• 컴퓨터교육학회논문지
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• 제6권3호
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• pp.109-117
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• 2003

교육컨텐츠의 양적 팽창은 필연적으로 질적 개선에 대한 관심을 불러일으킨다. 양적으로 풍부한 컨텐츠가 존재하는 상황에서는 학습자들은 같은 인터넷 정보라도 질 높은 사이트를 찾고자 한 것이고, 개발자나 정보제공자는 이러한 수요에 부응하는 WBI를 제공하여야만 생존이 가능할 것이기 때문이다. 그럼에도 불구하고 많은 사이트들은 아직도 사용자의 입장에서 보다는 개발자 자신의 취향이나 시장논리에 의해서 컨텐츠를 제공하는 경우가 많다. 본 연구는 컨텐츠 개발시 질적 완성도가 높은 WBI를 개발하기 위한 방법의 하나로 Usability Test를 제안하고 그 유용성을 시험하기 위해 수행되었다. 이 과정에서 Usability Test를 위한 한 사례로서 <지층과 화석>이라는 컨텐트가 제작되었으며 그 제작 사례를 통해 WBI 완성도 향상을 위한 Usability Test 의 실천방안들이 논의 되었다.

• 디지털융복합연구
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• 제19권8호
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• pp.249-255
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• 2021

본 연구는 소프트웨어 시험성적서를 중심으로 국제표준에서 제시하고 있는 8가지 품질특성인 기능성, 신뢰성, 사용성, 유지보수성, 이식성, 효율성, 보안성, 상호운용성에 대한 가중치 결정 문제에 대한 방안을 제시했다. 현재는 소프트웨어 품질 평가에 대한 시험결과는 8가지 품질 특성을 동일한 가중치를 적용해서 산술평균을 구하고 있으나, 소프트웨어 품질 평가 점수는 제품의 특성에 따라 8가지 품질 특성을 구별하여 평가해야 한다는 점을 고려하여 소프트웨어 시험성적서의 결과를 중심으로 텍스트분석을 실시하였다. 텍스트분석을 통해서 나온 결과를 이용해서 8가지 품질 특성별 가중치를 적용하였으며, 두 개의 제품에 대한 시험성적서를 텍스트분석 한 결과를 이용해서 가중치를 적용하여 본 결과 가중치를 적용한 품질특성에 따른 시험성적서의 평균이 더 효율적이라는 것을 확인할 수 있었다.

• 물과 미래
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• 제29권2호
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• pp.179-190
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• 1996

한강하류부 수질의 통계학적 해석을 통하여 수질 시계열자료의 기본 통계특성치, 지점별 및 계절별 변동성을 검토하였으며, 유량과 수질인자간의 상관성 분석을 실시하였다. 본류의 주요 6개 지점 및 3개 지류에 대한 통계특성치와 적정분포형을 산정하여 제시하였으며, 시간의존성 및 계절성을 검토하여 제시하였다. 또한, 수질 항목간의 상관성 검토를 통하여 상관성이 높은 수질, 항목간, 그리고 지점간의 상관식을 제시하였다. 추계학적 모의모형의 적용가능성을 확인하였으며, DO 항목은 전 지점간에 높은 상관성을 가지고 있었다. 유량과의 상관관계 검토에 있어서 DO, SS 항목은 유량보다는 수온에 민감하였으며, BOD, COD 항목은 유량이 적은 갈수기에는 유량에 민감한 것으로 나타났다. 수온에 밀접한 영향을 받는 DO 항목외에도 BOD, COD 항목은 계절적인 주기성을 가지고 있었으며, 상호상관 분석결과 DO, BOD, COD 항목 외의 수질 항목들에서도 각 수질 항목들에 내재된 주기성을 찾아볼 수 있었다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2000년도 추계공동학술대회논문집
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• pp.265-283
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• 2000

Factors influencing the success or failure of information systems(IS) have been discussed in many literature. However, little theoretical development or empirical research has examined effectiveness of hospital information systems(HIS) This study set the research model of influencing factors and consequences of HIS through theoretical studies based on Management Information Systems, and then empirically tested several hypotheses related to this model. Based on a sample of 274 respondents who participated in dealing with the HIS, this research used a multiple regression analysis to test the research model. The results of this study are as follows: system quality, information quality and support of top management are statistically significant influence on user satisfaction. Service quality is a partially significant influence on user satisfaction. Hypothesis 5, proposing that computer self-efficacy would relate positively to user satisfaction, was not supported by the questionnaire results. Based on these results, system quality, information quality and support of top management are very important variables for IS success. And the study's findings indicate DeLone and McLean's model is correct in proposing that the indirect relationship between influencing factors and organizational effectiveness, mediated by user satisfaction, is an important one.

• 품질경영학회지
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• 제21권2호
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• pp.156-161
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• 1993

Limiting distributions of Studentized test statistics have been shown for testing the slope parameter in a simple linear structural model. Since the limiting distribution of Studentized one appears to yield inaccurate inference, this paper suggests adjustment of critical value and normalization of the Studentized one. As results, we can have procedures for refined inference based on our approximate distrbution instead of the limiting distribution.

• 품질경영학회지
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• 제21권1호
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• pp.108-120
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• 1993

In this article an economic life test sampling plan is considered for repairable products when the products in each lot have the same interfailure time distribution, but the mean time between failure (MTBF) of a lot varies from lot to lot according to a known prior distribution. A cost model is constructed which consists of test cost, accept cost, and reject cost. Determination of the optimal plan which minimizes the expected average cost per lot is discussed. Numerical examples are presented to illustrate the use of the proposed sampling plans and sensitivity analyses for parameters of the prior distribution are performed.

• 품질경영학회지
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• 제17권2호
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• pp.17-26
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• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2006년도 총회 및 춘계학술발표회
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• pp.391-393
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• 2006

In this study, the performance of artificial neural network (ANN) models for estimating spatial distribution of water quality was evaluated using electric conductivity (EC) values in landfill site. For the ANN model development, feedforward neural networks and backpropagation algorithm with gradient descent method were used. In Test 1, the interpolation ability of the ANN model was evaluated. Results of the ANN model were more precise than those of the Kriging model. In Test 2, spatial distributions of EC values were predicted using precipitation data. Results seemed to be reasonable, however, they showed a limitation of ANN models in extrapolations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.282-285
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• 1996

In the water purification plant, the raw water is promptly purified by injecting chemicals. The amount of chemicals is directly related to water quality such as turbidity, temperature, pH and alkalinity. At present, however, the process of chemical reaction to the turbidity has not been clarified as yet. Since the process of coagulant dosage has no feedback signal, the amount of chemical can not be calculated from water quality data which were sensed from the plant. Accordingly, it has to be judged and determined by Jar-Test data which were made by skilled operators. In this paper, it is concerned to model and control the coagulant dosing process using jar-test results in order to predict optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride). The considering relations to the reaction of coagulation and flocculation, the five independent variables(turbidity, temperature, pH, Alkalinity of the raw water, PAC feed rate) are selected out and they are put into calculation to develope a neural network model and a fuzzy model for coagulant dosing process in water purification system. These model are utilized to predict optimum coagulant dosage which can minimize the water turbidity in flocculator. The efficacy of the proposed control schemes was examined by the field test.

• 대한산업공학회지
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• 제40권3호
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• pp.257-266
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• 2014

The semiconductor manufacturing industry is managed by a number of parameters from the FAB which is the initial step of production to package test which is the final step of production. Various methods for prediction for the quality and yield are required to reduce the production costs caused by a complicated manufacturing process. In order to increase the accuracy of quality prediction, we have to extract the significant features from the large amount of data. In this study, we propose the method for extracting feature from the cell level data of probe test process using OPTICS which is one of the density-based clustering to improve the prediction accuracy of the quality of the assembled chips that will be placed in a package test. Two features extracted by using OPTICS are used as input variables of quality prediction model because of having position information of the cell defect. The package test progress for chips classified to the correct quality grade by performing the improved prediction method is expected to bring the effect of reducing production costs.