• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.46-57
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• 2022

In this paper, we proposed the DFMEA Implementation Method for safety design of Weapon System. First, we presented the process for DFMEA. And then, the case analysis of OOO missile was performed in accordance with the process presented. After defining the system requirements of OOO missile, failure definition scoring criteria was set. In order to clarify the definition of failure, the failure was classified into safety, reliability, maintainability and others. After performing the function analysis, the relationship matrix analysis was performed to identify the failure mode according to the function without omission. After clarifying the failure classification, mode of failure, cause of failure and effect were analyzed to calculate the severity, occurrence and detection values. After the action priority was judged, the recommended action according to the failure classification was identified for the determined action priority. The results of this study can be used as a relevant basis for the design reflection and resource re-allocation of stakeholders.

• Korean Chemical Engineering Research
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• v.48 no.4
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• pp.483-489
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• 2010

An image analysis-based soft sensor is designed and applied to automatic quality classification of product appearance with color-textural characteristics. In this work, multiresolutional multivariate image analysis (MR-MIA) is used in order to analyze product images with color as well as texture. Fisher's discriminant analysis (FDA) is also used as a supervised learning method for automatic classification. The use of FDA, one of latent variable methods, enables us not only to classify products appearance into distinct classes, but also to numerically and consistently estimate product appearance with continuous variations and to analyze characteristics of appearance. This approach is successfully applied to automatic quality classification of intermediate and final products in industrial manufacturing of engineered stone countertops.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• Journal of Navigation and Port Research
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• v.27 no.3
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• pp.307-313
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• 2003

Off-line ship chartering is done nearly through the brokers. Because of the international scale of chartering market, brokers spend too much times and costs on searching the most appropriate product which the consumers want. In this research, we propose the on-line Charter Product Categorization Model to search the products efficiently in the Cyber Chartering System. This Model will make concerned parties of the ship chartering to get unified product information efficiently, and the select the most appropriate product. In this research, we classified the ship chartering products into categories of cargo, ship type, and sea routes, and defined mutual relation of each products, and we verified that this classification is necessary to search the products through the product searching experiment.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.89-101
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• 2019

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.515-522
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• 2015

Through the correspondence works with IEC in the smart grid fields and power IT fields, we set up the interpretation work procedure and defined the work rule for correspondence by analyzing the work results. In addition, we suggest cases for discussion of terms and definitions in the IEC and analyze them and then propose a matrix classification system for standardization to solve the cases for discussion. The matrix classification system with 3-axes of classification has been applied to newly emerging terminologies followed by smart gird. We drew the usefulness in search of terms in application fields and showed the cases of applying the matrix classification. The IEC Electropedia classification standard is unclear and the classification is mixed with principle, application and product areas. We proposed a new working group in IEC TC1 for research on the matrix classification system and then TC 1 decided to organize a new WG titled in the "IEV structure and supporting tools".

• Journal of the Korean Society of Costume
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• v.64 no.5
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• pp.76-90
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• 2014

The Design Protection Act of Korea classifies industrial designs into examined-based and unexamined-based articles. For design application and registration under the DPA, applicable product for the design needs to be chosen in order for it to be registered. Clothing and personal belongings under class B in the classification list are subject to unexamined-based articles. A sound and logical classification system will lead to higher administrative efficiency as well as assurance of more convenience for the system users. This paper examines the suitability of the design classification for clothing and personal belongings and purposes to suggest improvements.

• Steel and Composite Structures
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• v.7 no.3
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• pp.185-200
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• 2007

Tubular construction is widely used in a range of civil and structural engineering applications. To date, the principal product range has comprised square, rectangular and circular hollow sections. However, hot-rolled structural steel elliptical hollow sections have been recently introduced and offer further choice to engineers and architects. Currently though, a lack of fundamental structural performance data and verified structural design guidance is inhibiting uptake. Of fundamental importance to structural metallic design is the concept of cross-section classification. This paper proposes slenderness parameters and a system of cross-section classification limits for elliptical hollow sections, developed on the basis of laboratory tests and numerical simulations. Four classes of cross-sections, namely Class 1 to 4 have been defined with limiting slenderness values. For the special case of elliptical hollow sections with an aspect ratio of unity, consistency with the slenderness limits for circular hollow sections in Eurocode 3 has been achieved. The proposed system of cross-section classification underpins the development of further design guidance for elliptical hollow sections.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.24-33
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• 2001

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiments. So ones are trying to reach the robustness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.7
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• pp.1193-1205
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• 1994

This paper presents a fuzzy system that adaptively classifies subimages to four classes according to image activity distribution. In adaptive transform image coding, subimage classification improves the compression performance by assigning different bit maps to different classes. A conventional classification method sorts subimages by their AC energy and divides them to classes with equal number of subimages. The fuzzy system provides more flexible classification to natural images with various distribution of image details than does the conventional method. Clustering of training data in the input-output product space generated the fuzzy rules for subimage classification. The fuzzy system of small number of fuzzy rules successfully classified subimages to improve the compression performance of the transform image coding without sorting of AC energies.