• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.31-38
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• 1988

This paper presents a methodology for the development of a part classification and coding system suited to each individual company. When coding a group of parts for a specific company by a general purpose part classification & coding system like OPITZ system, it is frequently observed that we use only a small subset of total available code numbers. Such sparsity in the actual occurrences of code numbers implies that we can design a better system which uses digits of the system more parsimoniously. A 2-dimensional fuzzy ISODATA algorithm is developed to extract the important characteristics for the classification from the set of given parts. Based on the extracted characteristics nd the distances between fuzzy clustering cenetroids, a company-unique classification and coding system can be developed. An example case study for a medium sized machine shop is presented.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.795-801
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• 2013

Recently, support vector machine has been widely used in various application fields due to its superiority of classification performance comparing with decision tree and neural network. Since support vector machine is basically designed for the binary classification problem, output coding method to analyze the classification result of multiclass binary classifier is used for the application of support vector machine into the multiclass problem. However, previous feature selection method for output coding based support vector machine found the features to improve the overall classification accuracy instead of improving each classification accuracy of each classifier. In this paper, we propose the novel feature selection method to find the features for maximizing the classification accuracy of each binary classifier in output coding based support vector machine. Experimental result showed that proposed method significantly improved the classification accuracy comparing with previous feature selection method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.67-72
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• 1993

An adaptive block truncation coding(BTC) using human visual system(HVS) is proposed. To reduce visible blocking effect at sensitive area in HVS. a new category classification coefficient is proposed. The categroy classification coefficient was derived by combining the modified HVS and standard deviation. By computer simulations, we showed that the proposed method reduced blocking effect at low bit rate coding more than the conventional Hui's method.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.594-601
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• 2006

Coding of occupational and industrial codes is a major operation in census survey of Korean statistics bureau. The coding process has been done manually. Such manual work is very labor and cost intensive and it usually causes inconsistent results. This paper proposes an automatic coding system based on example-based learning. The system converts natural language input into corresponding numeric codes using code generation system trained by example-based teaming after applying manually built rules. As experimental results performed with training data consisted of 400,000 records and 260 manual rules, the proposed system showed about 76.69% and 99.68% accuracy for occupational code classification and industrial code classification, respectively.

• The Journal of Korean Association of Computer Education
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• v.7 no.4
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• pp.51-60
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• 2004

This paper proposes an automated coding system of Korean standard industry/occupation for census which reduces a lot of cost and labor for manual coding. The proposed system converts natural language responses on survey questionnaires into corresponding numeric codes using information retrieval techniques and document classification algorithm. The system was experimented with 46,762 industry records and occupation 36,286 records using 10-fold cross -validation evaluation method. As experimental results, the system show 87.08% and 66.08% production rates when classifying industry records into level 2 and level 5 codes respectively. The system shows slightly lower performances on occupation code classification. We expect that the system is enough to be used as a semi-automate coding system which can minimize manual coding task or as a verification tool for manual coding results though it has much room to be improved as an automated coding system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.195-207
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• 1999

Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing. The steps of developing the C&C system are as follows: 1) analysis of existing coding system and drawing type; 2) design of C&C system; 3) practice of designed coding system to a field.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.33-40
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• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.281-285
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• 2000

This paper proposes context-based coding methods for variable length coding of inter-frame DCT coefficients. The proposed methods classify run-level symbols depending on the preceding coefficients. No extra overhead needs to be transmitted, since the information of the previously transmitted coefficients is used for classification. Two entropy coding methods, arithmetic coding and Huffman coding, are used for the proposed context-based coding. For Huffman coding, there is no complexity increase from the current standards by using the existing inter/intra VLC tables. Experimental results show that the proposed methods give ～ 19% bits gain and ～ 0.8 dB PSNR improvement for adaptive inter/intra VLC table selection, and ～ 37% bits gain and ～ 2.7dB PSNR improvement for arithmetic coding over the current standards, MPEG-4 and H.263. Also, the proposed methods obtain larger gain for small quantizaton parameters and the sequences with fast and complex motion. Therefore, for high quality video coding, the proposed methods have more advantage.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.166-170
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• 1998

Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing.