• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.2059-2063
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• 2004

Most power plants have operated many independent computerize systems for maintenance. Independence of systems have caused complexity of business process and inconvenience of computer system management. Because the equipment and material master data is not standardize and structurize, it is difficult to manage equipment maintenance history and material delivery. Especially equipment classification criterion is important for standardization of every maintenance information. It is necessary to integrate function of independent systems for business process simplification and rapid work flow. this paper provides equipment classification criterion design and system integration method with the case of live system development.

• 반도체디스플레이기술학회지
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• 제16권3호
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• pp.20-24
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• 2017

For process improvement and cutting down on expenses in solar cell industry, it is necessary to improve recycling process of wafer manufacturing. In this research, a study is introduced to develop classifier which is for recycling of abrasive. First of all, recycling process of wafer manufacturing is analyzed. And then, 3 steps of experiments such as oil removal, impurities removal and classification were executed. For the classification of slurry, a classifier is designed and manufactured. From experiments, it is verified that ultra sound vibration and flux are very important factors for classification. By experiencing the recycling processes and making devices, the technique can be initiated industry if needed such as decreasing waste and cutting down on expenses.

• 대한한의학원전학회지
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• 제36권3호
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• pp.89-128
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• 2023

Objectives : This study aims to diachronically examine the classification systems of all materia medica, followed by categorization and analysis of each category to deduce each category's characteristic. This will provide foundation for further examining classifications of bencao in contemporary herbology. Methods : Classification systems from a total of 93 bencao related texts were collected and categorized. Each category's classification system was analyzed to determine its meaning. The classification systems were compared from a diachronic perspective, to further deduce each system's problem from a historical context. Results : The classification systems of materia medica could be summarized as following three standards: quality, origin, and medical application. In reality, bencao could be generally classified according to origin and medical application. The origin-based classification system provided a stable and flexible classification outline in the expansion process of bencao. The medical application-based classification strengthened the relationship between bencao and illness pattern, improving clinical applicability. Conclusions : In the history of herbology, the two classification systems created the current of herbology through mutual contribution and conflict. We hope that further discussion on the direction towards which classification system of bencao in contemporary herbology should head will proceed based on this study.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.245-250
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• 2004

The classification of the satellite images is basic part in Remote sensing. In classification of the satellite images, class separability feature is very effective accuracy of the images classified. For improving classification accuracy, It is necessary to study classification methode than analysis of class separability feature deciding classification probability. In this study, IKONOS, SPOT 5, Landsat TM, were resampled to sizes 1m grid. Above images were calculated the class separability prior to the step for classification of pixels. The results of the study were valued necessary process in geometric information building. This study help to improve accuracy of classification as feature of class separability in the class through optimizing previous classification steps.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• 한국산학기술학회논문지
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• 제16권5호
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• pp.3000-3005
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• 2015

신뢰할 수 있는 공정 감시와 진단은 생산 공정의 안전과 최종제품의 품질을 보장이라는 관점에서 중요하다. 공정진단의 목적은 특정한 공정 이상의 원인을 밝혀내는 것이다. 본 연구에서는 분류기법에 기반한 공정진단 체계를 제시한다. 여기서는 공정데이터를 비선형 데이터 표현기법을 통해 변환함으로써 데이터의 크기를 줄이며 효율적인 데이터 표현이 가능하다. 추가적인 단계로서 공정 데이터의 전처리 과정을 통해 진단에 무관한 공정 패턴을 제거하고 진단 성능을 높이고자 한다. 진단 성능을 평가하기 위해 회분식 공정에 대한 사례연구를 수행한 결과 기존 선형 진단 방법론 및 전처리 과정이 없는 방법론에 비해 향상된 진단 결과를 얻을 수 있었다.

• 한국멀티미디어학회논문지
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• 제14권9호
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• pp.1190-1201
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• 2011

본 연구는 간호사 및 간호학생을 위한 간호진단, 간호중재, 간호결과 분류체계의 간호과정 프로그램을 모바일 응용 기반으로 개발하였다. 연구재료는 표준화된 분류체계인 북미간호진단협의회의 간호진단 분류체계와 아이오와 대학을 중심으로 개발된 간호중재 분류체계, 간호결과 분류체계를 사용하였다. 기존 연구 방법은 간호과정의 일부분만을 선택하여 개발하므로 환경에 제한적인 프로그램으로 임상에 일반화시켜 환자들에게 적용하기 어려웠다. 그러나 본 연구는 진단-결과-중재의 전체를 연계시킨 프레임워크를 개발하므로 어떠한 임상환경에서도 적용이 가능한 가이드라인으로 개발하였다. 개발된 프로그램은 한글판으로 3월부터 앱 스토어에 등록되었으며 간호교육 도구로 적극적으로 활용되기를 기대한다.

• 산업경영시스템학회지
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• 제44권3호
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• pp.1-9
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• 2021

This research examines deep learning based image recognition models for beef sirloin classification. The sirloin of beef can be classified as the upper sirloin, the lower sirloin, and the ribeye, whereas during the distribution process they are often simply unified into the sirloin region. In this work, for detailed classification of beef sirloin regions we develop a model that can learn image information in a reasonable computation time using the MobileNet algorithm. In addition, to increase the accuracy of the model we introduce data augmentation methods as well, which amplifies the image data collected during the distribution process. This data augmentation enables to consider a larger size of training data set by which the accuracy of the model can be significantly improved. The data generated during the data proliferation process was tested using the MobileNet algorithm, where the test data set was obtained from the distribution processes in the real-world practice. Through the computational experiences we confirm that the accuracy of the suggested model is up to 83%. We expect that the classification model of this study can contribute to providing a more accurate and detailed information exchange between suppliers and consumers during the distribution process of beef sirloin.

• 산업기술연구
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• 제19권
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• pp.155-162
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• 1999

In the last few years the automatic classification of morpholgical landforms using GSIS and DEM was investigated. Particular emphasis has been put on the morphological point attribute approaches and the extraction of drainage basin variables from digital elevation models. The automated derivation of landforms has become a neccessity for quantitative analysis in geomorphology. Furthermore, the application of GSIS technologies has become an important tool for data management and numerical data analysis for purpose of geomorphological mapping. A process developed by Dikau et al, which automates Hanmond's manual process, was applied to the pyoung chang of the kangwon. Although it produced a classification that has good resemblance to the landforms in the area, it had some problems. For example, it produced a progressive zonation when landform changes from plains to mountains, it does not distinguish open valleys from a plains mountain interface, and it was affected by micro relief. Although automating existing quantitative manual processes is an important step in the evolution automation, definition may need to be calibrated since the attributes are oftem measured differently. A new process is presented that partly solves these problems.

• 대한공간정보학회지
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• 제14권2호
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• pp.69-75
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• 2006

본 연구의 목적은 공간데이터 구측의 공종분류체계를 표준화하는데 있다. 공종분류체계는 지리정보 구축시 발생되는 제반정보를 체계적으로 분류하기 위한 기본틀이다. 국토지리정보원에서 수행되는 기본측량을 대상으로 하였으며, 측량 업체의 기본측량 실무공정과 국토지리정보원의 규정을 조사, 분석하였다. 조사, 분석한 내용을 기반으로 공간데이터 구축사업의 종류, 사업별 공종 및 공종별 성과물 체계를 표준화하였다. 본 연구에서 제시된 지리정보 공종분류체계를 국가 표준에 반영하고 공간데이터베이스 구축방법론으로 발전시킨다면, 지리정보 제작 사업을 체계적으로 관리하고 선진화할 수 있을 것으로 기대된다.