• Journal of Information Technology Applications and Management
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• 제11권4호
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• pp.209-225
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• 2004

This paper presents case studies on database Quality uSing an extended database Quality model developed by Korea Database Promotion Center, which shall be called KDPC2003. The model is applied to evaluate two kinds of databases ; one is an operational database, the other is an information service database. The purpose of this research is two-folded. One is to evaluate database quality and assess current status of database quality management; the other is to assess usefulness of KDPC2003 and to propose ideas for its augmentation. The findings in this study will provide basic facts to test database quality evaluation models.

• 정보교육학회논문지
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• 제2권1호
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• pp.35-51
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• 1998

Software reliability growth model is one of the evaluation methods, software quality which quantitatively calculates the software reliability based on the number of errors detected. For correct and precise evaluation of reliability of certain software, the reliability model, which is considered to fit dose to real data should be selected as well. In this paper, the optimal model for specific test data was selected one of among five software reliability growth models based on NHPP(Non Homogeneous Poission Process), and in result reliability estimating scales(total expected number of errors, error detection rate, expected number of errors remaining in the software, reliability etc) could obtained. According to reliability estimating scales obtained, Software development and predicting optimal release point and finally in conducting systematic project management.

• Genomics & Informatics
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• 제20권2호
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• pp.23.1-23.9
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• 2022

A survival prediction model has recently been developed to evaluate the prognosis of resected nonmetastatic pancreatic ductal adenocarcinoma based on a Cox model using two nationwide databases: Surveillance, Epidemiology and End Results (SEER) and Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP). In this study, we applied two machine learning methods-random survival forests (RSF) and support vector machines (SVM)-for survival analysis and compared their prediction performance using the SEER and KOTUS-BP datasets. Three schemes were used for model development and evaluation. First, we utilized data from SEER for model development and used data from KOTUS-BP for external evaluation. Second, these two datasets were swapped by taking data from KOTUS-BP for model development and data from SEER for external evaluation. Finally, we mixed these two datasets half and half and utilized the mixed datasets for model development and validation. We used 9,624 patients from SEER and 3,281 patients from KOTUS-BP to construct a prediction model with seven covariates: age, sex, histologic differentiation, adjuvant treatment, resection margin status, and the American Joint Committee on Cancer 8th edition T-stage and N-stage. Comparing the three schemes, the performance of the Cox model, RSF, and SVM was better when using the mixed datasets than when using the unmixed datasets. When using the mixed datasets, the C-index, 1-year, 2-year, and 3-year time-dependent areas under the curve for the Cox model were 0.644, 0.698, 0.680, and 0.687, respectively. The Cox model performed slightly better than RSF and SVM.

• 한국조경학회지
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• 제32권4호
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• pp.28-38
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• 2004

Korean goral (Nemorhaedus caudatus raddeanus) is one of the endangered species in Korea, and the rugged terrain of the Soraksan National Park (373㎢) is a critical habitat for the species. But the goral population is threatened by habitat fragmentation caused by roads and hiking trails. The objective of this study was to develop a potential habitat suitability model for Korean goral in the park, and the model was based on the concepts of fuzzy set theory and multi-criteria evaluation. The process of the suitability modeling could be divided into three steps. First, data for the modeling was collected by using field work and a literature survey. Collected data included 204 points of GPS data obtained through a goral trace survey and through the number of daily visitors to each hiking trail during the peak season of the park. Second, fuzzy set theory was employed for building a GIS data base related to environmental factors affecting the suitability of the goral habitat. Finally, a multiple-criteria evaluation was performed as the final step towards a goral habitat suitability model. The results of the study were as follows. First, characteristics of suitable habitats were the proximity to rock cliffs, scattered pine (Pinus densiflora) patches, ridges, the elevation of 700∼800m, and the aspect of south and southeast. Second, the habitat suitability model had a high classification accuracy of 93.9％ for the analysis site, and 95.7％ for the validation site at a cut off value of 0.5. Finally, 11.7％ of habitatwith more than 0.5 of habitat suitability index was affected by roads and hiking trails in the park.

• 산업경영시스템학회지
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• 제41권1호
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• pp.1-10
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• 2018

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

• 한국조사연구학회지:조사연구
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• 제11권2호
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• pp.161-176
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• 2010

본 논문은 학위논문에 사용된 여론조사 자료의 품질을 평가하였으며, 또한 학위논문에 사용되는 데이터의 품질평가 모형을 제시하였다. 데이터의 품질평가와 평가모형에 사용한 평가지표는 한국조사연구학회에서 제시한 조사윤리강령 제3조의 16가지 항목을 사용하였다. 연구결과 학위논문에 사용된 여론조사 데이터의 품질은 낮은 수준임을 확인할 수 있었다. 16개 항목별로 석 박사학위에 따른 유의적인 차이가 있는지를 확인하기 위하여 두 집단 간 비율 차이 검정을 실시한 결과 표집오차와 분석방법의 수에서만 차이가 있을 뿐 다른 지표에서는 차이가 나타나지 않았다. 끝으로 학위논문에 사용된 여론조사 자료의 질을 평가하기 위한 품질평가를 위해 9가지 주요 평가지표에 가중치를 부여하는 모형을 제시하였다.

• 산업경영시스템학회지
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• 제23권54호
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• pp.87-95
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• 2000

To constuct the stochastic model for performance evaluation of Multi-AGV, two aspects must be considered. The first is stochastic situation for moving jobs. The second is the dispatching rule of AGV. In this paper, the stochastic model for performance evaluation of Multi-AGV is developed. The case of stochastic model with two AGV is developed. But it difficult to solve in the case of stochastic model with more than three AGV because the model have three-ordered equations. The evaluation factor of the model is utilization and empty travel time of AGV. Using these factors, one can easily evaluate a wide range of handling and layout alternatives from given flow data. Hence, the model would be most effective when used in the early stage of designing to narrow down the number of alternative prior to simuation.

• 유통과학연구
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• 제14권8호
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• pp.45-50
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• 2016

Purpose - This study aimed to develop a new practical and universally applicable service quality model by improving the service quality measurement model proposed by many previous studies. Research design, data, and methodology - An in-depth analysis on what influences such service quality model had on the improvement effect of service quality, and Service Evaluation Model("SEM"), which was revised from the existing service quality measurement model, was developed. The model is divided into the two integrative categories: First, activity, that is the group of service-related activities. Next is item, the group of service-related objects. The level of service is evaluated for each category via survey questionnaire on service level evaluation. Based on the model, SEM has visibility by structuring the whole service industry. Results - For the application of the new service quality model, this study attempted to examine the appropriateness of the newly proposed service quality model by applying it to retail service field. Conclusions - As a result, the proposed service model would be a useful and applicable service quality measurement model required by many organizations. Service company can set up self check service levels. Through these results, they can look for the ways to provide better services to customers. Service users can ensure the objectivity of business plan based upon SEM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

• 대한토목학회논문집
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• 제42권5호
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• pp.599-606
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• 2022

공용 중 강교량의 피로 평가에 활용할 수 있는 현장계측 데이터에는 대표적으로 변형률 계측과 Brigde Weight-In-motion (BWIM)이 있다. AASHTO The Manual For Bridge Evaluation에 따라, 대상 교량에서 계측된 데이터로부터 피로 상세에 가해지는 유효응력범위 및 반복응력 횟수를 추정할 수 있다. 추정된 유효응력범위와 반복응력 횟수를 통해 피로 손상 누적에 의한 신뢰도분석을 수행할 수 있다. 하지만 현장계측 데이터로부터 유효응력범위 및 응력범위 반복횟수를 추정하는 절차가 평가규정에 구체적으로 제시되어 있지 않고, 계측 데이터의 종류 또는 처리방법에 따른 피로 평가결과의 차이를 정량적으로 비교한 연구는 아직 미비한 실정이다. 본 연구에서는 공용 중 교량에서 동시에 계측한 변형률계 및 BWIM 데이터를 활용하여 피로 신뢰도평가를 수행하여, 활용되는 현장계측 데이터의 종류에 따른 평가결과의 차이에 대해 정량적으로 검토하였다. 이때, BWIM 데이터를 활용한 피로 신뢰도평가 시 구조해석모델의 정밀성이 평가결과에 미치는 영향을 검토하기 위해 평가 대상 교량의 뼈대요소 해석모델과 Shell-Solid 해석모델을 구축하였다. 또한, BWIM 데이터로부터 유효응력범위와 반복응력 횟수를 추정하기 위한 두 종류의 데이터 처리 방법을 정의하였으며, 이로 인한 피로 신뢰도 차이 역시 검토하였다.