complex choices, making privacy visible, providing feedback and control, and testing and iterating. Our analysis highlights the need for a more nuanced understanding of user behavior and decision-making in the context of privacy, and demonstrates the potential of behavioral economics to inform the design of more effective PbD solutions.

Full－range nonlinear analysis of fatigue behaviors of reinforced concrete structures by finite element method

The offshore reinforced concrete structures are always subject to cyclic load, such as wave load.In this paper a new finite element analysis model is developed to analyze the stress and strain state of reinforced concrete structures including offshore concrete structures, subject to any number of the cyclic load. On the basis of the anal ysis of the experimental data,this model simplifies the number of cycles-total cyclic strain curve of concrete as three straight line segments,and it is assumed that the stress-strain curves of different cycles in each segment are the same, thus the elastoplastic analysis is only needed for the first cycle of each segment, and the stress or strain corresponding to any number of cycles can be obtained by superposition of stress or strain obtained by the above e lastoplastic analysis based on the cyclic numbers in each segment.This model spends less computer time,and can obtain the stress and strain states of the structures after any number of cycles.The endochronic-damage and ideal offshore concrete platform subject to cyclic loading are experimented and analyzed by the finite element method based on the model proposed in this paper. The results between the experiment and the finite element analysis are in good agreement,which demonstrates the validity and accuracy of the proposed model.

User Behavior Traffic Analysis Using a Simplified Memory-Prediction Framework

As nearly half of the incidents in enterprise security have been triggered by insiders,it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software(malware)in real-time.Failing to do so may cause a serious loss of reputation as well as business.At the same time,modern network traffic has dynamic patterns,high complexity,and large volumes that make it more difficult to detect malware early.The ability to learn tasks sequentially is crucial to the development of artificial intelligence.Existing neurogenetic computation models with deep-learning techniques are able to detect complex patterns;however,the models have limitations,including catastrophic forgetfulness,and require intensive computational resources.As defense systems using deep-learning models require more time to learn new traffic patterns,they cannot perform fully online(on-the-fly)learning.Hence,an intelligent attack/malware detection system with on-the-fly learning capability is required.For this paper,a memory-prediction framework was adopted,and a simplified single cell assembled sequential hierarchical memory(s.SCASHM)model instead of the hierarchical temporal memory(HTM)model is proposed to speed up learning convergence to achieve onthe-fly learning.The s.SCASHM consists of a Single Neuronal Cell(SNC)model and a simplified Sequential Hierarchical Superset(SHS)platform.The s.SCASHMis implemented as the prediction engine of a user behavior analysis tool to detect insider attacks/anomalies.The experimental results show that the proposed memory model can predict users’traffic behavior with accuracy level ranging from 72%to 83%while performing on-the-fly learning.

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

Different types of pandemics that have appeared from time to time have changed many aspects of daily life.Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown.The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these applications.The manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming task.Therefore,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these apps.This research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning methods.To the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi Arabia.The findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app store.Different methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

Game analysis of building energy saving behaviors between government and developers

Information asymmetry phenomenon and the differences between the main body's earning targets,which are existing in the building energy saving field,have made the game behaviors of its economic activities become inevitable.There are strategies choice between government departments and the developers,when the building energy saving work is carried out under the government control.Based on the players based assumptions,the path of player's behavior strategy choices is analyzed,expected revenue models are established and mixed Nash equilibrium is obtained in this paper.Based on the analysis results,the incentive strategy enlightenment could be concluded that it is particularly important to design the scientific incentive system for developers to develop energy-saving buildings reasonably and for the government to implement effective control;the role of informal system in encouraging developers to develop energy-saving buildings should not be ignored.

User Behavior Path Analysis Based on Sales Data

With the rapid development of science and technology and the increasing popularity of the Internet,the number of network users is gradually expanding,and the behavior of network users is becoming more and more complex.Users’actual demand for resources on the network application platform is closely related to their historical behavior records.Therefore,it is very important to analyze the user behavior path conversion rate.Therefore,this paper analyses and studies user behavior path based on sales data.Through analyzing the user quality of the website as well as the user’s repurchase rate,repurchase rate and retention rate in the website,we can get some user habits and use the data to guide the website optimization.

Game Analysis on Heathcliff's Behaviors in the Wuthering Heights

Wuthering Heights was an extraordinary novel in the nineteenth century,for it is very different from other contemporary novels which are reconciled with the public opinion by presenting Victorian values and tastes.It depicts a story of strong love and extreme hatred.This paper used the game theory to analyse the behaviors of Heathcliff in the Wuthering Heights.Some basic strategies and game models were used to illustrate the choices of the characters.This paper can be divided into four parts.The introduction is to introduce the novel,the description of the research approach and the definition of basic theories.It emphasizes on the introduction of basic strategies and some game models which would be used for the later analysis.The second part is to discuss the formation of Heathcliff's dual personality and analyses its causes.Heathcliff was very cruel in his revenge,but he also has a tender side in love,that is the manifestation of his dual personality.The formation of his dual personality dates back to his childhood suffering,the abnormal family environment,the pressure from long labor and finally his only love—Catherine's betrayal.The third part focuses on discussing how his dual personality affects Heathcliff's choices in the game plays with others.His tender personality affected Heathcliff's choice when facing Catherine's betrayal.He could not choose a grim strategy to totally break up with her,but choose a Tit for Tat and to combine with her after a revenge.His cruel personality made him harm other people indifferently which hide the foreshadowing for his death.The conclusion summarizes the arguments of this paper.This paper analyses from the formation of Heathcliff's dual personality,and then analyzes how his dual personality affected his choices in the game plays with others.

Web users' language utilization behaviors in China

The paper focuses on the habits of China Web users' language utilization behaviors in accessing the Web. It also seeks to make a general study on the basic nature of language phenomenon with regard to digital accessing. A questionnaire survey was formulated and distributed online for these research purposes. There were 1,267 responses collected. The data were analyzed with descriptive statistics, Chi-square testing and contingency table analyses. Results revealed the following findings. Tagging has already played an important role in Web2.0 communication for China's Web users. China users rely greatly on all kinds of taxonomies in browsing and have also an awareness of them in effective searching. These imply that the classified languages in digital environment may aid Chinese Web users in a more satisfying manner. Highly subject-specific words, especially those from authorized tools, yielded better results in searching. Chinese users have high recognition for related terms. As to the demographic aspect, there is little difference between different genders in the utilization of information retrieval languages. Age may constitute a variable element to a certain degree. Educational background has a complex effect on language utilizations in searching. These research findings characterize China Web users' behaviors in digital information accessing. They also can be potentially valuable for the modeling and further refinement of digital accessing services.

Analysis and Guiding Strategy of Female College Students' Behaviors in the Webcast

With the rise of live webcasts,the phenomenon of female college students'live webcasts is worthy of attention.According to the present situation,female college students'behaviors of the live webcast are different because of the difference in subject attributes,and they have higher cognition degrees due to the effect of advertisement implantation.Thanks to the convenient means of live broadcast,the diversity of the motive of live broadcast,and the multi-dimensional content,they have higher participation.There are many hidden dangers because of weak supervision and management.The main problems are as follows:the content has a vulgar tendency,public opinion has out-of-control risk,competition has hidden violence,supervision has a“Vacuum zone”.To strengthen the education and guidance of female college students'live webcast behaviors,we should adhere to the valuable guidance and set up the correct network values.Meanwhile,we also need to strengthen the guidance of public opinions,purify the field of live broadcast public opinion,and improve media literacy to establish an excellent concept of network security,strengthen network supervision,and build a perfect system of live broadcast rules.

S^(2-) behaviors analysis in leaching SrS and precipitating high purity SrCO_3 by reduction-decomposition process

A new preparation method （reduction-decomposition process） for high purity SrCO3 was investigated, which mainly includes four processes: reduction, leaching, purification and precipitation. The affecting factors about S2- behaviors in leaching process and the effects of variables on purity and particle sizes distribution of SrCO3 were analyzed theoretically and practically. It is concluded that with the increase of temperature or decrease of pH value in leaching process, the strontium recovery increases, but SrS decomposes and hydrogen sulphide （H2S） gas discharges. The purity of SrCO3 is dependent on dissolution-recrystallization times, for example, the purity of （SrCO3） is as high as 99.97% when it is recrystallized three times. Besides, the solution concentration of Sr（OH）2 and flow rate of CO2 have important effects on particle size distribution of SrCO3 particles, especially, the particle sizes of （SrCO3） meanly distribute in 0.11.0 μm when the flow rate of CO2 is about 2 000 mL/min and other parameters are invariable.

Analysis of Eco-tourism Tourist Behavior and Potential Market in Taibai Mountain

This paper provided full and accurate material for Taibai Mountain eco-tourism and forecasted its potential market through investigating on the visitors of Taibai Mountain Nature Reserve and the surrounding forest parks eco-tourism tourist.By using Excel and mapping method,this study described the sample characteristics and tourist behavior.In addition,this paper also carried on descriptive statistics factorial analysis by using SPSS statistics software,analyzed the potential market according to tourists' characteristics of Taibai Mountain.The survey results showed that visitors of Taibai Mountain Nature Reserve mainly were middle-income young people,and the majority of tourists were with higher education.With the purpose of enjoying the scenery and relaxing,tourists were interested in natural ecological landscape of Taibai Mountain Nature Reserve.Tourists mainly came from Shaanxi Province and preferred to day trip,the travel route was single.There were a small number of tourists travelling for business,conference and medical treatment in Taibai Mountain Nature Reserve.According to the analysis,related countermeasures were given in this paper as the following:① Promoting activities should be focused on the big or medium cities in Shaanxi Province,such as Xi'an,Xianyang,Baoji,etc..Meanwhile,various means should be adopted to expand its influence and raise awareness around the provincial cities for attracting tourists.② Strengthening the infrastructure construction and improving comprehensive tourist reception capacity with the pursuit of the diversity of tourism resources,and create a good environment for the tourism market;③ Focusing on tourism product development;④ Protecting the ecological resources and developing ecotourism.

Sensitivity analysis for stochastic user equilibrium with elastic demand assignment model

This paper puts forward a rigorous approach for a sensitivity analysis of stochastic user equilibrium with the elastic demand （SUEED） model. First, proof is given for the existence of derivatives of output variables with respect to the perturbation parameters for the SUEED model. Then by taking advantage of the gradient-based method for sensitivity analysis of a general nonlinear program, detailed formulae are developed for calculating the derivatives of designed variables with respect to perturbation parameters at the equilibrium state of the SUEED model. This method is not only applicable for a sensitivity analysis of the logit-type SUEED problem, but also for the probit-type SUEED problem. The application of the proposed method in a numerical example shows that the proposed method can be used to approximate the equilibrium link flow solutions for both logit-type SUEED and probit-type SUEED problems when small perturbations are introduced in the input parameters.

2011—2015年国际应用行为分析热点研究——以《Journal of Applied Behavior Analysis》为例

为了探究应用行为分析在国外的研究成果和动态,利用共词分析的原理对2011—2015年JABA刊文的关键词进行了分析,结果显示近五年国外应用行为分析研究热点有自闭症谱系障碍、功能分析、区别性强化、口语行为、进食障碍等。对这些热点进行分类,探讨了各领域所处的研究地位,最后提出我国学界不仅要加强应用行为分析在特殊儿童问题行为管理和干预中的运用,也要把它推广到其他领域。