• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1361-1369
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• 2008

The analysis of software reliability model provides the means to analysts, software engineers, and systems analysts and developers who want to predict, estimate, and measure failure rate of occurrences in software. In this paper, reliability growth model, in which the operating time between successive failure is a continuous random variable, is proposed. This model is based on order statistics of two parameters Burr type XII distribution. We propose the measure based on U-plot. Also the performance of the suggested model is tested on real data set.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.241-249
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• 2022

The current research attempts to measure the level of the acceptance of the Blackboard System (BBS) during the Corona crisis, and whether this is one of the reasons for the low use of the BBS at Al-Jouf University. To achieve this, the technology accepting model in the time of crisis (TAMTC) has been proposed to measure the degree of acceptance by students, which was then applied to a random sample of 339 of such. The results show a high level of student acceptance, despite their lower use of the system. The research also highlights the importance of upgrading e-courses and that the discontinuation of exam disqualification of students is secondary to their poor course attendance.

• Proceedings of the Korean Reliability Society Conference
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• 2001.06a
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• pp.301-310
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• 2001

Lim et al.(1998) proposed the Bayesian Imperfect Repair Model, in which a failed system is perfectly repaired with probability P and is minimally repaired with probability 1 - P, where P is not fixed but a random variable with a prior distribution II(p). In this note, the steady state availability of the model is derived and the measure is obtained for several particular prior distribution functions.

• Journal of applied mathematics & informatics
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• v.35 no.5_6
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• pp.651-657
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• 2017

A sequence {$X_n,\;n{\geq}1$} of independent and identically distributed random variables with absolutely continuous (with respect to Lebesque measure) cumulative distribution function F(x) is considered. We obtain two characterizations of a family of continuous probability distribution by independence property of record values.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.370-373
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• 2006

In this paper, we consider set-valued aggregation operators and investigate some properties of them. Moreover, we define interval-valued Choquet integral aggregation operators and discuss their characterizations.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.201-212
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• 1998

In the present paper we define the codes which assign D-alphabet one-one codeword to each outcome of a random variable and the functions which represent possible transormations from one-one codes of size D to suitable codes. By using these functions we obtain lower bounds on the exponentiated mean codeword length for one-one codes in terms of the generalized entropy of order $\alpha$ and type $\beta$ and study the particular cases also.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.701-705
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• 2011

The paper reviews Cronbaha's coefficient to measure a single source of error. On the contrary to classical measurement theory, the generalizability study can be used in the social survey design to calculate Generalizability Index (GI) and Dependability Index (DI) for measuring multiple sources of errors of behavior evaluation. The study proposes application guidelines to implement R:($A{\times}B$) mixed models that are composed of random factor and fixed factor.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.2
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• pp.41-51
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• 1988

In this paper an efficient heuristic for the generalized assignment problem(GAP) is presented. A new lower bound that is slightly improved by adding the feasibility constraint is used to measure the quality of solutions obtained by the heuristic. The heuristic was tested on a number of large-scale random problems and a large sample of small problems. The heuristic appears to be better than the best previously existing heuristic for GAP. Its effectiveness in comparison of running times and closenesses to lower bound is discussed.

• Economic and Environmental Geology
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• v.33 no.4
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• pp.295-307
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• 2000

Probabilistic analysis is a powerful method to quantify variability and uncertainty common in engineering geology fields. In rock slope engineering, the uncertainty and variation may be in the form of scatter in orientations and geometries of discontinuities, and also test results. However, in the deterministic analysis, the factor of safety which is used to ensure stability of rock slopes, is based on the fixed representative values for each parameter without a consideration of the scattering in data. For comparison, in the probabilistic analysis, these discontinuity parameters are considered as random variables, and therefore, the reliability and probability theories are utilized to evaluate the possibility of slope failure. Therefore, in the probabilistic analysis, the factor of safety is considered as a random variable and replaced by the probability of failure to measure the level of slope stability. In this study, the stochastic properties of discontinuity parameters are evaluated and the stability of rock slope is analyzed based on the random properties of discontinuity parameters. Then, the results between the deterministic analysis and the probabilistic analysis are compared and the differences between the two analysis methods are explained.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.899-904
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• 2022

As the world becomes an aging society due to a decrease in the birth rate and an increase in life expectancy, a system for health management of the elderly population is needed. Among them, various studies on occupancy and activity types are being conducted for smart home care services for indoor health management. In this paper, we propose a random forest model that classifies activity type as well as occupancy status through indoor temperature and humidity, CO2, fine dust values and UWB radar positioning for smart home care service. The experiment measures indoor environment and occupant positioning data at 2-second intervals using three sensors that measure indoor temperature and humidity, CO2, and fine dust and two UWB radars. The measured data is divided into 80% training set data and 20% test set data after correcting outliers and missing values, and the random forest model is applied to evaluate the list of important variables, accuracy, sensitivity, and specificity.