• Journal of Intelligence and Information Systems
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• v.2 no.1
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• pp.1-9
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• 1996

사출 성형의 초보자도 이용할 수 있으며 사출 성형기의 이력 관리를 할 수 있는, 플라스틱 사출 성형의 진단과 불량대책을 위한 지식 기반 전문가 시스템을 ATR-IM 이라는 범용 전문가시스템 쉘을 이용하여 구현하였다. 지식베이스(knowledge base)는 수지 회사와 관련 서적, 전문가의 경험을 토대로 구축하였으며, 구현된 시스템은 크게 사출 공정 조건 설정 시스템, 사출기 ID에 따른 이력 관리 시스템, 사출성형 불량진단 시스템의 세부분으로 나누어 구성하였다. 본 연구를 통해 제안된 방법에 따라 업체별 사출기 성능에서 오는 공정 조건값의 차이를 사출공정 조건값의 저장에 의해 고려할 수 있으며, 불량 해결에 대한 전문가시스템이 추론 순서 결정을 경험적 확률에 따라 이루어지도록 함으로써 현장에서의 작업 환경을 고려한 전문가시스템이 되도록 하였다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.304-305
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• 2007

본 논문에서는 진단부분에서 서버를 중심으로 받은 정보를 능동적으로 해석하고 이상 유무에 따른 차단 역할 수행하도록 하는 지능형 차단 시스템에 대한 알고리즘 개발을 목표로 하고 있다. 제안하고자 하는 분류 알고리즘이란, 저압 배선에서 받은 신호에 대한 해석과 더불어 이를 각 이상 정도에 따라 분류하는 것을 말한다. 일반적으로, TFDR을 통해 알아 낼 수 있는 이상 유무의 종류는 damage, open 그리고 short 등이다. 도선 이상의 종류 및 특성에 따른 분류를 위하여, 알고리즘 개발을 위한 사전 이론 조사 및 개요 구성을 목표로 하고 있다. 또한, 기존의 통신 선 상에서 이루어진 결과를 토대로 한 퍼지 분류 규칙 생성 및 분류 알고리즘 개발 역시 앞으로 수행 될 예정이며, 이를 통한 지능형 차단 시스템 구축이 최종 목표이다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.258-263
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• 2005

Haplotype-based analysis using high-density SNP markers have gained a great attention in evaluating genes in gene analysis and various clinical situations. However, there has been no research on disease diagnostic modeling based on SNPs analysis to our knowledge. The purpose of this study is to explore how knowledge discovery techniques are applied in medical informatics area and proposes a Case Based Reasoning (CBR) technique for diagnosis of gastric caner using Single Nucleotide Polymorphism(SNP).

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1428-1429
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• 2007

The paper used to the Neral Netwok for a forecasting conservation system. A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. The true power and advantage of neural network lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Netwok is will play an important role for insulation diagnosis system of real site GIS and power equipment using Dry-Air gas.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.369-376
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• 2001

도심지에서 자주 발생되는 교통체증의 문제를 효과적으로 해결하기 위해서는 교통 상황을 신속하고 정확하게 진단하며, 이를 바탕으로 최대한의 효율을 얻을 수 있도록 교통 신호체계를 수립하는 것이 중요하다. 본 논문에서는 '병렬기반 미시적 교통류 시뮬레이션 시스템'을 활용하여 교통상황을 정확하게 모델링한 결과정보를 추출하고, 이를 바탕으로 교통상황을 종합적으로 진단할 수 있는 '교통류 시뮬레이션 평가 및 진단 시스템'을 제시한다. 교통상황에 대한 시뮬레이션 결과정보를 쉽게 분석할 수 있는 교통류 시뮬레이션 평가 및 진단 시스템을 개발하기 위하여, 교통상황의 해석에 필요한 제반 문제와 원인들의 인과관계를 파악하여 규칙화하고, 이를 바탕으로 규칙 기반추론 기법을 적용할 수 있도록 전문가시스템을 도입하였다. 또한 효율적인 진단을 위하여 시뮬레이션 결과정보로부터 구한 정량적인 각종 평가 지표를 정성적인 측면에서 재평가하여 사유할 수 있도록 fuzzy 기술을 도입하였다. 아울러 교통류 시뮬레이션 평가 및 진단 시스템의 결과는 최적의 신호체계를 수립하는데 활용될 수 있도록 하였다. 서울광역시 과천 주변의 8 개 교차로를 포함하는 교통망에 대한 교통정보를 바탕으로 실험해 봄으로써 사용자가 복잡한 교통망에 대해 보다 효과적으로 교통흐름을 분석하여 정체원인을 실시간으로 판단할 수 있는 가능성을 보여준다.

• Clinical Endoscopy
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• v.51 no.6
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• pp.547-551
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• 2018

Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine the lesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reported based on artificial intelligence for computer-aided diagnosis. Recently, deep learning-based approaches have been applied to many possible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recent deep learning-based approaches for clinical applications, we present the current status and future direction of artificial intelligence for capsule endoscopy.

• ETRI Journal
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• v.43 no.1
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• pp.31-39
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• 2021

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.

• Journal of The Korea Institute of Healthcare Architecture
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• v.22 no.4
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• pp.7-17
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• 2016

Purpose: As our population ages and becomes an elderly society the number of elderly care hospitals is rapidly increasing. Because physical functions and spatial perception in the elderly decrease with age, these hospitals require more systematic and intelligent space designs. The design of these spaces are even more complex because they must accommodate medical programs to treat various different diseases and ailments and also because there are many first time patients and irregular short term patients that seek out outpatient treatment services. Also by analyzing the spatial configuration systems and systematic relationships between each of the functional spaces of the outpatient treatment service departments for hospitals specialized in care for the elderly by focusing on the hallway and corridor systems of these hospitals, the according characteristics and trends were examined. Methods: Based on preceding research, the types of hallway and corridor systems of these hospitals were categorized into five types, including gallery corridors, middle corridors, hall-type, mixed type and cyclic type corridors, and into six types according to function including by medical diagnosis, patient registration, examination, administration and convenience and shared common space to derive any interconnecting relationships between the corridor systems. Also by comprehensively examining the types and combined utilization of the corridor types and the integration and the intelligibility of the space syntax, any trends within the corridor system were derived. The elderly care hospitals examined in this research study were twelve hospitals that opened after the year 2000 in Korea with more that 150 sick beds with areas larger than $1000m^2$ and with all outpatient medical service related rooms located entirely on a single floor of the hospital. Results: The following results could be confirmed based on this research study. 1) The spaces where medical diagnosis and examination occurred were adjacent, and the movement lines for first time patients and re-visiting patients were taken into consideration by separating the treatment space. 2) This research study confirmed that the larger the size of the hospital was, there were more detailed categorizations of treatment services and that there was a tendency for treatment areas to be separated and independent from examination areas. 3) There was a tendency for integration and intelligibility to decrease the more complex and diverse the combination of hall types designed into the corridor systems of these hospitals was. cyclic type corridors dramatically decreased the intelligibility of the corridor systems of these hospitals. 4) The priority rank of these spaces were confirmed to be highest in the order of registration, diagnosis, examination, treatment, administration and shared common spaces. However it was confirmed for the local integration that the diagnosis scope had the highest priority rank. Implications: There were exceptional cases confirmed where the number of unit spaces did not have an absolute effect on integration and intelligibility. These results can be interpreted to mean that this can be overcome through efficient architectural planning.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.154-159
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• 2007

Wake distribution data of stem flow fields have been accumulated systematically by model tests. If the correlation between geometrical hull information and wake distribution is grasped through the accumulated data, this correlation can be helpful to designing similar ships. In this paper, Neuro-Fuzzy system that is emerging as a new knowledge over a wide range of fields nowadays is tried to estimate the wake distribution on the propeller plan. Neuro-Fuzzy system is well known as one of prospective and representative analysis method for prediction, classification, diagnosis of real complicated world problem, and it is widely applied even in the engineering fields. For this study three-dimensional stern hull forms and nominal wake values from a model test ate structured as processing elements of input and output layer, respectively. The proposed method is proved as an useful technique in ship design by comparing measured wake distribution with predicted wake distribution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.539-542
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• 2003

A motor is the workhorse of our industry. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. Different internal motor faults (e.g., inter-turn short circuits, broken bearings, broken rotor bars) along with external motor faults (e.g., phase failure, mechanical overload, blocked rotor) are expected to happen sooner or later. This paper introduces the fault detection technique of induction motors based upon the stator current. The fault motors have rotor bar broken or rotor unbalance defect, respectively. The stator currents are measured by the current meters and stored by the time domain. The time domain is not suitable to represent the current signals, so the frequency domain is applied to display the signals. The Fourier Transformer is used for the conversion of the signal. After the conversion of the signals, the features of the signals have to be extracted by the signal processing methods like a wavelet analysis, a spectrum analysis, etc. The discovered features are entered to the pattern classification model such as a neural network model, a polynomial neural network, a fuzzy inference model, etc. This paper describes the fault detection results that use wavelet decomposition. The wavelet analysis is very useful method for the time and frequency domain each. Also it is powerful method to detect the features in the signals.