• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 C
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• pp.1982-1984
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• 2004

Stator coil of rotating machinery has shown different characteristics according to impregnated with coil or not. And this is major determinant of equipment's life. In this paper, PD characteristics is studied as a classification scheme between two specimens. Processing of the coil impregnation is very important thing because that influences on thermal and electrical characteristics of the coil. And then PD is occurring at the coil and causing insulation degradation. For processing statistical processing, PD data acquired from PD detector using PDASDA(partial discharge acquisition, storage and display system). And also these statistical distribution and parameter are applied to classify PD sources by neural networks. As a result of, Neural Networks have a good discrimination rate for classification PD sources.

• Journal of Information Processing Systems
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• 제11권3호
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• pp.450-464
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• 2015

In linguistics, stemming is the operation of reducing words to their more general form, which is called the 'stem'. Stemming is an important step in information retrieval systems, natural language processing, and text mining. Information retrieval systems are evaluated by metrics like precision and recall and the fundamental superiority of an information retrieval system over another one is measured by them. Stemmers decrease the indexed file, increase the speed of information retrieval systems, and improve the performance of these systems by boosting precision and recall. There are few Persian stemmers and most of them work based on morphological rules. In this paper we carefully study Persian stemmers, which are classified into three main classes: structural stemmers, lookup table stemmers, and statistical stemmers. We describe the algorithms of each class carefully and present the weaknesses and strengths of each Persian stemmer. We also propose some metrics to compare and evaluate each stemmer by them.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.347-350
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• 2011

This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

• 품질경영학회지
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• 제25권1호
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• pp.116-134
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• 1997

The present automated manufacturing environment is very different when the classical statistical process control method based on batch processing were used. Therefore these must be replaced by automated statistical process control method. In this point of view, this paper intends to develop the automated statistical process control method which can be implemented in the present automated manufacturing environment. Specially this study developed the rules to identify the special causes of the manufacturing process in the aspect of the 100 PPM management, and a numerical example is demonstrated to verify the usefulness of these rules.

• 한국유기농업학회지
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• 제30권1호
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• pp.21-35
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• 2022

Measuring the food safety has been focused only on the psychological consumers' recognition of food safety. The actual measurement tool should consist of the evidence-based statistical data to assess the level of national food safety in scientific perspectives. This paper described the development of a concept to measure the food safety of the food chain based on OECD PSR framework. This paper discusses the elaboration of a set of 8 food safety related data issued as statistical data, and which were same weighted. These food safety statistical data (FSDs) were derived as the basis of measuring the variation of food safety during 2013-2019. The values of the primary production indicator (PPI), the processing and manufacturing indicator (PMI), and the distribution and consumption indicator (DCI) are 0.558-0.859, 0.533-0.691, and 0.979-0.982, respectively. The food safety status (FSS) derived from the safety indicator values of each of the three stages is 0.700-0.810. In order to increase the level of food safety, it is necessary to pay attention to PMI and PPI management. In the future, continuously calculating the level of food safety, managing it like the level of psychological safety, and further expanding it to the level of food safety between countries will help establish policies to improve the level of food safety in Korea.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2023년도 임시총회 및 춘계학술대회
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• pp.25-25
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• 2023

As the demand for processing potatoes increases, imports of raw potatoes and potato products are increasing, so it is necessary to expand potato production as raw materials for processing in Korea. Potato varieties for processing that can be grown in fall have been developed, but research on cultivation technology and processing quality management technology to improve chip processing quality is very insufficient. Therefore, this study was conducted to investigate the optimal harvest time by investigating the quantity and chipping characteristics of potato chips during autumn cultivation. As the test varieties, the chip processing varieties "Saebong", "Eunsun", and "Geumnaru" were used, and the potato cultivation site was the Seocheon-gun Test field (214 Gaeya-ri) of the Chungcheongnam-do. The test treatment was at harvest time after spring cultivation, and the potatoes were harvested at 70, 80, 90, and 100 days after sowing based on the sowing time. The investigation items were potato productivity (total yield, yield of standard processing, and number of tubers) and chip-processing characteristics (chip color, dry matter content, glucose content, etc.). As a result of examining the yield characteristics according to the harvest time, statistical significance was not found according to the treatment. The total yield (ton/ha) was 27.5 to 30.5, and there was no significant difference depending on the time of 70 to 100 days after harvest. The standard quantity for processing (yield of 81-250g potatoes per unit) also showed a similar trend. In chipping characteristics according to harvest time, statistical significance was high in specific gravity and glucose content. The specific gravity was highest at 1.077 at 70 days after harvest, and the glucose (mg/dL) content was the lowest at 37.5 at 80 days after harvest. Statistical significance was not recognized, but chip color (L value) was the highest at 64.4 at 70 days after harvest. Therefore, it is judged that the optimal harvesting time for chip processing is 70 to 80 days after sowing.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.331-332
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• 2007

• 한국정밀공학회지
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• 제15권2호
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• pp.75-80
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• 1998

Process information is known to have the continuous distribution in many manufacturing processes. Generalized p-chart has been developed for controlling processes by classifying the information characteristics into several groups. But it is improper to describe continuous processes with the classified process informal ion, which is based on the classical set concept. Fuzzy control chart, has been developed for the control of linguistic data, but it is also based on the dichotomous notion of classical set theory. In this paper, fuzzy sampling method is studied in order to process the uncertain data properly. The method is incorporated with the fuzzy control chart. Statistical characteristics of the fuzzy representative value are utilized to device the fuzzy-statistical control chart. The fuzzy-statistical control chart is compared with the generalized p-chart and both the sensitivity to the process information distribution change pared robustiness against the noise on the process information of the fuzzy-statistical control chart are shown to be superior.

• Industrial Engineering and Management Systems
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• 제14권4호
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• pp.392-400
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• 2015

Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

• Journal of Information Science Theory and Practice
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• 제11권2호
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.