• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.229-231
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• 2006

NLPCA(Nonlinear Principal Component Analysis) is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA operates by a feedforward neural network called AANN(Auto Associative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA is presented. To verify its applicability, simulation study on the data supplied from sensor network is executed.

• KIEE International Transactions on Electrophysics and Applications
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• 제3C권4호
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• pp.130-135
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• 2003

This study describes neural network based dissolved gas analysis using composition patterns of gas concentrations for transformer fault diagnosis. DGA samples were gathered from related literatures and classified into six types of faults and then a neural network was trained using the DGA samples. Diagnosis tests were performed by the trained neural network with DGA samples of serviced transformers, fault causes of which were identified by actual inspection. Diagnosis results by the neural network were in good agreement with actual faults.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.109-118
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• 2023

Energy awareness is an essential design flaw in wireless sensor network. Clustering is the most highly regarded energy-efficient technique that offers various benefits such as energy efficiency and network lifetime. Clusters create hierarchical WSNs that introduce the efficient use of limited sensor node resources and thus enhance the life of the network. The goal of this paper is to provide an analysis of the various energy efficient clustering algorithms. Analysis is based on the energy efficiency and network lifetime. This review paper provides an analysis of different energy-efficient clustering algorithms for WSNs.

• 한국농공학회논문집
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• 제58권3호
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• pp.13-19
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• 2016

Element-focused network analysis method for truss structure is proposed. The propagation process of loads from external loads to connected other elements is similar to that of connections between nodes in accordance with attachment rule in a network. Here nodes indicate elements in a truss structure and edges represent propagated loads. Therefore, the flows of loads in a truss structure can be calculated using the network analysis method, and consequently the structure can also be analyzed. As a first step to analyze a truss structure as a network, we propose a local load transfer rule in accordance with the topology of elements, and then analyze the loads of the truss elements. Application of this method reveal that the internal loads and reactions caused by external loads can be accurately estimated. Consequently, truss structures can be considered as networks and network analysis method can be applied to further complex truss structures.

• Genomics & Informatics
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• 제5권3호
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• pp.133-136
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• 2007

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

• 무역학회지
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• 제46권1호
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• pp.113-134
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• 2021

This study analyzed the centrality of the GVCs network and the value-added-based production structure of the electrical and electronic industries using ADB-MIRO and social network analysis methods. According to the analysis, the centrality and power of the GVSc intermediate goods network were differentiated into China, the United States, and the EU due to the advancement of industrial structure in Asia. In the 2000 network, the United States and Japan had a very strong influence in all aspects, including connectivity and strength. However, in 2017, China's power index rose to number one among 62 countries in the network. Furthermore, this study presented strategic implications of the Korean electrical and electronic industries to respond to the reorganization of GVSs based on the analysis results.

• 정보관리학회지
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• 제31권4호
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• pp.49-68
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• 2014

본 연구의 목적은 국내 학술논문 데이터베이스에서 검색한 언어 네트워크 분석 관련 53편의 국내 학술논문들을 대상으로 하는 내용분석을 통해, 언어 네트워크 분석 방법의 기초적인 체계를 파악하기 위한 것이다. 내용분석의 범주는 분석대상의 언어 텍스트 유형, 키워드 선정 방법, 동시출현관계의 파악 방법, 네트워크의 구성 방법, 네트워크 분석도구와 분석지표의 유형이다. 분석결과로 나타난 주요 특성은 다음과 같다. 첫째, 학술논문과 인터뷰 자료를 분석대상의 언어 텍스트로 많이 사용하고 있다. 둘째, 키워드는 주로 텍스트의 본문에서 추출한 단어의 출현빈도를 사용하여 선정하고 있다. 셋째, 키워드 간 관계의 파악은 거의 동시출현빈도를 사용하고 있다. 넷째, 언어 네트워크는 단수의 네트워크보다 복수의 네트워크를 구성하고 있다. 다섯째, 네트워크 분석을 위해 NetMiner, UCINET/NetDraw, NodeXL, Pajek 등을 사용하고 있다. 여섯째, 밀도, 중심성, 하위 네트워크 등 다양한 분석지표들을 사용하고 있다. 이러한 특성들은 언어 네트워크 분석 방법의 기초적인 체계를 구성하는 데 활용할 수 있을 것이다.

• International Journal of Knowledge Content Development & Technology
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• 제8권4호
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• pp.75-98
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• 2018

In this study, the network analysis of researchers, institutions, and research principal agent was conducted to understand structure characteristics of international cooperation research project implemented from 1997 to 2018. The network of researchers and institutions were decentralized structure. On the other hands, the network of research principal agent was centralized structure. The Soul National University is the leading organization of international cooperation research project. In terms of research principal agent, corporation is the leading principal agent. In additions, the results of the network centroid analysis of the researchers and institutions were correlated with the research funds. As a result, it was confirmed that the network centroid of research organization was linearly related to research funds.

• 국제초고층학회논문집
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• 제8권1호
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• pp.49-56
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• 2019

Against the background of the rapid development of the Shanghai Metro network, this paper attempts to establish an analytical approach to evaluate the impact of multiple transport network accessibilities on commercial space use in metro station areas. Ten well-developed metro station areas in central Shanghai are selected as samples. Commercial space floor area and visitors in these areas are collected. Using ArcGIS and Spatial Design Network Analysis, the Shanghai Metro network and road network are modeled to compute diversified transport accessibilities. Evidence from land use and commercial space floor area within a 0-to-500-meter buffer zone of stations is consistent with location and land-use theory: commercial land use is concentrated closer to stations. Correlation analysis suggests that hourly visitors to the shopping mall are mainly influenced by metro network accessibility, while retail stores and restaurants are affected by both metro and pedestrian accessibility.

• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.141-148
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• 2016

In this paper, we propose a topic network analysis approach which integrates topic modeling and social network analysis. We collected 2,039 scientific papers from five top journals in the field of data mining published from 1996 to 2015, and analyzed them with the proposed approach. To identify topic trends, time-series analysis of topic network is performed based on 4 intervals. Our experimental results show centralization of the topic network has the highest score from 1996 to 2000, and decreases for next 5 years and increases again. For last 5 years, centralization of the degree centrality increases, while centralization of the betweenness centrality and closeness centrality decreases again. Also, clustering is identified as the most interrelated topic among other topics. Topics with the highest degree centrality evolves clustering, web applications, clustering and dimensionality reduction according to time. Our approach extracts the interrelationships of topics, which cannot be detected with conventional topic modeling approaches, and provides topical trends of data mining research fields.