• Journal of Internet Computing and Services
• /
• v.11 no.2
• /
• pp.73-84
• /
• 2010

Rapid development of Internet has increased users' desire for more information, and as a result, it created 'deluge of information', generating so much information. Especially, profit-pursuing corporations have done a lot of research to secure its own technological power. However, damages caused by illegal copy of information by illegal outside users or insiders are coming to the fore as social problem. Therefore, this paper is to propose secure knowledge management system to prevent illegal copy of data by insiders. The proposed scheme is a secure knowledge management system that carries out explicit authentication for internal users using 2MAC and provides data based on the authentication, thereby preventing illegal copy of data by insiders.

• Journal of Preventive Medicine and Public Health
• /
• v.53 no.3
• /
• pp.180-188
• /
• 2020

Objectives: The Short Form 36 (SF-36) questionnaire is increasingly being used to measure health-related quality of life (HRQoL) in Indonesia. However, evidence that it is valid for use in Indonesian adults is lacking. This study assessed the validity and reliability of the SF-36 in Indonesian middle-aged and older adults. Methods: Adults aged 46-81 years (n=206) in Yogyakarta, Indonesia completed the SF-36, another measure of HRQoL (the EuroQoL visual analogue scale [EQ-VAS]), and measures assessing their demographic characteristics. Fifty-four percent (n=121) completed the SF-36 measure again 1 week later. Confirmatory factor analysis was conducted to confirm the factor structure of the SF-36. Internal consistency reliability was estimated using Cronbach's alpha, and test-retest reliability was assessed using intraclass correlations. Convergent and discriminant validity were assessed by computing correlations among SF-36 subscales, between subscales and the 2 component scores, and between component scores and EQ-VAS scores. Results: Most scaling assumptions were met. The hypothetical factor structure fit the data poorly (root mean square error of approximation [RMSEA]=0.108) and modification was required for a good fit (RMSEA=0.060). Scores on all subscales demonstrated acceptable internal consistency (α>0.70) and test-retest reliability (r>0.70). Divergent validity was supported by weak to moderate interscale correlations (r=0.19 to 0.64). As expected, the 2 summary scores were moderately to strongly correlated with the EQ-VAS (r>0.60). Conclusions: The findings adequately support the use of SF-36 in Indonesian middle-aged and older adults, although the optimal algorithm for computing component scores in Indonesia warrants further investigation.

• Journal of the Korea Society for Simulation
• /
• v.26 no.2
• /
• pp.9-17
• /
• 2017

The problem of social phenomenon is getting more complicated than past decades, and the simulation engineers need more computation power to solve the problem. Therefore, the needs of the computational resources of the modeling and simulation environment are increasing. In the perspective of the simulation, it is necessary to allocate computational resources flexibly so that the simulation can be performed per the available budget range. As an alternative to the simulation environment to accommodate these requirements, cloud service has emerged as an environment in which computing resources can be used flexibly. This paper proposes a web-based simulation framework which consists of a front-end that reconstructs the simulation model using the web, and a back-end that executes the discrete event simulation. This paper also carried out a case study which shows web-based simulation framework has better overall runtime than standalone simulation framework.

• Journal of the Korean Society of Safety
• /
• v.28 no.1
• /
• pp.158-163
• /
• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.135-143
• /
• 2022

As the world has implemented social distancing and telecommuting due to the spread of COVID-19, real-time streaming sessions based on routing protocols have increased dependence on the Internet due to the activation of video and voice-related content services and cloud computing. BGP is the most widely used routing protocol, and although many studies continue to improve security, there is a lack of visual analysis to determine the real-time nature of analysis and the mis-detection of algorithms. In this paper, we analyze BGP data, which are powdered as normal and abnormal, on a real-world basis, using an anomaly detection algorithm that combines statistical and post-processing statistical techniques with Rule-based techniques. In addition, we present an interactive spatio-temporal analysis plan as an intuitive visualization plan and analysis result of the algorithm with a map and Sankey Chart-based visualization technique.

• International Journal of Computer Science & Network Security
• /
• v.23 no.2
• /
• pp.203-209
• /
• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.34 no.5
• /
• pp.301-308
• /
• 2021

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.

• Journal of Industrial Convergence
• /
• v.20 no.5
• /
• pp.83-92
• /
• 2022

As cases of social and ethical problems caused by artificial intelligence technology have occurred, artificial intelligence ethics are drawing attention along with social interest in the risks and side effects of artificial intelligence. Artificial intelligence ethics should not just be known and felt, but should be actionable and practiced. Therefore, this study proposes an artificial intelligence ethics education model to strengthen the practical ability of artificial intelligence ethics. The artificial intelligence ethics education model derived educational goals and problem-solving processes using artificial intelligence through existing research analysis, applied teaching and learning methods to strengthen practical skills, and compared and analyzed the existing artificial intelligence education model. The artificial intelligence ethics education model proposed in this paper aims to cultivate computing thinking skills and strengthen the practical ability of artificial intelligence ethics. To this end, the problem-solving process using artificial intelligence was presented in six stages, and artificial intelligence ethical factors reflecting the characteristics of artificial intelligence were derived and applied to the problem-solving process. In addition, it was designed to unconsciously check the ethical standards of artificial intelligence through preand post-evaluation of artificial intelligence ethics and apply learner-centered education and learning methods to make learners' ethical practices a habit. The artificial intelligence ethics education model developed through this study is expected to be artificial intelligence education that leads to practice by developing computing thinking skills.

• Journal of Intelligence and Information Systems
• /
• v.13 no.3
• /
• pp.119-140
• /
• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

• Journal of Technology Innovation
• /
• v.23 no.1
• /
• pp.1-36
• /
• 2015

The purpose of this research is to find individual user's preference for cloud storage service such as Daum Cloud, Naver N-Drive, GoogleDrive, Dropbox, SkyDrive and iCloud. Through literature reviewed and pilot tests, 6 attributes of cloud storage service (storage capacity, perceived cost, collaboration, accessibility, social influence and perceived security) were selected and all 6 attributes had significant effects on the preference of cloud storage service by conjoint analysis. The results shows that the user's willingness to pay is estimated 10,553 won for the free storage, 4,646 won for the function for mobile accessibility, and 2,443 won for more reliable cloud computing service provider. This study has significance to apply conjoint analysis with economic, technological, and environmental factors to cloud storage service (SaaS) and shed light on policy promotion of next generation of cloud computing ecosystem by user perception with willingness to pay on the storage service.