• 제어로봇시스템학회논문지
• /
• 제18권8호
• /
• pp.725-730
• /
• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Computers and Concrete
• /
• 제13권2호
• /
• pp.271-290
• /
• 2014

In this study, structural irregularities in plan, which has a considerable effect on earthquake behavior of buildings, have been investigated in detail based on Turkish Earthquake Code 2007. The study consists of six main parametric models and a total of 144 sub-models that are grouped based on RC structural systems such as frame, frame + rigid core, frame with shear wall, and frame with shear wall + rigid core. All models are designed to have both symmetrical plan geometry and regular rigidity distribution. Changes in the earthquake behavior of buildings were evaluated according to the number of storeys, number of axes and the configuration of structural elements. Many findings are obtained and assessed as a result of the analysis for each structural irregularity. The study shows that structural irregularities can be observed in completely symmetric buildings in terms of plan geometry and rigidity distribution.

• 한국정보시스템학회지:정보시스템연구
• /
• 제28권2호
• /
• pp.93-107
• /
• 2019

Purpose The purpose of this study is to explain the mechanism of user behaviors in password reset context based on descriptive data from conducting interviews. Specifically, this study attempted to describe the process of changing password from the shadow work perspective. Design/methodology/approach This study has interviewed 8 participants who can freely use numerous online web-sites. This study also employed the grounded theory methodology to analyze interview manuscripts. After conducting analyzing the manuscripts, this study has extracted 46 codes in the coding steps and ultimately presented 8 categories by combining similar concepts from those codes. Findings According to the results, this study provides new viewpoints to explain unique user behavior in the password reset context by capturing the shadow work based on the results. This study further offers practical implications to numerous practitioners by finding various codes, which related to users' reaction and behavior.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제7권2호
• /
• pp.154-158
• /
• 2007

As the technology developed, the system is being developed as the structure that is adapted to the intelligent environment. Therefore, the existing situation information system couldn't provide satisfactory service to the user as it provides service only by the information which it received from the sensor. This paper analyzed the problems of the existing user intention awareness system and suggested user intention awareness system to provide a stable and efficient service that fits to the intention of the user compensating this. This paper has collected the behavior data based on the scenario of the sequential behavior course of the user that occurs at breakfast time in the kitchen which is the home domain environment thai is closely related to our lives. This scenario course also showed the flow that the goal intentional user intention awareness system acted that it suggested, and showed the sequential course processing the user behavior data by tables and charts.

• 정보보호학회논문지
• /
• 제10권3호
• /
• pp.11-28
• /
• 2000

In these days it is rapidly increasing that multi-user, multi-layered commercial software developments for companies or public institutions. Security services are necessary for most of systems and the access control service is the essential of security services. Current access control methods that are used as access control policies are classified as Discretionary Access Control Mandatory Access Control and Role Based Access Control. However there are some inefficiencies when those methods are applied to current multi-user, multi-layered systems. Therefore it is required that a new access control method that takes complex system resources into account from the side of policy. In this paper extending previous Role Based of 'Behavior' and a basic model of the method. And we simply implement the method on the mobile agent based workflow management system that is a representative example of multi-user. multi-layered softwares and shows implementation results to tap possibilities of real-world application.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.124-127
• /
• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• 한국정보시스템학회지:정보시스템연구
• /
• 제21권4호
• /
• pp.1-29
• /
• 2012

The purpose of this study was to find about personal information security of internet and social networks by focusing on end users. User competence and subjective criterion, which are the antecedents, are affecting security behaviors For these security behaviors, the study examined the relationship between security behavior intention on internet use and security behavior intention about social network that is actively achieved in many fields. Behaviors of internet and social network were classified into an action of executing security and an action of using a security technology. In addition, this study investigated a theory about motivational factors of personal intention on a certain behavior based on theory of reasoned action in order to achieve the purpose of this study. A survey was conducted on 224 general individual users through online and offline, and the collected data was analyzed with SPSS 12.0 and SmartPLS 2.0 to verify demographic characteristics of respondents, exploratory factor analysis, and suitability of a study model. Interesting results were shown that security behavior intention of social network is not significant in all security behavior execution, which is security performance behavior, and security technology use. Internet security behavior is significant to security technology use but it does not have an effect on behavior execution.

• Asia pacific journal of information systems
• /
• 제23권4호
• /
• pp.29-51
• /
• 2013

In line with network technology development and smart device penetration, the social network service (SNS) has expanded its influence. The SNS which is a service based on communication and sharing among people, has grown based on users' voluntary engagement and participation and its influence has appeared beyond the cyberspace into the overall areas of domestic and foreign culture and society. In particular, SNS-based real-time communication during diverse disasters, can help prevent further damage. By sharing information on social donation activities and environmental campaigns, people have used SNS as a tool to change the society in a more positive way. Such series of activities functioning as a power to change the society have been made much faster and wider through the help of a new media called SNS. To better understand such trends, we are required to study about the SNS and its user relationships first. In this context, this study sought to identify the effects of people's desire to build friendships through SNS on the voluntary and society-friendly activities of people. This study considers online pro-social behavior and proposes online citizenship behavior. Citizenship behavior has been examined in organization context. That is, organizational citizenship behavior explains an employee's pro-social behavior in an organization context. Organizational citizenship behavior is characterized by the individual's helping others and promoting the functioning of the organization. By applying organizational citizenship behavior to an online context, we propose online citizenship behavior, an individual's pro-social behavior in an online context. An individual's pro-social behavior, i.e., online citizenship behavior, could be considered as a way for the better management of online community and society. It also needs to examine the development of online citizenship behavior. This study examined online citizenship behavior from the friendship desire. Because online society or community is characterized by online relationships between members, the friendship between members would lead to pro-social behavior, i.e., helping others and promoting the functioning of the online society, in such online context. This study further examines the antecedents of friendship desire in terms of SNS interactivity with its four factors. The findings based on the survey from real SNS users explain that the three factors of SNS interactivity (connectivity, enjoyment, and synchronicity) increases online friendship desire which then increases online citizenship behavior significantly. This study contributes to the literature by examining the key role of online friendship desire in leading to online citizenship behavior and identifying its antecedents in terms of SNS characteristics. The findings in this study also provide guidance on how to manage online society and how to promote the effective functioning of SNS.

• 한국산업정보학회논문지
• /
• 제19권6호
• /
• pp.63-76
• /
• 2014

최근 많은 사람들이 스마트폰을 이용해 다양한 방법으로 원하는 정보를 추천 받고 있다. 그와 관련해 추천을 위한 많은 어플리케이션이 존재하지만, 현재 사용자 상황에 맞는 정보를 추천해 주는 것은 없다. 자동으로 사용자의 상황에 맞는 추천을 하기 위해서는 사용자의 과거 행위이력으로 부터 미래의 행위를 예측할 필요가 있다. 이에 본 논문에서는 스마트폰을 이용해 사용자의 현재 상황을 수집하고, 수집된 데이터를 라이프로그를 분석하여 구축한 베이지안 네트워크에 적용하여 현 행동을 판별한 후 연관분석을 통해 사용자가 미래에 하게 될 행동을 예측하는 방법을 제안한다. 5명의 실제 학생과 5명의 가상의 직장인에 대해서 실험 및 분석해 본 결과 그 유용성을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권6호
• /
• pp.2188-2203
• /
• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.