• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.9-16
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• 2016

In this paper, we present a performance evaluation agent based on fuzzy cluster analysis and validity measures. The proposed agent is consists of three modules, fuzzy cluster analyzer, performance evaluation measures, and feature ranking algorithm for feature selection step in CAD system. Feature selection is an important step commonly used to create more accurate system to help human experts. Through this agent, we get the feature ranking on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. Also we design a CAD system incorporating the agent and apply five different feature combinations to the system. Experimental results proposed approach has higher classification accuracy and shows the feasibility as a diagnosis supporting tool.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.241-251
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• 2022

화장품 및 뷰티산업에서 고객의 피부상태 진단과 관리는 중요한 필수기능이다. 소셜미디어 환경이 사회 전 분야에 확산되고 일반화되면서 피부 상태의 진단과 관리에 대한 다양하고 섬세한 고민과 요구 사항의 질문과 답변의 상호작용이 소셜미디어 커뮤니티에서 활발하게 다루어지고 있다. 그러나 소셜미디어 정보는 매우 다양하고 비정형적인 방대한 빅데이터이므로 적절한 피부상태 정보분석과 인공지능 기술을 접목한 지능화된 피부상태 진단 시스템이 필요하다. 본 논문에서는 소셜미디어의 텍스트 분석정보를 학습데이터로 가공하여 고객의 피부상태를 지능적으로 진단 및 관리하기 위한 피부상태진단시스템 SCDIS를 개발하였다. SCDIS에서는 딥러닝 기계학습 방법인 인공신경망 기술을 사용하여 자동적으로 피부상태 유형을 진단하는 인공신경망 모델 AnnTFIDF을 빌드업하여 사용하였다. 인공신경망 모델 AnnTFIDF의 성능은 테스트샘플 데이터를 사용하여 분석되었으며, 피부상태 유형 진단 예측 값의 정확성은 약 95%의 높은 성능을 나타내었다. 본 논문의 실험 및 성능분석결과를 통하여 SCDIS는 화장품 및 뷰티산업 분야의 피부상태 분석 및 진단 관리 과정에서 효율적으로 사용 가능한 지능화된 도구로 평가할 수 있다. 본 논문에서 제안된 시스템은 소셜미디어 기반의 새로운 환경에서 화장품 및 피부미용에 대한 사용자의 요구를 체계적으로 파악하고 진단하는 기초 기술로 사용 가능할 것이다. 그리고 이 연구는 새로운 기술 트렌드인 맞춤형 화장품제조와 소비자중심의 뷰티산업기술 수요를 해결하기 위한 기초 연구로 사용될 수 있을 것이다.

• Nuclear Medicine and Molecular Imaging
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• 제42권sup1호
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• pp.166-171
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• 2008

PET of the cerebral metabolic rate of glucose is increasingly used to support the clinical diagnosis in the examination of patients with suspected major neurodegenerative disorders, such as Alzheimer's disease. $^{18}F-FDG$ PET has been reported to have high diagnostic performance, especially, very high sensitivity in the diagnosis and clinical assessment of therapeutic efficacy. According to clinical research data hitherto, $^{18}F-FDG$ PET is expected to be an effective diagnostic tool in early and differential diagnosis of Alzheimer's disease. Since 2004, Medicare covers $^{18}F-FDG$ PET scans for the differential diagnosis of fronto-temporal dementia (FTD) and Alzheimer's disease (AD) under specific requirements; or, its use in a CMS approved practical clinical trial focused on the utility of $^{18}F-FDG$ PET in the diagnosis or treatment of dementing neurodegenerative diseases.

• 한국안전학회지
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• 제18권1호
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• pp.50-55
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• 2003

This paper presents an intelligent computer system, which can easily diagnose electrical fire causes, without the help of human experts of electrical fires diagnosis. For this system, a database is built with facts and rules driven from real electrical fires, and an intellectual database system which even a beginner can diagnose fire causes has been developed, named as an Electrical Fire Causes Diagnosis System : EFCDS. The database system has adopted, as an inference engine, a mixed reasoning approach which is constituted with the rule-based reasoning and the case-based reasoning. The system for a reasoning model was implemented using Delphi 3, one of program development tools, and Paradox is used as a database building tool. To verify effectiveness and performance of this newly developed diagnosis system, several simulated fire examples were tested and the causes of fire examples were detected effectively by this system. Additional researches will be needed to decide the minimal significant level of the solution and the weighting level of important factors.

• 한국소음진동공학회논문집
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• 제27권2호
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• pp.189-194
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• 2017

An compressor that is combined with the rotor and pneumatic technology has been researching for the performance of pressure. However, the control of operations, an accurate diagnosis and the maintenance of compressor system are limited though the simple structure of compressor and compression are advantaged to reduce the energy. In this paper, the characteristic of the compressor operating under the normal or abnormal condition is realized. and the efficient diagnosis method is proposed through feature based analysis. Also, by using the GA (genetic algorithm) and SVM (support vector machine) of machine learning, the performance of feature analysis is conducted. Different misalignment mode of learning data for compressor is evaluated using the fault simulator. Therefore, feature based analysis is conducted considering misalignment mode of the compressor and the possibility of a diagnosis of misalignment is evaluated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.224-227
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• 1989

In this paper, The implementation of modular neural net for fault diagnosis in power system is presented. Until now, there have been many researches on expert system for fault diagnosis. On expert system, a lot of time for searching goal is needed. But, neural net processes with high speed, as it has parallel distributed processing structure. So neural net has good performance in on-line fault diagnosis. For fault diagnosis in large power system, the constitution of modular neural net with partition of large power system is presented.

• 대한전기학회논문지:전력기술부문A
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• 제52권2호
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• pp.99-106
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• 2003

In this paper, an intelligent fault location and diagnosis system is proposed. The proposed system identifies the fault location in two-step procedure. The first step identifies candidates of fault location using an fault distance calculation using an iterative method. The second step is diagnosis the actual fault location in the candidates by comparing the current waveform patterns with the expected operation of the protective devices and considering the interrupted load after the operation protective device. The simulations results in the case study demonstrates a good performance of the proposed fault location and diagnosis system.

• 산업경영시스템학회지
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• 제32권4호
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• pp.215-222
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• 2009

Human voice reacts very sensitively to human's minute physical condition. For instance, human voice disorders affect patients profoundly especially in the case of Parkinson's disease. Acoustic tools such as MDVP, can function as an equipment that measures various voice in different objects. Many different approaches have been applied for analyzing the voice disorders for diagnosis of Parkinson's disease. According to the voice data of suspected Parkinson's patients from UCI Machine Learning Repository, it is reported to have 23 people with Parkinson's disease and 8 healthy people. Applying Mahalanobis Taguchi System (MTS) for diagnosis of Parkinson's disease, the correct diagnosis performance is compared to previous research results.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.136-144
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• 2021

Railroad Systems, which are national infrastructure industries, cause unexpected property and human damage if they fail to function while operating. Accordingly, railroad facilities supporting the railroad system are areas where high reliability and safety are required. However, it is time for systematic and scientific maintenance to be taken away from the traditional maintenance methods, as the nation's railroad facilities are now aging seriously. The purpose of this study was to secure the safety and reliability of the aging railroad communication facilities and to improve their performance. The research subjects were selected as a precision diagnosis process for railroad communication facilities, and improvement points were derived through detailed precision diagnosis process analysis. It is deemed that this study can contribute based on securing stability, improving reliability, and continuous improvement of railroad communication facilities should be conducted in the operation of the entire railroad system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.994-999
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• 2008

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Because vibration diagnosis can avoid sudden breakdown of machine and reduce the maintenance costs. In the factory, Air-Compressor which can affect the performance and capacity of output is important machine. Therefore, in this paper, The measuring and analyzing is carried out for air-compressor in order to the factor of resonance and resonance avoidance for air-compressor. The result of diagnosis and solution is discussed in this paper.