• 정보기술응용연구
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• 제1권
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• 한국도서관정보학회지
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• 제44권2호
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• pp.399-422
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• 2013

이 연구는 KDC에서의 통계학 주제가 사회과학 통계학과 자연과학 수리통계학에 교착분류되는 문제점을 개선하고 세부영역의 체계적 전개방안을 제시하는데 있다. 이를 위해 통계학의 학문적 특성, 국내 대학 통계학과의 현황 및 학과명의 변천과정, 교과과정을 분석하였으며, DDC, LCC, NDC의 문헌분류법과 한국연구재단의 연구분야분류표를 비교 분석하였다. 그 결과 관련학과와 연구분야분류표의 학문적 배경에 따라 사회과학의 통계학을 자연과학 아래로 이치 및 통합하였다. 기존의 사회통계학 주제는 사회과학 연구방법을 보완하여 통계적 연구방법으로 세분하여 전개하였다. 또한, 자연과학의 '확률, 수리통계학'의 표목을 '통계학'으로 수정하고 세부영역의 주제를 체계화하여 확대 전개하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권2호
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• pp.175-196
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• 2018

Purpose The purpose of this study is to identify problems of current educational facility data management and recommend a standardized terminology classification system as a solution. In addition, the research aims to present a preemptive and integrated disaster and safety management framework for educational facilities by seeking efficient business processes through secured data quality, systematic data management, and external data linkage and analysis. Design/methodology/approach A terminology classification system has been established through various processes including filtering and analysis of related data including laws, manuals, educational facilities accidents, and historical records. Furthermore, the terminology classification system has been further reviewed through several consultations with experts and practitioners. In addition, the accumulated data was refined according to the established standard terminology and an Excel database was developed. Based on the data, accident patterns occurred in educational facilities over the past 10 years were analyzed. Findings In the study, a template was developed to collect consistent data for the standardized disaster and safety management terminology classification system in educational facilities. In addition, the standardized data utilization methods are presented from the viewpoint of 'education facility disaster safety data management', 'data analysis and insight', 'business management through data', and 'leaping into big data management'.

• 한국CDE학회논문집
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• 제12권5호
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Journal of Power Electronics
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• 제16권3호
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• pp.1097-1109
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• 2016

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination of optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system.

• 대한원격탐사학회지
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• 제27권3호
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• pp.379-388
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• 2011

At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.

• 대한토목학회논문집
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• 제37권5호
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• pp.863-869
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• 2017

본 연구에서는 다양한 정수처리공법과 시설을 분류하여 정수장의 시설물 정보분할코드체계를 구축하였으며, 이것은 정수장 시설의 생애주기 동안 소요되는 유지관리비용, 에너지 사용비용 산정 및 배출된 환경오염원의 규명과 환경영향평가의 정량적 분석 등을 위한 정보를 통합하기 위한 전산시스템의 코드체계로 활용하게 된다. 건설공사의 정보는 많은 이질정보를 포함하고 있기 때문에 이를 통합해서 관리하기 위한 코드체계가 매우 중요하다. 또한 정수장 시설은 많은 프로세스를 포함한 시설물 설치공사가 주를 이루기 때문에 좀 더 세분화된 분활코드가 필요하다. 따라서 본 연구에서는 국내에서 시도되지 않은 정수장 관련 분류체계를 건설공사 분류체계인 파셋 분류체계 표현방식을 활용하여 구축하였다.

• 정보처리학회논문지D
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• 제16D권3호
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• pp.433-440
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• 2009

최근 건설 분야의 정보화 기술이 발달함에 따라 건설업무의 생산성 향상과 비용 절감을 위한 다양한 건설자재 정보 서비스 차원의 web 기반 온라인 시스템이 급증하는 추세이다. 그러나 이러한 시스템들이 제공 중인 품질 및 규격등 건설자재정보가 표준화되지 못하여 특정자재의 정보획득시 여러 정보시스템을 이용하거나 유사한 작업을 반복하는등 건설현장 실무자들의 자재정보 활용에 있어 많은 어려움을 겪고 있다. 이에 본 연구에서는 국제 데이터 상품 속성 시스템(GDAS, Global Data Alignment System)을 기준으로 건설자재 정보항목을 정형화하고 건설자재 통합정보 관리를 위한 시스템 모델을 설계하였다. 본 시스템은 건설공정별 국제 표준분류체계(OmniClass Part-22)와 유엔 표준 제품 및 서비스 분류체계(UNSPSC, United Nations Standard Products and Services Classification)를 적용한 건설 자재의 자동 분류, 자재정보의 조건별 복합검색, 전자카탈로그의 실시간 자동구현, RFID 검색 및 관리 기능을 지원함으로써 자재정보의 효율적인 관리 및 활용이 가능하다.

• 보건행정학회지
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• 제33권3호
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• pp.295-310
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• 2023

Background: The long-term care (LTC) group has higher rates of chronic disease and disability registration compared to the general older people population. There is a need to provide integrated medical services and care for LTC group. Consequently, this study aimed to identify medical usage patterns based on the ratings of LTC and the characteristics of benefits usage in the LTC group. Methods: This study employed the National Health Insurance Service Database to analyze the effects of demographic and LTC-related characteristics on medical usage from 2015 to 2019 using a repeated measures analysis. A longitudinal logit model was applied to binary data, while a linear mixed model was utilized for continuous data. Results: In the case of LTC ratings, a positive correlation was observed with overall medical usage. In terms of LTC benefit usage characteristics, a higher overall level of medical usage was found in the group using home care benefits. Detailed analysis by medical institution classification revealed a maintained correlation between care ratings and the volume of medical usage. However, medical usage by classification varied based on the characteristics of LTC benefit usage. Conclusion: This study identified a complex interaction between LTC characteristics and medical usage. Predicting the requisite medical services based on the LTC rating presented a challenge. Consequently, it becomes essential for the LTC group to continuously monitor medical and care needs, even after admission into the LTC system. To facilitate this, it is crucial to devise an LTC rating system that accurately reflects medical needs and to broaden the implementation of integrated medical-care policies.

• 한국해양학회지:바다
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• 제25권4호
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• pp.132-159
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• 2020

다학제적인 해양연구가 활발하게 수행됨에 따라 다양한 종류의 해양연구시설·장비가 매년 구입되고 있다. 그러나 해양 연구시설·장비 중, 환경자료 수집 및 시료채취 등에 사용하는 다양한 종류의 현장 관측장비들을 현재의 국가연구시설·장비 표준분류체계로 분류하여 관리하는 데 어려움이 있다. 한국해양과학기술원의 경우 미분류상태로 적절히 관리되지 않는 연구시설·장비가 약 30% 정도이다. 본 연구에서는 해양 연구시설·장비를 특성에 따라 중분류군 7개와 소분류군 36개로 분류하고, 국가연구시설장비 표준분류체계에 의해 해양 연구시설·장비를 효율적으로 관리하기 위해 '환경관측/분석장비'라는 대분류군을 국가연구시설장비 표준분류체계에 추가하기를 제안한다. 그리고 해양 연구시설·장비 중 실험실에서 운영하는 장비들은 기존의 국가연구시설장비 표준분류체계에 따라 분류할 것을 제안한다. 이를 통하여 우리나라 전체의 해양관련 연구시설·장비를 체계적으로 분류하여 효과적으로 관리할 수 있을 것으로 기대한다.