• Title/Summary/Keyword: Abnormal Pattern Analysis

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A Visualization Scheme with a Calendar Heat Map for Abnormal Pattern Analysis in the Manufacturing Process

  • Chankhihort, Doung;Lim, Byung-Muk;Lee, Gyu-Jung;Choi, Sungsu;Kwon, Sun-Ock;Lee, Sang-Hyun;Kang, Jeong-Tae;Nasridinov, Aziz;Yoo, Kwan-Hee
    • International Journal of Contents
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    • 제13권2호
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    • pp.21-28
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    • 2017
  • Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.

일부 요통환자의 인자분석 (Factor Analysis of Low Back Pain Patients)

  • 강점덕
    • 대한물리치료과학회지
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    • 제9권1호
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    • pp.123-128
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    • 2002
  • Objectives: The objective of this study was to investigate factor analysis of low back pain patients. Methods: The data were collected from hospital located in Daegu. Observation was made on 40 low back pain patients and factor analysis study was also performed in terms of their abnormal physical findings. Results: The low back pain patients occupied 20% of all clinical patients in male group and 20% in female group. The occurrence of acute low back pain in the first factor tended to be higher among in male group than among in female group. While it was significantly higher muscle weakness of the back in female group. The most prevailing abnormal finding among low back pain patients in the first factor were tender point on the back, While it was significantly lower Decreased tendon reflex in both sexes Conclusions: The factor pattern of abnormal physical findings in low back pain patients was much different between male and female patients, suggesting the different pattern of etiology. Although low back pain is one of the most common symptoms causing limitation activity, as yet there is no known specific effective treatment.

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비정상 주행패턴 분석을 통한 WIM 시스템 개선 연구 (A Research for Improvement of WIM System by Abnormal Driving Patterns Analysis)

  • 박제우;김영백;정경호;안광선
    • 인터넷정보학회논문지
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    • 제11권4호
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    • pp.59-72
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    • 2010
  • WIM(Weigh-In-Motion) 시스템은 고속으로 이동 중인 차량의 무게를 측정하는 시스템이다. 기존의 WIM 시스템에서는 등속을 기준으로 차량의 무게를 측정하며 오차율이 10% 범위에 있다. 하지만 운전자의 가 감속 조작과 같은 비정상 주행패턴을 고려하고 있지 않으므로 실제 오차율은 더욱 크다. 이러한 오차를 최소화하기 위해서 비정상적인 주행패턴을 찾고 이를 적용한 개선된 WIM 시스템이 필요하다. 본 논문에서는 기존의 WIM 시스템의 오차율에 영향을 미치는 비정상 주행패턴을 분석하고 오차율을 최소화하는 개선된 WIM 시스템을 설계한다. 개선된 WIM 시스템은 기존의 시스템에 루프센서를 추가한 다단 루프 구조를 가진다. 또한 내부적으로 정의된 측정 함수를 개선하여 비정상 주행패턴별로 측정된 무게를 보정한다. 실험 분석 결과 개선된 WIM 시스템은 기존의 최대 평균 오차율 22.98% 에서 8% 미만으로 오차율이 감소한 사실을 알 수 있다.

인공 신경망의 패턴분석에 근거한 지능적 부품품질 관리시스템의 설계 (Design of Intelligent Material Quality Control System based on Pattern Analysis using Artificial Neural Network)

  • 이장희;유성진;박상찬
    • 품질경영학회지
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    • 제29권4호
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    • pp.38-53
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    • 2001
  • In resolving industrial quality control problems, a vector of multiple quality characteristic variables is involved rather than a single variable. However, it is not guaranteed that a multivariate control chart based on statistical methods can monitor abnormal signal in case that small changes of relationship between each variables causes abnormal production process. Hence a quality control system for real-time monitoring of the multi-dimensional quality characteristic vector under a multivariate normal process is needed to enhance tile production system quality performance. A pattern analysis approach based on self-organizing map (SOM), an unsupervised learning technique of neural network, is applied to the design of such a quality control system. In this study we present a new material quality control system based on pattern analysis approach and illustrate the effectiveness of proposed system using actual electronic company material data.

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이상 패턴 분석을 통한 정책의 적합성 분석 연구 : S 시의 아동 급식 전자 카드 사례를 중심으로 (Analyzing the Relevancy of Policy by Abnormal Pattern Analysis : Focused on the Case of S-City's e-Card for Child Meal Support)

  • 전종식;권오병
    • 한국IT서비스학회지
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    • 제17권1호
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    • pp.135-153
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    • 2018
  • E-Card Service for Child Nutrition Program is one of the main public policy services nowadays. In case of inconvenience during the use of the e-cards, it is recommended to cooperate with related organizations in order to promptly handle and provide guidance, and thoroughly manage child feeding service such as hygiene, nutrition and kindness etc. To do so, it is very important to provide food service that meets local actual conditions and children's needs in a cost effective manner for the underage who are worried about the poorly-fed by understanding the pattern of child feeding e-card service. Hence. this paper aims to investigate how child feeding e-card service efficiently provides meals according to the local situation and children's needs through big data analysis and to propose a method of identifying welfare conditions according to the purpose of service with actual application examples. The results suggest that, first of all, this study is able to judge appropriateness of public institution's policy in a timely and repetitive manner through non-standard data analysis such as Naver News and transaction data. Secondly, this paper proposes a multi-layered analysis framework, which performs online open data analysis to detect policy issues, visualizes retrieval and preprocessing of real data, and performs abnormal pattern recognition. These will be worthy of reference to other similar projects.

그래프 데이터베이스 환경에서 이상징후 탐지를 위한 연관 관계 분석 기법 (Association Analysis for Detecting Abnormal in Graph Database Environment)

  • 정우철;전문석;최도현
    • 융합정보논문지
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    • 제10권8호
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    • pp.15-22
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    • 2020
  • 4차 산업 혁명과 데이터 환경의 급격한 변화는 기존 관계형 데이터베이스(RDB)는 기술적 한계를 드러내고 있다. IDC/금융/보험 등 전 분야에서 비정형 데이터에 대한 새로운 분석방안으로 그래프 데이터베이스(GDB) 기술에 관심이 높아지고 있다. 그래프 데이터베이스는 상호 연동된 데이터를 표현하고 광범위한 네트워크에서 연관 관계 분석에 효율적인 기술이다. 본 연구는 기존 RDB를 GDB 모델로 확장하고, 새로운 이상징후 탐지를 위해 기계학습 알고리즘(패턴인식, 클러스터링, 경로거리, 핵심추출)을 적용하였다. 성능분석 결과 이상 행위 성능(약 180배 이상)이 크게 향상되었고, RDB로 분석 불가능한 5단계 이후 이상징후 패턴을 추출할 수 있음을 확인하였다.

오신호 입력에 따른 펌프의 고장징후 조기감지 성능분석 (Performance Analysis on Early Detection of Fault Symptom of a Pump with Abnormal Signals)

  • 정재영;이병오;김형균;김대웅
    • 동력기계공학회지
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    • 제20권2호
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    • pp.66-72
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    • 2016
  • As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

Realtime Wireless Monitoring of Abnormal ST in ECG Using PC Based System

  • Jeong, Gu-Young;Yu, Kee-Ho;Kim, Nam-Gyun;Inooka, Hikaru
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.176-180
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    • 2004
  • The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

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시-주파수 분석법을 이용한 시각자극 유발전위에 관한 연구 (Estimation of Visual Evoked Potentials Using Time-Frequency Analysis)

  • 홍석균;성홍모;윤영로;윤형로
    • 대한의용생체공학회:의공학회지
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    • 제22권3호
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    • pp.259-267
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    • 2001
  • The visual evoked potentials(VEPs) is used to assist in the diagnosis of specific disorders associated with involvement of the sensory visual pathways. The P100 latency is an important parameter which is diagnosis of optic nerve disorders. There are characteristics of latency delay, wave distortion, amplitude deduction in abnormal subjects. It is difficult to diagnose in the case of producing peak at the P100 latency. In this paper, difference of pattern between normal VEPs and abnormal VEPs using the Choi-Williams distribution method is studied. We observed the relationship about time and spectrum. The result shown that normal VEPs had maximum spectral value at 20Hz~26.7Hz and abnormal VEPs had maximum spectral value at 16.7Hz~20Hz. Also normal VEPs spectrum is higher than abnormal VEPs spectrum.

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웨어러블 헬스케어 환경에서 ECG 전기패턴 QRS을 이용한 급성 심장마비 예방 시스템 (Design of Acute Heart Failure Prevention System based on QRS Pattern of ECG in Wearable Healthcare Environment)

  • 이주관;김만식;전문석
    • 한국전자통신학회논문지
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    • 제11권11호
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    • pp.1141-1148
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    • 2016
  • 본 논문은 웨어러블 시스템을 이용하여, ECG 전기 패턴을 QRS을 이용하여 급성 심장마비 예측 감지 시스템으로, 웨어러블 심장 이상 징후 감지 스마트 워치와, 이를 포함 하고 디지털 ECG (X, Y) 패턴 좌표 DB를 이용하여 비정상 패턴을 즉시 감지하고, 급성 심장마비 예방 시스템 및 그 방법을 보여준다. 특히, 디지털 ECG(X, Y) 패턴 정보를 이용한 이상 징후 유형과 대비하는 단계를 통해서 급성 심장마비 발생 시, 골든타임을 놓치지 않고 응급 처치할 수 있음을 보여 준다.