• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of the Korean Applied Science and Technology
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• v.39 no.1
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• pp.115-131
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• 2022

The purpose of this study was to develop and examine the effect of the Health Promotion Education Program for the Auxiliary Police based on the PRECEDE-PROCEED Model. This study was conducted using a nonequivalent control group pretest-posttest design. Twenty-five participants were selected by convenience sampling method and assigned to the experimental group, and 26 participants were assigned to the control group. The data were collected from Auxiliary Police officer in D provincial Police Agency. All of participations completed questionnaires about self-efficacy, social support, availability of resources, health promotion behavior, quality of life and received the objective stress test. In addition, the experimental group completed 7 sessions of health promotion Education programs according to PRECEDE-PROCEED model for 5 weeks. Data were analyzed using the SPSS/WIN 21.0 Program. There was significant differences over time between the groups in terms of health promotion behavior (F=7.63, p<.001), autonomic nervous activity (F=29.24, p<.001), stress resistance (F=31.22, p<.001), stress index (F=22.42, p<.001), fatigue (F=12.87, p<.001), and quality of life (F=3.49, p=.042). The results may be crucial to develop strategy in order to decrease the disease prevalence as well as increase the participants' overall quality of life. As a result, the Health Promotion Education Program for the auxiliary police was proved to be an effective intervention in order to improve the quality of life. Therefore, the program may be a useful intervention for the auxiliary police.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.117-128
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• 2004

Compared with traditional face-to-face instruction, online learning causes learners to experience more severe feeling of isolation and results in higher dropout rate. This is due to the lack of interaction, sense of belonging, membership, interdependency, cooperation among members and social environment that enables persistence in online learning. Therefore, it is very important for grouping e-learning community to lower the dropout rate and eliminate feeling of isolation. In this paper, the research has been done on the inclination test list to be applied for grouping the desirable learning community. And on the basis of this research, the grouping system for e-learning community(GSE) based on intelligent multi agents for an inclination test using homogeneous and heterogeneous items has been developed. GSE system has such properties that construct a personalized user profile by an agent, and then make groupings according to users' inclination. When this system was evaluated, about 88% of learners were satisfied, and they wanted the group not to be disorganized but to be maintained.