• Journal of Information Processing Systems
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• 제13권4호
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• pp.703-715
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• 2017

Mammogram images are sensitive in nature and even a minor change in the environment affects the quality of the images. Due to the lack of expert radiologists, it is difficult to interpret the mammogram images. In this paper an algorithm is proposed for a computer-aided diagnosis system, which is based on the wavelet based adaptive sigmoid function. The cascade feed-forward back propagation technique has been used for training and testing purposes. Due to the poor contrast in digital mammogram images it is difficult to process the images directly. Thus, the images were first processed using the wavelet based adaptive sigmoid function and then the suspicious regions were selected to extract the features. A combination of texture features and gray-level co-occurrence matrix features were extracted and used for training and testing purposes. The system was trained with 150 images, while a total 100 mammogram images were used for testing. A classification accuracy of more than 95% was obtained with our proposed method.

• 한국정보통신학회논문지
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• 제25권10호
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• pp.1279-1286
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• 2021

Electrocardiogram (ECG) 신호는 심장의 이상을 조기에 진단하기 위한 좋은 지표이다. ECG 신호는 사람마다 기준이 되는 정상 신호의 형태가 다르고, 진단에 많은 데이터가 필요하다. 본 논문에서는 ECG 신호 진단을 효율적으로 가속하기 위한 OpenCL을 기반 FPGA-GPU 혼합 계층 적응형 플랫폼을 제안한다. 플랫폼에서 MIT-BIH 부정맥 신호데이터의 19870개 ECG 신호를 진단한 결과 FPGA 가속기는 진단 시간이 1.15s로 소프트웨어로 실행했을 때보다 89.94% 감소하였고, 전력 소모는 84.0% 감소하였다. GPU 가속기는 실행 시간이 소프트웨어 대비 83.56% 감소한 1.87s였으며, 전력 소모는 62.3% 감소하였다. 제안하는 FPGA-GPU 혼합 플랫폼은 FPGA 가속기보다 진단 속도가 느리지만 GPU를 이용하여 상황에 따라 유연한 알고리즘을 동작할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.87-87
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• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• 전기학회논문지
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• 제58권2호
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• pp.342-348
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• 2009

This paper introduces a novel denoising algorithm for the partial-discharge(PD) signals from power apparatuses. The developed algorithm includes three kinds of specific denoising sub-algorithms. The first sub-algorithm uses the fuzzy logic which classifies the noise types in the magnitude versus phase PD pattern. This sub-algorithm is especially effective in the rejection of the noise with high and constant magnitude. The second one is the method simply removing the pulses in the phase sections below the threshold count in the count versus phase pattern. This method is effective in removing the occasional high level noise pulses. The last denoising sub-algorithm uses the grouping characteristics of PD pulses in the 3D plot of the magnitude versus phase versus cycle. This special technique can remove the periodical noise pulses with varying magnitudes, which are very difficult to be removed by other denoising methods. Each of the sub-algorithm has different characteristic and shows different quality of the noise rejection. On that account, a parameter which numerically expresses the noise possessing degree of signal, is defined and evaluated. Using the parameter and above three sub-algorithms, an adaptive complex noise rejection algorithm for the on-line PD diagnosis system is developed. Proposed algorithm shows good performances in the various real PD signals measured from the power apparatuses in the Korean plants.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.518-521
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• 2003

A new measurement system was developed by fault diagnosis system for traction motor using current signal analysis. The motor current signature analysis method is used for traction motor fault diagnosis. The diagnosis system program is constructed by artificial neural networks algorithm, those results from the program are used to train neural networks. The trained neural networks have the ability to compute adaptive results for non-trained inputs, and to calculate very fast due to original parallel structure of neural networks with high accuracy within destined tolerance. This system suggested that available test for checking, the probable extent of aging, and the rate of which aging is taking place.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

• Journal of information and communication convergence engineering
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• 제20권3호
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• pp.153-159
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• 2022

Plain radiographic analysis is the initial imaging modality for suspected small bowel obstruction. Among the many features that affect the diagnosis of small bowel obstruction (SBO), the presence of gas-filled or fluid-filled small bowel loops is the most salient feature that can be automatized by computer vision algorithms. In this study, we compare three frequently applied pixel-clustering algorithms for extracting gas-filled areas without human intervention. In a comparison involving 40 suspected SBO cases, the Possibilistic C-Means and Fuzzy C-Means algorithms exhibited initialization-sensitivity problems and difficulties coping with low intensity contrast, achieving low 72.5% and 85% success rates in extraction. The Adaptive Resonance Theory 2 algorithm is the most suitable algorithm for gas-filled region detection, achieving a 100% success rate on 40 tested images, largely owing to its dynamic control of the number of clusters.

• 한국정보과학회논문지:시스템및이론
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• 제26권12호
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• pp.1447-1457
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• 1999

본 논문에서는 일반적인 네트워크에서 적응력 있는(adaptive) 분산형 시스템 레벨 결함 진단을 위한 분할 기법을 제안한다. 적응력 있는 분산형 시스템 레벨 결함 진단 기법에서는 시스템의 형상이 변경될 때마다 시험 할당 알고리즘이 수행되므로 적응력 없는 결함 진단 기법에 비하여 결함 감지를 위한 시험의 갯수를 줄일 수 있다. 기존의 시험 할당 알고리즘들은 전체 시스템을 대상으로 하는 비분할(non-partitioning) 방식을 이용하였는데, 이 기법은 불필요한 과다한 메시지를 생성한다. 본 논문에서는 전체 시스템을 이중 연결 요소(biconnected component) 단위로 분할한 후, 시험 할당은 각 이중 연결 요소 내에서 수행한다. 이중 연결 요소의 관절점(articulation point)의 특성을 이용하여 각 시험 할당에 필요한 노드의 수를 줄임으로서, 비분할 기법들에 비해 초기 시험 할당에 필요한 메시지의 수를 감소시켰다. 또한 결함이 발생한 경우나 복구가 완료된 경우의 시험 재 할당은 직접 영향을 받는 이중 연결 요소내로 국지화(localize) 시켰다. 본 논문의 시스템 레벨 결함 진단 기법의 정확성을 증명하였으며, 기존 비분할 방식의 시스템 레벨 결함 진단 기법과의 성능 분석을 수행하였다.Abstract We propose an adaptive distributed system-level diagnosis using partitioning method in arbitrary network topologies. In an adaptive distributed system-level diagnosis, testing assignment algorithm is performed whenever the system configuration is changed to reduce the number of tests in the system. Existing testing assignment algorithms adopt a non-partitioning approach covering the whole system, so they incur unnecessary extra message traffic and time. In our method, the whole system is partitioned into biconnected components, and testing assignment is performed within each biconnected component. By exploiting the property of an articulation point of a biconnected component, initial testing assignment of our method performs better than non-partitioning approach by reducing the number of nodes involved in testing assignment. It also localizes the testing reassignment caused by system reconfiguration within the related biconnected components. We show that our system-level diagnosis method is correct and analyze the performance of our method compared with the previous non-partitioning ones.

• 한국항공우주학회지
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• 제38권12호
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• pp.1177-1183
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• 2010

본 논문은 항공기의 신뢰도를 높이기 위한 목적으로, 항공기 조종면에 장착된 구동기에 고장이 발생하여 특정위치에 고정되어 움직이지 않을 때, 다중 미지입력 관측기(UIO, Unknown Input Observer)와 적응기법을 이용하여 고장이 발생한 구동기를 구분하고 해당 조종면의 고정된 위치를 추정하여, 조종력 할당 알고리듬 등의 조종면 고장에 대한 재형상 제어를 위한 입력을 제공하는 방법을 다룬다. 구동기의 개수와 동일한 관측기를 구성하되, 각 구동기의 고장이 반영된 선형모델을 사용함으로써 정상인 경우의 관측기에서 출력된 잔차와 고장이 발생한 경우의 관측기에서 출력된 잔차를 비교하여 고장을 분리하고, 적응기법을 이용하여 1초 내에 고장의 정도를 추정한다. 그러나 2개의 동일 형상의 러더가 존재할 경우, 고장분리가 불가함을 밝힌다.

• 대한의용생체공학회:의공학회지
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• 제12권4호
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• pp.277-284
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• 1991

This study describes the ambulatory ECG monitoring system for the remote autom atic diagnosis. System: tlardware is based on one chip microcomputer(80c31) and its peripherals which consists of A/D, EPROM, RAM, LCD display and two preamplifiers, Power circuits, control logic circuits. A/D converted data were differentiated and low pass filtered. The detection of QRS complex and R point were accomplished by software algorithm based on adaptive threshold computed on low pass fi:leered signal. Rhythm analysis is performed by RR interval and average RR interval. The performance of QRS detection algorithm is evaluated by using MIT/BIH data base. Using this system, the trends of the arrythmia during the long term could be saved and displayed.