• 한국안광학회지
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• 제13권4호
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• pp.115-119
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• 2008

목적: 노안에서 십자와 적록을 조합한 시표를 사용하여 얻어진 잠정가입도와 최종가입도를 비교하기 위해 실시하였다. 방법: 대상자는 41~60세(평균연령 51.7세) 사이의 노안이 있는 60명으로 하였다. 잠정가입도는 십자시표(CG), 적록시표(RG) 및 두 가지 시표를 조합하여 만든 적록십자시표(RGCG)를 사용하여 결정하였으며, 최종가입도는 검사거리 40 cm에서 각 대상자에 맞게 잠정가입도를 조정하여 결정하였다. 결과: 측정 방법별 잠정가입도와 최종가입도 사이의 유의한 차이가 있었으며, 적록십자시표에 의한 방법이 높은 신뢰도(repeatability)를 나타냈다. 결론: 적록 십자시표(RGCG)는 노안 가입도 결정에 필요한 적절한 데이터를 얻을 수 있으며, 양안시 임상에서 가입도 처방의 진단 평가에 유용할 것이다.

• 대한산업공학회지
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• 제40권1호
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• pp.43-51
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• 2014

Statistical process control (SPC) is an important technique for monitoring and managing the manufacturing process. In spite of its easiness and effectiveness, some problematic sides of application exist such that the SPC techniques are hardly reflect the changes of the process conditions. Especially, update of control limits at the right time plays an important role in acquiring a reasonable performance of control charts. Therefore, we propose the control chart performance evaluation index (CPEI) based on count data model to monitor and manage the performance of control charts. The CPEI could indicate the degree of control chart performance and be helpful to detect the proper update cycle of control limits in real time. Experiments using real manufacturing data show that the proper update intervals are made by proposed method.

• 한국CDE학회논문집
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• 제11권2호
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• pp.148-155
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• 2006

This paper presents a new method for assessing the efficiency of production process plans using tolerance chart to lower production cost. The tolerance chart is used to predict the accuracy of a part that is to be produced following the process plan, and to carry out the quantitative measurement on the efficiency of the process plan. By comparing the values of design tolerances and their corresponding resultant tolerances calculated using the tolerance chart, the process plan that is incapable of satisfying the design requirements and the faulty production operations can be identified. Similarly, the process plan that imposes unnecessarily high accuracy and wasteful production operations can also be identified. For the latter, a quantitative measure on the efficiency of the process plan is introduced. The higher the unnecessary cost of the production, the poor is the efficiency of the process plan. A coefficient is introduced for measuring the process plan efficiency. The coefficient also incorporates two weighting factors to reflect the difficulty of manufacturing operations and number of dimensional tolerances involved. To facilitate the identification of the machining operations and the machined surfaces, which are related to the unnecessarily tight resultant tolerances caused by the process plan, a rooted tree representation of the tolerance chart is introduced, and its use is demonstrated. An example is presented to illustrate the new method. This research introduces a new quantitative process plan evaluation method that may lead to the optimization of process plans.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 추계공동학술대회
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• pp.293-297
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• 2006

Recently most universities are suffering from students leaving their majors. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, this paper uses decision tree algorithm which is one of the data mining techniques which conduct grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on students leaving their majors. The dataset consists of 5,115 features through data selection from total data of 13,346 collected from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006.6.30). The main objective of this study is to evaluate performance of algorithms including CHAID, CART and C4.5 for classification of students leaving their majors with ROC Chart, Lift Chart and Gains Chart. Also, this study provides values about accuracy, sensitivity, specificity using classification table. According to the analysis result, CART showed the best performance for classification of students leaving their majors.

• 대한의용생체공학회:의공학회지
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• 제43권5호
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• pp.299-307
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• 2022

In this paper, we propose a pre-processing method that converts to Spider Chart image data for classification of gripping movement using EMG (electromyography) sensors and Convolution Neural Networks (CNN) deep learning. First, raw data for six hand gestures are extracted from five test subjects using an 8-channel armband and converted into Spider Chart data of octagonal shapes, which are divided into several sliding windows and are learned. In classifying six hand gestures, the classification performance is compared with the proposed pre-processing method and the existing methods. Deep learning was performed on the dataset by dividing 70% of the total into training, 15% as testing, and 15% as validation. For system performance evaluation, five cross-validations were applied by dividing 80% of the entire dataset by training and 20% by testing. The proposed method generates 97% and 94.54% in cross-validation and general tests, respectively, using the Spider Chart preprocessing, which was better results than the conventional methods.

• 한국환경복원기술학회지
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• 제5권4호
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• pp.39-50
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• 2002

The purpose of this study was to evaluate site-based environmental education(EE) programs. For the evaluation, an evaluation chart was developed. The chart was consisted of twenty evaluation items in the following six categories : 'goals & objectives', 'instructional planning', 'instruction', 'learning outcomes & evaluation', 'features of program', and 'program operation'. One hundred sixty five site-based EE programs, funded by the Korean Ministry of Environment in 2000, were evaluated. After the evaluation, the programs were also categorized and analyzed according to regions, organizations, and amount of funds. The results indicated that awareness, participation, and attitude were addressed in the purpose of the programs, while knowledge and skills were not. The diversity of activities and teaching strategies of the programs were insufficient. Cultural aspects, fairness, originality, and accuracy were also insufficiently addressed. Assessment and evaluation of such programs were needed to be considered to a larger degree. From the analysis of programs according to categories, Choongbuk province in the regional aspect and schools in the organizational aspect got higher scores than others. Overall, the more funding the program received, the higher score it got in evaluation. Some improvements and strategies for activating site-based EE were recommended based on the result of the evaluation.

• 정보처리학회논문지A
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• 제17A권2호
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• pp.73-80
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• 2010

하드웨어의 성능이 향상됨에 따라 멀티태스킹 방식으로 병행 처리하는 연구가 다양하게 진행되고 있다. 프로그램 개발 단계에서 프로그램을 수정할 경우, 전체 프로그램을 다시 평가하는 대신 수정한 부분과 그 부분에 영향 받는 부분만을 다시 평가하는 방법이 점진 평가인데, 여러 프로세서에서 병렬로 처리하는 대신 자바언어의 멀티쓰레딩 기능을 활용하여 점진 평가의 효율성을 증대시키는 연구가 필요하다. 본 논문에서는 의미 구조에 직접적으로 영향을 주는 변수의 값을 나타내는 속성을 중심으로 종속성을 표시하여 객체 지향언어인 자바 언어에서 병행 점진 평가를 동시에 효율적으로 수행할 수 있는 병행 점진 평가 알고리즘을 제시하고 그 알고리즘의 정확성을 증명한다. 실험을 통해 병행 점진 평가 방법의 효율성을 분석한다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.51-56
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• 2006

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare performance of algorithms for data analysis of industrial accidents and this paper provides a comparative analysis of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. In this study, data on 67,278 accidents were analyzed to create risk groups for a number of complications, including the risk of disease and accident. The sample for this work chosen from data related to manufacturing industries during three years $(2002\sim2004)$ in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.

• 산업경영시스템학회지
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• 제22권52호
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• pp.347-354
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• 1999

Statistical Process Control(SPC) which uses control charts is widely used to inspect and improve manufacturing process as a effective method. A parametric method is the most common in statistical process control. Shewhart chart was made under the assumption that measurements are independent and normal distribution. In practice, this assumption is often excluded, for example, in case of (equation omitted) chart, when the subgroup sample is small or correlation, it happens that measured data have bias or rejection of the normality test. A bootstrap method can be used in such a situation, which is calculated by resampling procedure without pre-distribution assumption. In this study, applying bootstrap percentile method to (equation omitted) chart, it is compared and evaluated standard process control limit with bootstrap percentile control limit. Also, under the normal and non-normal distributions, where parameter is 0.5, using computer simulation, it is compared standard parametric with bootstrap method which is used to decide process control limits in process quality.

• 대한안전경영과학회지
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• 제10권2호
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• pp.195-203
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• 2008

The purpose of this study is to develop a guideline of process capability evaluation and to apply this guideline improving the quality of products, especially in the small and medium enterprises. In this study we deal in the concept of process capability evaluation, the calculation of process capability index, and the application of a case study. Man must compare the state of process with the standards in evaluating of the process capability. Control chart can be used as a yardstick for judgement for the long term period and the distribution shape of histogram for the short term period. Man should regard to the significant figure by the calculation of process capability index.