• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.115-123
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• 2024

The purpose of this study is to contribute to how the advantages of artificial intelligence (AI) services and the associated limitations can be simultaneously overcome, using the keywords AI and risk management. To achieve this, two cases were introduced: (1) presenting a risk monitoring process utilizing AI and (2) introducing an operational toolkit to minimize the emerging limitations in the development and operation of AI services. Through case analysis, the following implications are proposed. First, as AI services deeply influence our lives, the process are needed to minimize the emerging limitations. Second, for effective risk management monitoring using AI, priority should be given to obtaining suitable and reliable data. Third, to overcome the limitations arising in the development and operation of AI services, the application of a risk management process at each stage of the workflow, requiring continuous monitoring, is essential. This study is a research effort on approaches to minimize limitations provided by advancing artificial intelligence (AI). It can contribute to research on risk management in the future growth and development of the related market, examining ways to mitigate limitations posed by evolving AI technologies.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.109-115
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• 2024

This paper proposes an interference recognition-based resource allocation (IaRA) scheme for very high frequency (VHF) data exchange-terrestrial (VDE-TER) to ensure the reliability of automatic identification system (AIS) message transmission in a coastal environment with dense vessels. To this end, IaRA conducts channel selection and slot allocation based on scheduling information obtained through monitoring VHF data exchange system (VDES) channels. The simulation results show that IaRA achieved an 8.79% higher packet delivery ratio (PDR) and a 9.69% lower channel interference ratio (CIR) compared to the VDE-TER resource allocation scheme of the existing VDES standard.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.107-121
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• 2014

Distributed systems are collection of physically distributed computers linked by a network. General use of wired/wireless Internet enables users to make use of distributed service anytime and anywhere. The explosive growth of distributed services strongly requires functional verification of services as well as verification of non-functional elements such as service quality. In order to verify distributed services it is necessary to build a test environment for distributed systems. Because, however, distributed systems are composed of physically distributed nodes, efforts to construct a test environment are required more than those in a test environment for a monolithic system. In this paper we propose a test framework to verify functional and non-functional features of distributed systems. The suggested framework automatically generates test cases through the message sequence charts, and includes a test driver composed of the virtual nodes which can simulate the physically distributed nodes. The test result can be checked easily through the various graphs and the graphical user interface (GUI). The test framework can reduce testing efforts for a distributed system and can enhance the reliability of the system.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.77-87
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• 2021

With the development of the Internet and personal computers, various and complex attacks begin to emerge. As the attacks become more complex, signature-based detection become difficult. It leads to the research on behavior-based log anomaly detection. Recent work utilizes deep learning to learn the order and it shows good performance. Despite its good performance, it does not provide any explanation for prediction. The lack of explanation can occur difficulty of finding contamination of data or the vulnerability of the model itself. As a result, the users lose their reliability of the model. To address this problem, this work proposes an explainable log anomaly detection system. In this study, log parsing is the first to proceed. Afterward, sequential rules are extracted by Bayesian posterior probability. As a result, the "If condition then results, post-probability" type rule set is extracted. If the sample is matched to the ruleset, it is normal, otherwise, it is an anomaly. We utilize HDFS datasets for the experiment, resulting in F1score 92.7% in test dataset.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.10
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• pp.1607-1613
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• 2014

The purpose of this study was to investigate intake of protein supplements by university students majoring in physical education. Intake experience rate, reasons for intake, purchasing place, effectiveness, satisfaction level, and side effects were analyzed using a questionnaire. Of 476 students, those who consumed protein supplements were 198 (41.6%). Male's intake experience rate was significantly higher than that of females, and members of health-related clubs also consumed more protein than non-members. The main purchasing place was internet shopping malls, and users obtained information from their friends or upperclassmen. The most frequently consumed protein supplement was 'WPH', and the most frequent reason for intake was 'building muscle or maintaining body shape'. For effectiveness, 'normal' was 49.0% and 'effectiveness' was 33.3%. For satisfaction, 'satisfaction' was 45.5% and 'normal' was 43.4%. The rate of side effects was 44.9%, and digestive issues such as diarrhea and indigestion were observed with high frequency. The results of this study show that education is needed for nutritional knowledge, adequate intake, and side effects of protein supplements.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.1
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• pp.153-184
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• 2018

This study aims to investigate the effects of emotional labor level on the level of job satisfaction and library information service provision in public libraries. The research model used emotional labor levels as an independent variable; job satisfaction and level of library information service provision as a dependent variable; and organizational culture as a control factor. The data were collected randomly from 220 librarians of public libraries in Seoul by distributing and collecting internet surveys. Reliability analysis, correlation coefficient analysis, multiple regression analysis, and regression analysis were performed using the SPSS 18.0 program. The statistic hypothesis test results of this study can be summarized as follows. First, public library librarians did not like to express their emotions to users, trying to express their emotions more positively than what they were actually feeling. Second, although librarians experience emotional labors, they feel a sense of achievement when undertaking their tasks and develop pride and happiness in their work. As librarians perceive their work professional, they overcome emotional labors, and have pride in their work. Third, although librarians experience emotional labors, a reasonable job evaluation with goals, and their relationships with colleagues would lead to accomplishment in their work. In addition, although the evaluation of employees is focused on performance, librarians improve their service if library users are satisfied with their service and the services are provided adequately.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.65-71
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• 2019

Conventional methods of measuring ground resistance and ground resistance field measurement are used to measure voltage drop according to the resistance value of the site by applying current by installing a constant interval of measurement electrode. If the stratified structure of the site site is unique, errors in boundary conditions will occur in the event of back acid and the analysis of the critical ground resistance in the ground design will show much difference from simulation. This study utilizes the Arduino module and smart ground measurement technology in the convergent information and communication environment to develop a reliable smart land resistance measuring device even if the top layer of land is unique, to analyze the land resistance and accumulate data to predict the change in the age of the land. Considering the topographical characteristics of the site, we propose a ground resistance measuring device and its method of measuring ground resistance so that the auxiliary electrode can be installed by correctly positioning the angle and distance in measuring ground resistance. Not only is ground resistance value obtained through electrodes installed to allow accurate ground resistance values to be selected, but it can also be used as a useful material for installing electrical facilities in similar areas. Moreover, by utilizing reliable data and analyzing the large sections of the site, a precise analysis of the site, which is important in ground design as well as construction cost, is expected to be used much in ground facility design such as potential rise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.193-200
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• 2022

In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.

• Management & Information Systems Review
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• v.31 no.2
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• pp.143-172
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• 2012

While e-commerce market(B2C) grows rapidly, many experts argue that EC(B2C) transactions have not reached its full potential. A notable difference between online and offline consumer markets that is suppressing the growth of EC(B2C) is the decreased presence of human and social elements in the online shopping environments. Generally online shopping lacks human warmth and sociability. In this study, social presence in online shopping mall was proposed as a substitute for face-to-face social interaction in the traditional commerce and author explored what variables affect social presence(human warmth and sociability) on online shopping malls and how human warmth and sociability can influence on online store loyalty. To achieve research objectives, we reviewed literatures related with marketing, psychology and communication research areas. Based on literature review, we proposed a research model on the online shopping mall. To examine the proposed research model, we gathered data by using a self-report questionnaire. Respondents consists of online shoppers with at least five or more times of purchase experience in online shopping malls. Because social presence is a feeling which needs frequent contacts with malls to experience, respondents must have enough purchase experiences. The empirical results are as follows : First, shopping mall's customization efforts influence perceived social presence on the mall significantly. Second, shopping mall's responsiveness influences perceived social presence significantly. Third, perceived activity of community of online shopping mall influences perceived social presence significantly. Mall managers have to activate their customer community to reinforce social presence, resulting in trust building. Finally, perceived social presence influences trust and enjoyment on the mall significantly. And then trust and enjoyment on the mall affect store loyalty significantly. From these findings it can be inferred that perceived social presence appears determinant which is critical to the formation of core variables(trust and loyalty) in existing online shopping papers.