• Title/Summary/Keyword: behavior-based systems

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An Empirical Study of the Effect of Uncertainty Avoidance on Post-Adoption Behavior: Focusing on Mobile Internet Services (불확실성 회피성향이 수용 후 행동에 미치는 영향: 모바일 인터넷 서비스를 중심으로)

  • Choi, Hun;Kim, Jin-Woo
    • Asia pacific journal of information systems
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    • v.16 no.3
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    • pp.95-116
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    • 2006
  • Although the study of post-adoption has increased in recent years, few studies have focused on the moderating effect of uncertainty avoidance on the relationship between post-expectation and behavior. The purpose of this study is to examine the moderating effect of uncertainty avoidance in the mobile Internet domains. This study proposed a post-adoption model based on prior continuance model. This theoretical model was verified empirically by conducting web surveys and multi-group analysis. Based on the survey data, we classified users into those with high uncertainty avoidance and those with low uncertainty avoidance. The results indicate that post expectations have significant impacts on satisfaction and continuance intention. The results also show that the impacts of intrinsic motivational factors of mobile Internet services on satisfaction and continuance intention are stronger for users with high uncertainty avoidance. On the other hand, the impacts of extrinsic motivational factors on satisfaction and continuance intention are stronger for users with low uncertainty avoidance, with a few exceptions. This paper ends with theoretical and managerial implications of the study results, as well as limitations and future research directions.

A System for Improving Data Leakage Detection based on Association Relationship between Data Leakage Patterns

  • Seo, Min-Ji;Kim, Myung-Ho
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.520-537
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    • 2019
  • This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

Linking Benefit/Cost, Negative Attitudes toward Shadow Work, and Consumer's Response Behavior (혜택/비용, 그림자 노동에 대한 부정적 태도, 반응행동 간 구조적 관계)

  • Liu, Ting Ting;Koh, Joon
    • The Journal of Information Systems
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    • v.30 no.2
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    • pp.79-103
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    • 2021
  • Purpose Based on consumers' economic, psychological, self-development and conversion costs, this study discusses the relationship between consumers' negative attitude to their shadow work during the course of using self-service in unmanned supermarkets and their behavior. Design/methodology/approach Along with the Hirschman(1970)'s EVLN(Exit, Voice, Loyalty, and Neglect) reviewed, the proposed model of this study is based on the S-O-R model(Mehrabian and Russel, 1974) and mental accounting theory(Thaler, 1999), having empirical validation. Findings In the process of visits and consumption in unmanned supermarkets, increasing economic and psychological benefits can effectively reduce consumers' negative attitudes towards shadow work. In addition, the increase in switching costs will also effectively reduce consumers' negative attitudes towards shadow work. When shadow work holds a negative attitude, all the three kinds of actions will occur. Unmanned supermarket operators use consumers to create value while giving a certain return to them, which is conducive to the sustainable development of unmanned supermarket enterprises.

BAYESIAN APPROACH TO MEAN TIME BETWEEN FAILURE USING THE MODULATED POWER LAW PROCESS

  • Na, Myung-Hwa;Kim, Moon-Ju;Ma, Lin
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.10 no.2
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    • pp.41-47
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    • 2006
  • The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

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Memory Behavior in Scientific vs. Commercial Applications

  • Kim, Taegyoun;Heejung Wang;Lee, Kangwoo
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.421-425
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    • 1999
  • As the market size of multiprocessor systems for commercial applications, parallel systems, especially cache-coherent shared-memory multiprocessors that are conventionally designed for scientific applications need to be tuned in different fashion to achieve the best performance for new application area. In this paper, indepth investigation on the memory behavior which is the primary cause for performance changes were made. We chose representative benchmarks in scientific and commercial application areas. After running execution-driven simulation for bus-based cache-coherent shared-memory multiprocessors, we experienced significant differences and conclude that the systems must be carefully and differently designed to achieve the best performance when they are built for distinct applications.

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Design Approach and Structural Analysis for Development of a Micro-Wear Tester (마이크로 마모 시험기 개발을 위한 설계 방안 및 구조 해석)

  • Yoo, Shin-Sung;Kim, Dae-Eun
    • Transactions of the Society of Information Storage Systems
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    • v.8 no.1
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    • pp.6-10
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    • 2012
  • The tribological behavior of microsystems needs to be clearly understood in order to improve the reliability of precision components. For example, friction and wear phenomena pose serious problems in MEMS applications. As a first step to investigate the tribological behavior of such systems, an appropriate testing system must be acquired. In this work, a micro-wear tester based MEMS platform was designed. The main concern was to achieve a desirable range of horizontal displacement for the specimen holder and also to apply a normal force in the tens of ${\mu}N$ range. The structural analysis of the micro-wear tester showed that the proposed design satisfied these requirements while maintaining the structural integrity.

A Biologically Inspired Intelligent PID Controller Tuning for AVR Systems

  • Kim Dong-Hwa;Cho Jae-Hoon
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.624-636
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    • 2006
  • This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

Computations of the Lyapunov exponents from time series

  • Kim, Dong-Seok;Park, Eun-Young
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.3
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    • pp.595-604
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    • 2012
  • In this article, we consider chaotic behavior happened in nonsmooth dynamical systems. To quantify such a behavior, a computation of Lyapunov exponents for chaotic orbits of a given nonsmooth dynamical system is focused. The Lyapunov exponent is a very important concept in chaotic theory, because this quantity measures the sensitive dependence on initial conditions in dynamical systems. Therefore, Lyapunov exponents can decide whether an orbit is chaos or not. To measure the sensitive dependence on initial conditions for nonsmooth dynamical systems, the calculation of Lyapunov exponent plays a key role, but in a theoretical point of view or based on the definition of Lyapunov exponents, Lyapunov exponents of nonsmooth orbit could not be calculated easily, because the Jacobian derivative at some point in the orbit may not exists. We use an algorithmic calculation method for computing Lyapunov exponents using time series for a two dimensional piecewise smooth dynamic system.

A Study on Customer Segmentation and Applications of e-mail System - Based on e-CRM - (e-CRM 관점에서 본 이메일 시스템의 고객분석 및 활용에 관한 연구)

  • Kim Yeon-Jeong
    • Journal of Korea Technology Innovation Society
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    • v.7 no.3
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    • pp.681-709
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    • 2004
  • The purpose of this study is to classify customers by e-mail responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems are adapted for Customer segmentations. ROI analysis are consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customers can be grouped into loyal customers, odds customers, dormant customers, secession customers, and observation customers by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mail systems were appropriate methods to group the customer with demographic variables. Therefore, effective e-mail marketing strategy of e-Biz should have suitable active DB and Behavior targeting is best approach to enforce the target e-mail marketing.

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Deep Learning and IoT Standards based High Rise Fieldworker's Behavior Analysis System (딥러닝과 IoT 표준을 이용한 고소 작업자 행동분석 시스템)

  • Lee, Se-hoon;Kang, Gun-ha;Sim, Gun-wu;Tak, Jin-hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.247-248
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    • 2019
  • 본 논문에서는 블루투스 비콘을 이용해 고소 작업장 등의 위험지역에서 작업자 추적 및 확인과 안전 벨트고리를 체결했는지 여부와 작업자의 행동에 따른 데이터를 추가로 수집하여 작업자의 행동 패턴을 분석하였다. IoT 국제 표준인 oneM2M을 기반으로 IoT Device와 Application을 연결하는 중간 매개체로 모비우스 플랫폼을 사용해 시스템을 구축하였다. 또한, 본 연구팀의 선행 연구에서 작업자 위험 행동분류 시스템을 개선할 수 있는 연구 결과를 비교하였다.

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