• Title/Summary/Keyword: Network Data Analysis

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Real-Time Characteristic Analysis of a DCS Communication Network for Nuclear Power Plants (원자력 발전소 디지털 제어 시스템을 위한 네트워크의 실시간 특성 해석)

  • Lee, Sung-Woo;Kim, Seok-Gon;Song, Seong-Il
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.797-801
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    • 2003
  • In this paper, a real-time communication method using a PICNET-NP (Plant Instrumentation and Control Network for Nuclear Power plant) is proposed with an analysis of the control network requirements of DCS (Distributed Control System) in nuclear power plants. The method satisfies deadline in case of worst data traffics by considering aperiodic and periodic real-time data and others.

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Development of Discriminant Analysis System by Graphical User Interface of Visual Basic

  • Lee, Yong-Kyun;Shin, Young-Jae;Cha, Kyung-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.447-456
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    • 2007
  • Recently, the multivariate statistical analysis has been used to analyze meaningful information for various data. In this paper, we develope the multivariate statistical analysis system combined with Fisher discriminant analysis, logistic regression, neural network, and decision tree using visual basic 6.0.

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Identification of sentiment keywords association-based hotel network of hotel review using mapper method in topological data analysis (Topological Data Analysis 기법을 활용한 호텔 리뷰데이터의 감성 키워드 기반 호텔 관계망 구축)

  • Jeon, Ye-Seul;Kim, Jeong-Jae
    • The Korean Journal of Applied Statistics
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    • v.33 no.1
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    • pp.75-86
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    • 2020
  • Hotel review data can extract various information that includes purchasing factors that lead to consumption, advantages, and disadvantages for hotels. In particular, the sentiment keyword of the review data helps consumers understand the pros and cons of hotels. However, it is not efficient for consumers to read a large number of reviews. Therefore, it is necessary to offer a summary review to customers. In this study, we suggest providing summary information on sentiment keywords association as well as a network of hotels based on sentiment keywords. Based on a sentiment keyword dictionary, the extracted sentiment keywords associations construct the hotel network through topological data analysis based mapper. This hotel network allows a consumer to find some hotels associated with specific sentiment keywords as well as recommends the same related hotels. This summary information provides users with a summarized emotional assessment of hotels and helps hotel marketing teams understand consumers' perceptions of their hotel.

Eight Confluent Acupoint Combinations Patterns: Data Mining and Network Analysis (데이터마이닝과 네트워크분석을 통한 팔맥교회혈의 배합 패턴 연구)

  • Min-Jeong Kwon;Da-Eun Yoon;Heeyoung Moon;Yeonhee Ryu;In-Seon Lee;Younbyoung Chae
    • Korean Journal of Acupuncture
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    • v.40 no.4
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    • pp.177-183
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    • 2023
  • Objectives : One of the crucial combinations of acupoints for treating various disorders involves the Eight Confluent acupoints. The present study aims to investigate the selection patterns of the Eight Confluent acupoints in clinical trials and determine the most frequent pairings through network analysis. Methods : The frequencies of the Eight Confluent acupoints were extracted from the Acusynth database, which includes data from 421 clinical investigations. We examined the degree distribution, eigenvector centrality, proximity centrality, and betweenness centrality of these acupoint combinations using network analysis. Results : Data mining revealed that among the Eight Confluent acupoints, PC6 and TE5 were the most commonly applied in the treatment of 30 disorders. Additionally, we identified the most frequently co-occurring pairs of Eight Confluent acupoints by network analysis which included PC6-GV20, SP4-GV4, LU7-LI4, TE5-PC7, GB41-SP6, KI6-BL62, and SI3-BL62. Conclusions : Through the application of data mining and network analysis, we have elucidated the selection patterns and combinations of the Eight Confluent acupoints. These findings provide valuable insights that can enhance doctors' understanding of clinical database-driven Eight Confluent acupoint selection patterns.

A Study on the Trend of Collaborative Research Using Korean Health Panel Data: Focusing on the Network Structure of Co-authors (한국의료패널 데이터를 활용한 공동연구 동향 분석: 공동 연구자들 연결망 구조를 중심으로)

  • Um, Hyemi;Lee, Hyunju;Choi, Sung Eun
    • Journal of Information Technology Applications and Management
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    • v.25 no.4
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    • pp.185-196
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    • 2018
  • This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.

Performance Analysis of an Integrated Voice/Data Packet Communication Network with Window Flow Control (Window Flow 제어기능을 가진 음성/데이타 패킷통신망의 성능해석)

  • 손수현;은종관
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.11 no.4
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    • pp.227-236
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    • 1986
  • In this paper, an integrated voice/data packet network with window flow control is modeled by a colsed multichain queueing system, and its performance is analyzed by the mean value analysis method. Particularly, for the analysis of a packet network having various kinds of messages with different priority classes, we introduce an approach based on the mean value analysis and the concept of effective capacity. By the mathematical analysis and computer simulation, we obtain the following network statistics in the steady state: Mean buffer occupancy at each node, utilization of link throughput of a virtual channel, and mean delay time of each message. Our iterative analysis method can predict the link data status in most cases within about 10 percent of accurady, and the statistics of voice messages and external data within 5 percent as compared to simulation results.

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Design and Construction of High Speed Data Communication Network Using FDDI and Frame Realy (FDDI와 프레임 릴레이를 이용한 고속 데이터 통신망 설계 및 구축)

  • 김도현
    • Journal of the military operations research society of Korea
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    • v.23 no.2
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    • pp.171-191
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    • 1997
  • In this paper, we design and construct a high speed LAN(Local Area Network) using FDDI(Fiber Distributed Data Interface) and Frame Relay in order to support our multimedia communication services. A program of this communication network is divided into requirement analysis, design, establishment and test. First, we propose an optimal communication method that compares various network techniques in the requirement analysis phase. Second, we design the physical network configuration, secure method, and address in the LAN and WAN. Finally, we establish and test the communication devices and lines. Ultimately, we minimized mistakes and satisfied user requirements using this program. We constructed efficiently a high speed data communication network using FDDI and Frame Relay.

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A Study on The Optimization Method of The Initial Weights in Single Layer Perceptron

  • Cho, Yong-Jun;Lee, Yong-Goo
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.331-337
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    • 2004
  • In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.

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A Neural Network Model for Bankruptcy Prediction -Domestic KSE listed Bankrupted Companies after the foreign exchange crisis in 1997 (인공신경망을 이용한 기업도산 예측 - IMF후 국내 상장회사를 중심으로 -)

  • Jeong Yu-Seok;Lee Hyun-Soo;Chae Young-Il;Suh Yung-Ho
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2004.04a
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    • pp.655-673
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    • 2004
  • This paper is concerned with analysing the bankruptcy prediction power of three models: Multivariate Discriminant Analysis(MDA ), Logit Analysis, Neural Network. The after-crisis bankrupted companies were limited to the research data and the listed companies belonging to manufacturing industry was limited to the research data so as to improve prediction accuracy and validity of the model. In order to assure meaningful bankruptcy prediction, training data and testing data were not extracted within the corresponding period. The result is that prediction accuracy of neural network model is more excellent than that of logit analysis and MDA model when considering that execution of testing data was followed by execution of training data.

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Exploring Community Structure and Function with Network Analysis: a Case Study of Cheonggye Stream (생태계 네트워크 분석을 이용한 생물 군집의 구조와 기능에 대한 연구: 청계천을 사례로)

  • Lee, Minyoung;Kim, Yongeun;Cho, Kijong
    • Korean Journal of Environmental Biology
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    • v.36 no.3
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    • pp.370-376
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    • 2018
  • It is important to consider interaction between species in understanding structure and function of the biological community. Current ecological issues such as climate change and habitat loss emphasize the significance of the concept of species interaction in that varying species' interaction across environmental gradients may lead to altered ecological function and services. However, most community studies have focused on species diversity through analysis of quantitative indices based on species composition and abundance data without considering species interactions in the community. 'Ecological network analysis' based on network theory enables exploration of structural and functional properties of ecosystems composed of various species and their interactions. In this paper, network analysis of Cheonggye stream as a case study was presented to promote uses of network analysis on ecological studies in Korea. Cheonggye stream has a simple biological structure with link density of 1.48, connectance 0.07, generality 4.43, and vulnerability 1.94. The ecological network analysis can be used to provide ecological interpretations of domestic long-term monitoring data and can contribute to conserving and managing species diversity in ecosystems.