• 수산해양교육연구
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• 제19권3호
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• pp.390-402
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• 2007

According to the paradigm of Neo-liberalism, the issue of ability grouping has grown more and more in education of Korea. And because of the influence of ability grouping, now ability grouping is enforcing partially in the subjects of English and Mathematics. But ability grouping is going to expand to the all subjects. So, it is very important that how teachers and students are recognize about partial ability grouping in the subjects of English and Mathematics. Because that information about partial ability grouping can guide direction for the future educational policy. The purpose of this study was to actually analyze teacher's and students' recognition of partial ability grouping in the subjects of English and Mathematics. To accomplish this purpose, 622 middles school students and 552 teachers were sampled. As a tool of investigation, questionnaires about teacher's and students' recognition of partial ability grouping had made by researcher of this study were used. And as processing of data, t-test, F-test, Scheff-test were used. The result of this study is as follow. First, teachers who are experiencing ability grouping recognized more negative about ability grouping than teachers who are not experiencing ability grouping. Second, students who have low ability recognized more negative about ability grouping than students who have high ability. Third, teachers who are experiencing ability grouping recognized more ineffective about ability grouping than teachers who are not experiencing ability grouping. Fourth, students who have low ability recognized more ineffective about ability grouping than students who have high ability.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• 한국컴퓨터정보학회논문지
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• 제16권5호
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• pp.109-125
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• 2011

폭소노미는 웹에 존재하는 리소스에 대해 구성원이 자유롭게 선택한 태그를 붙여서 정보를 체계화하는 새로운 분류 체계이다. Del.icio.us, Flickr, YouTube 등과 같은 최근의 폭소노미 기반 협력 태깅 시스템들을 살펴보면, 폭소노미 데이터를 체계화하고 유용한 서비스를 제공하기 위해 폭소노미의 각 구성요소들(사용자들, 태그들, 리소스들)을 그룹핑하기 위한 기능들을 추가하고 있다. 본 논문에서는, 일반적인 폭소노미에 "그룹(Group)"이라는 개념을 도입하여 확장한 그룹화된 폭소노미(Grouped Folksonomy) 모델과 그룹핑 관련 기본 연산들(Group Aggregation, Group Composition, Group Intersection, Group Difference)을 제안한다. 또한, 본 논문에서는 그룹화된 폭소노미의 구축과 기본연산 수행을 지원하는 도구(GFO)의 개발과 활용사례를 소개한다. 본 연구에서 제안된 모델과 기본 연산들로 구성된 그룹화된 폭소노미 구축을 위한 프레임워크는 폭소노미의 각 구성요소들을 그룹핑하여 그룹화된 폭소노미를 구성하고 보다 유용한 정보들을 추출 및 통합하여 체계화 할 수 있는 토대를 제공한다.

• 디지털융복합연구
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• 제16권7호
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• pp.243-248
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• 2018

협동학습이 효과적으로 이루어지기 위해 가장 중요한 요소는 학습자의 여러 특성을 고려한 모둠 구성에 있다. 모둠 구성이란 원활하게 협동학습을 진행하기 위해 학습자들을 다양한 특성에 근거하여 모둠을 구성하는 것이다. 잘못된 도구의 선정으로 인해 모둠의 구성이 제대로 이루어지지 않을 경우 학생들의 불만이 수업으로 이어져 학습의 효과로까지 나타나는 문제가 발생할 수 있다. 본 논문에서는 학습효과 향상 및 불링 경향성 진단을 함께 고려한 모둠 구성 도구를 구현하였다. 소시오메트리 설문을 통한 학생들 간의 학급선호도와 학생의 성적을 입력받아 교사의 주관에 맞게 모둠을 구성함으로써 학습 효과도 고려할 수 있고 더불어 불링 경향성도 진단할 수 있는 모둠 구성 도구를 제안하고자 한다. 이를 통해 교사는 학습 효과를 증진 시킬 수 있는 수업 진행이 가능한 협동학습뿐만 아니라 학생들의 교우관계를 미리 파악해 학급 내에서 일어날 수 있는 불링에 미리 대처할 수 있을 것으로 기대한다.

• 산업경영시스템학회지
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• 제39권3호
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• pp.83-89
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• 2016

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

• 정보보호학회논문지
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• 제29권6호
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• pp.1235-1242
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• 2019

본 논문에서는 머신러닝 기반의 악성코드 분류에 있어 오버피팅 문제를 비롯하여 실제로 실행되지 않는 코드가 APK에 포함되는 문제 등을 해결하기 위해 모든 API들의 연관성을 통해 그룹화하며, 제어 흐름 분석을 통해 실제로 실행되는 코드에 대한 분석을 수행하는 툴을 개발하였다. 툴은 약 1,500라인으로 이루어진 자바 기반의 소프트웨어로, 전체 API에 대한 빈도 분석을 수행하거나 생성된 제어 흐름 그래프를 바탕으로 빈도 분석을 수행한다. 툴을 이용하여 모든 버전에서의 총 39032개의 메서드에 대해 4972개의 그룹으로 축소할 수 있으며, 클래스를 포함한 결과로는 총 12123개의 그룹으로 축소할 수 있다. 결과 분석을 위해서 본 논문에서는 총 7개의 패밀리에서 7,000개의 APK를 랜덤으로 수집하였으며, 수집된 APK를 이용하여 feature를 축소하는 기법을 검증하였다. 또한, 추출된 데이터에서 빈도가 20% 이상으로 나타난 API만을 선별하여 feature를 더욱 축소하여 최종적으로 263개의 feature로 축소하였다.

• 전기학회논문지
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• 제58권5호
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• pp.911-917
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• 2009

This paper introduces a sequential clustering technique as a tool for an effective grouping of transmission systems. The interconnected network system retains information about the location of each line. With this information, this paper aims to carry out initial clustering through the transmission usage rate, compare the similarity measures of regional information with the similarity measures of location price, and introduce the techniques of the clustering method. This transmission usage rate uses power flow based on congestion costs and similarity measurements using the FCM(Fuzzy C-Mean) algorithm. This paper also aims to prove the propriety of the proposed clustering method by comparing it with existing clustering methods that use the similarity measurement system. The proposed algorithm is demonstrated through the IEEE 39-bus RTS and Korea power system.

• 한국정보과학회논문지:시스템및이론
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• 제35권7호
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• pp.340-353
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• 2008

화풍을 효과적이고 객관적으로 기술하는 한 방법으로 팔레트 추출에 대한 수학적 모델을 제시한다. 이 모델에서는 팔레트를 허용 오차 범위 내에서 회화 작품의 영상을 표현할 수 있는 주요 색상의 집합으로 정의하고 색상 그룹핑과 주요 색상 추출의 두 단계를 거처 팔레트 색상을 추출한다. 색상 그룹핑은 주어진 회화에 대해 적응적으로 색의 분해능을 조절하여 각 회화 작품을 이루는 기초 색상을 추출하며 다음 주요 색상 추출 단계에서 이것과 이것이 차지하는 영역에 대한 정보를 바탕으로 K-Means 클러스터링 알고리즘을 적용하여 팔레트를 얻는다. 실험을 통해 유명 화가의 작품을 대상으로 RGB와 CIE LAB 색상 모델을 사용하여 추출한 팔레트를 3차원 색 공간에 표시하였다. 팔레트 색상의 거리를 사용한 화가 분류 실험과 실사 영상의 색채 변환 실험 통해 이 방법이 화풍 분석과 그래픽 분야에 적용될 수 있음을 확인하였다.

• Management Science and Financial Engineering
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• 제2권1호
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• pp.1-18
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• 1996

FMS operating system consists of several subsystems in general. i.e. tool grouping subsystem. tool/job assignment subsystem. job dispatching subsystem, and papers dealing with each subsystem were published by many researchers [1], [4], [6], [8], [9], [10], [11], [12], [13], [14], [15], [16]. This paper mainly discusses about tool/job assignment subsystem as a job loading procedure. that occupies the kernel position of overall FMS operating system. Its performance is evaluated through simulation experiments of an integrated operating system under a typical FMS hardware configuration implemented in many machining factories, which is composed of the proposed procedure as well as a job dispatching procedure including several heuristic dispatching rules in terms of rule-base.

• Journal of Information Technology Applications and Management
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• 제12권3호
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• pp.111-128
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• 2005

This paper examines the validity of the newly developed IT consulting SERVQUAL measurement tool. In an attempt to measure Ire IS customers' expectations and perceived quality of the services they received, the researchers developed a diagnostic tool of SERVQUAL based on the solid theoretical background, which can specifically be applied to the IT consulting service sector. This on-going research so far, has been applied to six (6) different organizations that have received IT consulting services over the past years. From the preliminary data collected, the correlation and the factor analyses were conducted to understand the underlying concept and refinement of the measurement tool. Although the correlation analysis showed a little tendency of collinearity among some of the variables, all showed sound relationship of the proposed hypotheses. The exploratory factor analytic approach was chosen because it does not set any priori constraints on the estimation of components or the number of components to be extracted. The number of different factor solutions was extracted and tested to see which solution represents better grouping of the variables. The Crombach's Alpha was computed on different combinations of the factor solutions to ensure validity. The results show 8-dimensional IT consulting SERVQUAL measures which they are, assurance, knowledge & skill, customer relationship, support, empathy, process management, expertise, and education, seem more appropriate than the originally proposed 6 dimensions. The study approach was non-experimental cross-sectional research design. The longitudinal design of follow-up studies to periodically revise and refine current measure is strongly recommended for fine tuning of the tool.