• Title/Summary/Keyword: 컴퓨터지원진단

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Design and Implementation of a Remote Control Program (원격 제어 프로그램의 설계 및 구현)

  • Lee, Chul;Kim, Sang-Chul;Kim, Joong-Hwan
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10a
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    • pp.433-435
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    • 2001
  • 원격 제어 프로그램은 파일전송 관리, 고장난 컴퓨터의 원격 진단 및 A/S, 시스템 관리자의 원격지 컴퓨터관리, 원격 강의 시스템 등 다양한 곳에 이용되고 있다. 본 논문에서는 일대다 접속모델을 지원하는 원격 제어 프로그램의 구조와 동작원리를 기술한다. 여기서 일대다 접속이란 한 컴퓨터의 화면을 원격지에 있는 다수 컴퓨터들이 공유 및 제어하도록 하는 것을 말한다. 또한, 프로그램의 성능에 주요한 요인이 되는 화면 갱신 이벤트 처리와 마우스 움직임 이벤트 처리에 대한 효율적인 방법을 제안한다.

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Improvement of Sparse Representation based Classifier using Fisher Discrimination Dictionary Learning for Malignant Mass Detection (피셔 분별 사전학습을 이용해 개선된 Sparse 표현 기반 악성 종괴 검출)

  • Kim, Seong Tae;Lee, Seung Hyun;Min, Hyun-Seok;Ro, Yong Man
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.558-565
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    • 2013
  • Mammography, the process of using X-ray to examine the woman breast, is the one of the effective tools for detecting breast cancer at an early state. In screening mammogram, Computer-Aided Detection(CAD) system helps radiologist to diagnose cases by detecting malignant masses. A mass is an important lesion in the breast that can indicate a cancer. Due to various shapes and unclear boundaries of the masses, detecting breast masses is considered a challenging task. To this end, CAD system detects a lot of regions of interest including normal tissues. Thus it is important to develop the well-organized classifier. In this paper, we propose an enhanced sparse representation (SR) based classifier using Fisher discrimination dictionary learning. Experimental results show that the proposed method outperforms the existing support vector machine (SVM) classifier.

Application of Ontology technology for Adaptive Learning in e-Learning (적응형 학습을 위한 온톨로지 기술의 적용 방안)

  • Choi, Sook-Young
    • The Journal of Korean Association of Computer Education
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    • v.12 no.6
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    • pp.53-67
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    • 2009
  • In this study we surveyed the characteristics of the Semantic Web and ontology technology, analyzing the studies which applied ontology to e-Learning. In addition, we investigated the models which should be considered in the adaptive learning, analyzing the existing adaptive learning systems. On the basis of the analysis of them, we sought the ways to apply ontology for supporting the adaptive learning in the e-learning system, designing an ontology-based adaptive learning system. The system made up for the weak points of the existing ontology-based learning systems. That is, it appropriately diagnoses learners' knowledge level of learning concepts, classifying the learning styles in detail, and providing their corresponding learning methods and content. By adapting the learning content to the learners' individual learning style and knowledge level, this system would support their learning more efficiently and more effectively.

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Multimedia Expert System for a Nuclear Power Plant Accident diagnosis using a Fuzzy Inference Method (퍼지 추론 방법을 이용한 원자력 사고진단 시스템을 위한 멀티미디어 전문가 시스템)

  • Lee, Sang-Beom;Lee, Seong-Ju;Lee, Mal-Rye
    • Journal of the Korea Society of Computer and Information
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    • v.6 no.1
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    • pp.14-24
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    • 2001
  • The huge and complicated plants such as nuclear power stations are likely to cause the operators to make mistakes due to a variety of inexplicable reasons and symptoms in case of emergency. Thats why the prevention system assisting the operators is being developed for. First of all. I suggest an improved fuzzy diagnosis. Secondly. I want to demonstrate that a classification system of nuclear plants accident investigating the causes of accidents foresees possible problems. and maintains the reliability of the diagnostic reports in spite of improper working in part. In the event of emergency in a nuclear plant, a lot of operational steps enable the operators to find out what caused the problems based on an emergent operating plan. Our system is able to classify their types within twenty to thirty seconds. As so, we expect the system to put don the accidents right after the rapid detection of the damage control-method concerned.

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A Deign and Implementation of Data Display for Distributed Diagnosis/ Correction System (분단 진단/ 교정 시스템을 위한 데이터 디스플레이에 관한 설계 및 구현)

  • 정연정;조영욱;이단형
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.142-144
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    • 1998
  • 분산 처리 시스템은 여러 대의 컴퓨터에 분산된 프로그램들이 상호 통신을 통해 협력하면서 작업을 수행하는 시스템이다 .본 논문은 분산 처리시스템의 소프트웨어 개발을 효율적으로 지원하는 유니부(Uniview)를 개발하는 데 있어서 디스플레이 데이터의 설계 및 운용 방안을 제시한다. 디스플레이 데이터는 디버깅 작업과 관련된 정보를 효과적으로 페치, 저장할 수 있는 구조가 되어야 한다. 제안된 디스플레이 데이터 구조와 운용 방법은 디버깅 작업의 흐름에 따라 데이터를 생성, 유지하며 필요한 데이터만을 검사하여 효율적으로 운용한다.

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The Development of e-Learning System for Science and Engineering Mathematics using Computer Algebra System (컴퓨터 대수 시스템을 이용한 이공계 수학용이러닝 시스템 개발)

  • Park, Hong-Joon;Jun, Young-Cook;Jang, Moon-Suk
    • The KIPS Transactions:PartA
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    • v.14A no.6
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    • pp.383-390
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    • 2007
  • This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

Development of a Real-Time Control & Management System with In-Vitro Diagnostic Medical Device for Dengue Fever (실시간 뎅기열 관리를 위한 관제시스템 개발)

  • Changsun, Ahn;Yongho, Park;Jungdae, Moon;Jongchan, Park;Youngkon, Seo;Allen, Sohn;Yoonjong, Choi;Yanghwa, Ha;Bongsu, Jung;Youngjoo, Kim
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.2
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    • pp.77-84
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    • 2023
  • Dengue virus transmission is a viral infection disease between humans and Aedes mosquitoes. Dengue is ubiquitous throughout the tropics and subtropical zones, where 1/3 of the global population live. The weather in Korea is also changing to subtropical weather, resulting in increased vulnerable Korean population to dengue virus transmission. It is important to control and prevent the dengue risk with track-recording & monitoring system. It is also required to have the control system to treat and monitor dengue patients with various cases such as regions, ages, genders according to the track-record of the disease. In this paper, we developed a Dengue Control & Prevention System, which can monitor and control dengue outbreaks in real-time with in-vitro diagnostic devices. Dengue Control & Prevention System is composed of in-vitro diagnostic device, which is a fluorescent immunoassay, and real-time monitoring system. In the future, we expect that our Dengue Control & Prevention System can be upgraded to have various disease information from Korea Disease Control and Prevention Agency for government policies and diseases control in Korea.

An Integrated Fault Diagnosis System for Power System Devices using Meta-inference and Fuzzy Reasoning (메타-인퍼런스와 퍼지추론을 이용한 송변전 설비의 통합 고장진단 전문가 시스템)

  • 이흥재;임찬호;김광원
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.12 no.2
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    • pp.38-44
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    • 1998
  • This paper presents an integrated fault diagnosis expert system to assist SCADA operators in local control centers which controls unmanned distribution substations in a power system. The proposed system diagnoses various faults occurred in both substation devices and transmission devices. The system can be easily installed without disturbing main SCADA system. The system simply shares the dynamic information including alarms with main SCADA using dual data link interface. And the proposed expert system utilizes the fuzzy reasoning process in order to consider the uncertainty factor. The system is developed using a low cost personal computer owing to the special modular programming and the meta-inf!'lrence structure. Case studies showed a promising possibility.bility.

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A Study on the Domain Discrimination Model of CSV Format Public Open Data

  • Ha-Na Jeong;Jae-Woong Kim;Young-Suk Chung
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.129-136
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    • 2023
  • The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

Classification of the Diagnosis of Diabetes based on Mixture of Expert Model (Mixture of Expert 모형에 기반한 당뇨병 진단 분류)

  • Lee, Hong-Ki;Myoung, Sung-Min
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.11
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    • pp.149-157
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    • 2014
  • Diabetes is a chronic disease that requires continuous medical care and patient-self management education to prevent acute complications and reduce the risk of long-term complications. The worldwide prevalence and incidence of diabetes mellitus are reached epidemic proportions in most populations. Early detection of diabetes could help to prevent its onset by taking appropriate preventive measures and managing lifestyle. The major objective of this research is to develop an automated decision support system for detection of diabetes using mixture of experts model. The performance of the classification algorithms was compared on the Pima Indians diabetes dataset. The result of this study demonstrated that the mixture of expert model achieved diagnostic accuracies were higher than the other automated diagnostic systems.