• Title/Summary/Keyword: Industrial Classification

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산업분류와 만성질환 유무와의 관계 (The Relationship between Industrial Classification and Chronic Disease)

  • 홍진혁;유기봉;김선호;김충우;노진원
    • 한국병원경영학회지
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    • 제21권4호
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    • pp.55-62
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    • 2016
  • Purposes: The industry has specialized and fragmented than in the past. As a factor of economic growth and industrialization, the number of people employed in primary industry decreased and the number of people employed in secondary and third industry continuously increased. In modern times, incidence of chronic disease is increasing according to industrial development. So, the purpose of this study was to analyze the chronic disease according to Clark's industrial classification. Methodology: Data were derived from the 2012 Korea Health Panel. The sample was made up of 7,132 adult participants aged 20 or over selected Korea Health Panel by probability sampling from Korea. Binary logistic regression analysis was conducted to examine the main factors associated with chronic disease. Findings: The significant factors associated with chronic disease were gender, age, marital status, household member, education level, insurance type, disability, BMI, and industrial classification. Female, elderly, divorced(including bereavement, missing and separation), one-person households, less than high school graduation, medical aid, disability, obese and primary industry were confirmed chronic disease increases. Practical Implications: The study finds that primary industry's prevalence of chronic disease was higher than secondary and third industry. Therefore, this study aims to management and effort of the worker who engaged in the primary industry. Policy development is required to address inequality or popularization of the differences in these factors by conducting a study to define the working conditions and socio-economic factors between industry.

진동 아날로그 신호 기반의 이상상황 탐지를 위한 기계학습 모형의 성능지표 향상 (Improving the Performance of Machine Learning Models for Anomaly Detection based on Vibration Analog Signals)

  • 김재훈;엄상천;박철순
    • 산업경영시스템학회지
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    • 제47권2호
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    • pp.1-9
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    • 2024
  • New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.

Automated quality characterization of 3D printed bone scaffolds

  • Tseng, Tzu-Liang Bill;Chilukuri, Aditya;Park, Sang C.;Kwon, Yongjin James
    • Journal of Computational Design and Engineering
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    • 제1권3호
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    • pp.194-201
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    • 2014
  • Optimization of design is an important step in obtaining tissue engineering scaffolds with appropriate shapes and inner micro-structures. Different shapes and sizes of scaffolds are modeled using UGS NX 6.0 software with variable pore sizes. The quality issue we are concerned is the scaffold porosity, which is mainly caused by the fabrication inaccuracies. Bone scaffolds are usually characterized using a scanning electron microscope, but this study presents a new automated inspection and classification technique. Due to many numbers and size variations for the pores, the manual inspection of the fabricated scaffolds tends to be error-prone and costly. Manual inspection also raises the chance of contamination. Thus, non-contact, precise inspection is preferred. In this study, the critical dimensions are automatically measured by the vision camera. The measured data are analyzed to classify the quality characteristics. The automated inspection and classification techniques developed in this study are expected to improve the quality of the fabricated scaffolds and reduce the overall cost of manufacturing.

품질코스트시스템의 체계적 분류 및 산정모형 개발 (Systematic Classification and Estimation of Quality Cost.)

  • 서경범;박명규
    • 산업경영시스템학회지
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    • 제22권50호
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    • pp.363-372
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    • 1999
  • This paper is to propose models for systematic classification and estimation of quality costs. Especially in this research, quality costs are categorized into three aspects, ie., conventional quality cost system, ZD(Zero Defect) quality cost system and Taguchi quality system. In conclusion, I hope that this study will have contribution to application of quality loss system for all the business in Korea.

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전문가 시스템을 이용한 부품 분류 및 코딩 (an Expert System for Part Classification and Coding)

  • 박양병
    • 대한산업공학회지
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    • 제17권2호
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    • pp.17-26
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    • 1991
  • This paper discusses an expert system to generate part codes and construct part families, ESPCC, for the group technology application. The ESPCC, that is developed by using VP-Expert rule-based expert system development tool, embodies the specific knowledge of human experts to determine part codes consistent with the OPITZ classification and coding system. The ESPCC is implemented on an IBM compatible personal computers running MS-DOS.

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목표 속성을 고려한 연관규칙과 분류 기법 (Directed Association Rules Mining and Classification)

  • 한경록;김재련
    • 산업경영시스템학회지
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    • 제24권63호
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    • pp.23-31
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    • 2001
  • Data mining can be either directed or undirected. One way of thinking about it is that we use undirected data mining to recognize relationship in the data and directed data mining to explain those relationships once they have been found. Several data mining techniques have received considerable research attention. In this paper, we propose an algorithm for discovering association rules as directed data mining and applying them to classification. In the first phase, we find frequent closed itemsets and association rules. After this phase, we construct the decision trees using discovered association rules. The algorithm can be applicable to customer relationship management.

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제조시스템의 유연성 정의 및 분류에 관한 연구 (Flexibility : Definition and Classification in Manufacturing Systems)

  • 이창섭;하정진
    • 산업경영시스템학회지
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    • 제14권24호
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    • pp.155-161
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    • 1991
  • Flexibility has become a key objectives in the design of manufacturing systems and a critical measure of total manufacturing performance. The need for flexibility is increasing due to some environmental change such as changing technical characteristics of the products and the changing nature of market demands. Most importantly, flexibility embodies competitive value for a manufacturer. Although the importance of flexibility has stressed in the various research, very few attempts have been made to synthesize the literature dealing with definitions and measure of flexibility. It is this issue that have motivated us to search for the definition and classification of flexibility.

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전투기용 레이다 기반 SAR 영상 자동표적분류 기능 구조 및 CNN 앙상블 모델을 이용한 표적분류 정확도 향상 방안 연구 (Study on the Functional Architecture and Improvement Accuracy for Auto Target Classification on the SAR Image by using CNN Ensemble Model based on the Radar System for the Fighter)

  • 임동주;송세리;박범
    • 시스템엔지니어링학술지
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    • 제16권1호
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    • pp.51-57
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    • 2020
  • The fighter pilot uses radar mounted on the fighter to obtain high-resolution SAR (Synthetic Aperture Radar) images for a specific area of distance, and then the pilot visually classifies targets within the image. However, the target configuration captured in the SAR image is relatively small in size, and distortion of that type occurs depending on the depression angle, making it difficult for pilot to classify the type of target. Also, being present with various types of clutters, there should be errors in target classification and pilots should be even worse if tasks such as navigation and situational awareness are carried out simultaneously. In this paper, the concept of operation and functional structure of radar system for fighter jets were presented to transfer the SAR image target classification task of fighter pilots to radar system, and the method of target classification with high accuracy was studied using the CNN ensemble model to archive higher classification accuracy than single CNN model.

전기화재 조사 및 통계의 신뢰성 향상을 위한 원인분류방법의 개발 (Development of Cause Classification Method for Improving Reliability of Electrical Fire Statistics)

  • 전정채;전현재;이상익;유재근
    • 한국산학기술학회논문지
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    • 제8권3호
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    • pp.466-471
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    • 2007
  • 전기화재는 전체 화재의 30% 이상을 차지하고 있지만 전기화재 통계의 신뢰성에 대한 검토가 제대로 이루어지지 못하였다. 전기화재는 원인분류 방법 또는 체계의 미흡으로 전기적 요인이 아닌 경우에도 전기화재로 분류되어 높은 점유율을 차지하게 되었고 그로 인한 전기화재 통계의 문제점이 제기되었다. 따라서 기존의 전기화재 원인 분류 방법의 개선을 통해 전기화재 통계의 신뢰성 확보가 필요하다. 본 논문에서는 기존의 전기화재 원인분류에 따른 전기화재 조사 및 통계의 문제점을 분석하였고 새로운 전기화재 원인분류 방법을 제시하였다.

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A Framework for Designing Closed-loop Hand Gesture Interface Incorporating Compatibility between Human and Monocular Device

  • Lee, Hyun-Soo;Kim, Sang-Ho
    • 대한인간공학회지
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    • 제31권4호
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    • pp.533-540
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    • 2012
  • Objective: This paper targets a framework of a hand gesture based interface design. Background: While a modeling of contact-based interfaces has focused on users' ergonomic interface designs and real-time technologies, an implementation of a contactless interface needs error-free classifications as an essential prior condition. These trends made many research studies concentrate on the designs of feature vectors, learning models and their tests. Even though there have been remarkable advances in this field, the ignorance of ergonomics and users' cognitions result in several problems including a user's uneasy behaviors. Method: In order to incorporate compatibilities considering users' comfortable behaviors and device's classification abilities simultaneously, classification-oriented gestures are extracted using the suggested human-hand model and closed-loop classification procedures. Out of the extracted gestures, the compatibility-oriented gestures are acquired though human's ergonomic and cognitive experiments. Then, the obtained hand gestures are converted into a series of hand behaviors - Handycon - which is mapped into several functions in a mobile device. Results: This Handycon model guarantees users' easy behavior and helps fast understandings as well as the high classification rate. Conclusion and Application: The suggested framework contributes to develop a hand gesture-based contactless interface model considering compatibilities between human and device. The suggested procedures can be applied effectively into other contactless interface designs.