• Korea Journal of Hospital Management
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• v.21 no.4
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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.

• Journal of Computational Design and Engineering
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• v.1 no.3
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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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.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.466-471
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• 2007

Electrical fires form over 30 percent of fires, but the study on the reliability of electrical fire statistics is not performed. Electrical roe occupancy was very high due to investigating and classifying fires, which is not directly continuous with electrical cause, as electrical fire because insufficiency of cause classification method or system, and the problems of the reliability of electrical fire statistics were presented. So, the reliability of electrical fire statistics must be guaranteed by improvement of the existing cause classification method of electrical fire. This paper analyzed the problems of electrical rue statistics by the existing cause classification method of electrical fire and presented the new method to classify causes of electrical fire.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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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.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.184-191
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• 2020

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.