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

• 한국정보시스템학회지:정보시스템연구
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• 제16권4호
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• pp.157-176
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• 2007

Most of the Information Systems(IS) literature has focused on utilitarian or hedonic Information Technology(IT) to explain and predict IT adoption and use. This study investigates the relationships among individuals' beliefs and intention to use of movie website, which has both utilitarian and hedonic characteristics simultaneously. As a theoretical background, this study adopts Technology Acceptance Model(TAM) and Motivation Theory, in which the former is well-known as a theory of IT adoption and use in IS field, and the latter is famous for a theory of individual's behavior in organizational behavior field. With 153 responses, five hypotheses are tested by using structured equation model. The results show that perceived ease of use positively influences perceived usefulness and perceived enjoyment, and that all individuals' beliefs have a positive impact on intention to use of movie web-site. Based upon the study results, movie website's managers and professionals can plan and conduct their courses of action effectively for users' continuous visits on their operating website.

• Asia pacific journal of information systems
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• 제12권1호
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• pp.67-85
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• 2002

This study attempts (1) to analyze the changing pattern of organizational control by investigating the impacts of ERP implementations on the determinants of organizational control types and (2) to compare the performance variances based on the fitness between implementation of ERP and the changed mode of organizational control. Research results reveal that firms with ERP shows high degree of information integration, which partially affects the determinants of organizational control types. Also, results indicate that firms now with ERP shows the higher levels of both behavior and output control than without ERP, and the magnitude of change in behavior control level was greater than that of output control level. Finally, this research suggests that while the firms that implemented ERP for the purpose of quality and service improvement need to more focus on behavior control than on output control, the firms for the purpose of cost reduction need to excercise more output control in order to establish a cost effective control strategy.

• Asia pacific journal of information systems
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• 제28권2호
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• pp.133-153
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• 2018

This study investigates responses to privacy concerns by analyzing the psychological and behavioral characteristics related to the disposition toward invoices of courier service users. To this end, we develop a theoretical framework by combining stimulus response theory, communication privacy management theory, the theory of reasoned action, and the theory of planned behavior. Based on the theoretical framework, we analyze the relationships between social influence, privacy propensity, privacy control, privacy risk, privacy concern, invoice disposition intention, and invoice disposition behavior in the context of courier services. To test our hypotheses, we survey courier service users in the U.S. and Korea. Using a structural equation model, we test the relationships among these various factors for the courier service users of the two countries. Results have distinct implications for the psychological and behavioral characteristics concerning the disposal of courier invoices and enable understanding of the characteristics of courier service customers of the two countries.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.897-907
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• 2020

The development of information technology and the demands of society on an application in an operating system, as well as increasing the specifications and sophistication of smartphones, require banks to make changes to their mobile banking applications. The transformation of the mobile banking application into a digital banking application conducted by banks has made users re-evaluate based on their preferences. This study presents the behavior of users of digital banking applications in Yogyakarta, Indonesia. The hypothesis model is based on Technology Acceptance Model (TAM) with additional factors of the social image, perceived risk and perceived trust adopted from Muñoz-Leiva et al. (2017). The methodology in this study includes data collection through questionnaires distributed online and data analysis using the Structural Equation Model. The results of this study illustrate that the perceived trust and perceived risk have a more dominant part in influencing user attitude and user intention to use digital banking. Meanwhile, social image, perceived ease-of-use and perceived usefulness are not significant in influencing user attitude and user intention to use digital banking. The implication of this research helps to determine the right communication and strategy so that more users with more benefits can utilize this digital banking application.

• Steel and Composite Structures
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• 제26권3호
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• pp.361-373
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• 2018

This paper presents the development of finite element (FE) models to simulate the behavior of diagonally stiffened steel plate shear wall systems (SPSWs) with differently shaped openings subjected to a cyclic load. This walling system has the potential to be used for shear elements that resist lateral loads in steel-framed buildings. A number of $\text\tiny{^1/_2}$-scale one-story buildings that were un-stiffened, stiffened and stiffened with opening SPSWs are modeled and simulated using the finite element method based on experimental data from previous research. After validating the finite element (FE) models, the effects of infill plate thickness on the cyclic behavior of steel shear walls are investigated. Furthermore, triple diagonal stiffeners are added to the steel infill plates of the SPSWs, and the effects are studied. Moreover, the effects of a number of differently shaped openings applied to the infill plate are studied. The results indicate that the bearing capacity and shear resistance are affected positively by increasing the infill plate thickness and by adding triple diagonal stiffeners. In addition, the cyclic behavior of SPSWs is improved, even with an opening in the SPSWs.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.485-486
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• 2019

Simulated driving behavior is an important aspect of realistic simulation systems. To simulate natural driving behavior, this paper proposes an imitation learning method based on active learning that combines demonstration and experience. Driving demonstrations are collected from human drivers in a driving simulator. A driving behavior policy is learned from these demonstrations. The driving demonstration dataset is augmented with new demonstrations that the original demonstrations did not contain, in the form of behaviors from another driving behavior policy learned from experience. The final driving behavior policy is learned from an augmented demonstration dataset.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1177-1180
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• 1996

In this paper, we propose an algorithm that realizes cooperative behavior by construction of autonomous mobile robot system. Each robot is able to sense other robots and obstacles, and it has the rule of behavior to achieve the goal of the system. In this paper, to improve performance of the whole system, we use Genetic Programming based on Natural Selection. Genetic Programming's chromosome is a program of tree structure and it's major operators are crossover and mutation. We verify the effectiveness of the proposed scheme from the several examples.

• 제어로봇시스템학회논문지
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• 제10권5호
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.57-76
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• 2020

Purpose Although examining the antecedents of employees' extra-role behavior (i.e. information security participation behavior) in the information security context is significant for researchers and practitioners, most behavioral security studies have focused on employees' in-role behavior (i.e. information security policy compliance). Thus, this research addresses this gap by investigating how organizational information security climate influences information security participation behavior based on social information processing theory and Griffin and Neal's safety model. Design/methodology/approach We developed a research model by applying Griffin and Neal's safety model to the information security context and then tested our research model by conducting an online survey for employees of organizations with information security policies. Structural equation modeling (SEM) with SmartPLS 3.3.2 is used to test the corresponding hypothesis. Findings Our results show that organizational information security climate, information security knowledge, information security motivation are effective in motivating information security participation behavior. Also, we find that organizational information security climate positively influences both information security knowledge and information security motivation. Our findings emphasize the importance of organizational information security climate because it is capable of affecting employees on information security participation behavior. Our study contributes to the literature on information security by exploring the role of organizational information security climate in enhancing employees' information security participation behavior.