• Journal of Chest Surgery
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• v.23 no.2
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• pp.342-351
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• 1990

In recent years there are so many medical informations that surgeons should know to handle or analyze their large amount of surgical cases. Proper use of computer system offers new opportunities for the storage and manipulation of their hospital informations. But little is reported about which system, is appropriate, how much can we do with such a system, or what kind of work can be done with that, especially in the area of Thoracic and Cardiovascular Surgery section. Authors designed a computer-based patient file management system using 16 Bit AT IBM personal computer and dBASE IV program, and developed a coding system for the diagnosis and operation name, which offers the basis for the classification of the surgical patient data. And the result of some experiences which was got from the total surgical cases of Thoracic and Cardiovascular Section, Seoul District Armed Forces General Hospital during past 5years, was described.

• Journal of Drive and Control
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• v.9 no.2
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• pp.39-45
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• 2012

The NAS 1638 cleanliness classification system was originally developed in 1966 by the US Aircraft Industries of America to both simplify reporting of particle count data and to control the introduction of dirt during the assembly of aircraft fluid systems. The numbers of particles at stated sizes are represented by broad bands where the interval was generally a doubling of contamination. A number of systems have been introduced since this to suit differing requirements. NAS 1638 and AS4059 are used in other industrial sectors such as the Off-shore & Sub-Sea and the Primary Metal Industries. The changes to ISO contamination measurement standards controlled by ISO/TC131/SC6 in 1999 meant that a revision of most of these classification systems was necessary. The body responsible for NAS 1638 decided to withdraw it for new installations and replace it with an update of an existing standard, SAE AS 4059. This paper details the philosophy behind the contamination coding systems, the reasons for the changes to the ISO contamination standards and explains the workings of AS 4059, the replacement for NAS 1638. It goes on to detail the latest changes to this standard.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.245-252
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• 2008

We present a classification algorithm based on ant colony system(ACS) for classifying digital images. The ACS has been recently emerged as a useful tool for the pattern recognition, image extraction, and edge detection. The classification algorithm of digital images is very important in the application areas of digital image coding, image analysis, and image recognition because it significantly influences the quality of images. The conventional procedures usually classify digital images with the fixed value for the associated parameters and it requires postprocessing. However, the proposed algorithm utilizing randomness of ants yields the stable and enhanced images even for processing the rapidly changing images. It is also expected that, due to this stability and flexibility of the present procedure, the digital images are stably classified for processing images with various noises and error signals arising from processing of the drastically fast moving images could be automatically compensated and minimized.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.274-285
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• 2016

A designer is mainly supported by two essential factors in design decisions. These two factors are intelligence and experience aiding the designer by predicting the interconnection between the required design parameters. Through classification of product data and similarity recognition between new and existing designs, it is partially possible to replace the required experience for an inexperienced designer. Given this context, the current paper addresses a framework for recognition and flexible retrieval of similar models in product design. The idea is to establish an infrastructure for transferring design as well as the required PLM (Product Lifecycle Management) know-how to the design phase of product development in order to reduce the design time. Furthermore, such a method can be applied as a brainstorming method for a new and creative product development as well. The proposed framework has been tested and benchmarked while showing promising results.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.468-471
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• 2004

In this paper, a method for classifying fingerprint ridge lines using runlength codes is proposed. To detect feature points(minutiae) in automatic fingerprint identification system(AFIS), classification of fingerprint ridge lines are essential process. The fingerprint ridge lines are classified by run-length coding, and also the end and bifurcation regions in ridge lines are separated. To evaluate the performance of the proposed method, detected feature regions including minutiae points and classified fingerprint ridge lines are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.77-86
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• 1989

A fully automated cost estimation system(FACES) has been developed. Since speed, accuracy, and consistency are essential factors in automating a cost estimation, the use of computers in cost estimation system(CES) has grown rapidly in the last few years. FACES is a micro computer based cost estimation system that employs a manufacturing knowledge base. A Group Technology(GT) based part classification and coding(C&C) scheme is used to automate the process planning aspects of cost estimation. Variant process planning methods are employed to generate workstation routings from form features of the part. The system has been tested for an assembly of six machined parts. Results indicate that the system could provide a substantial improvement in accuracy, productivity, and performance over the more traditional full dialog approach to cost estimation. It also provides a good foundation for a factory automation by using a common GT based database through design to production.

• Journal of the Korean Society for information Management
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• v.17 no.4
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• pp.27-45
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• 2000

National statistical data such as Korean Census is fundamental data for national administration. In this paper, we present an automatic coding system utilizing morphological analyser and knowledge dictionaries. Knowledge bases are constructed based on an authority dictionaries which were developed by authors utilizing a newly learning theory. Test data indicates 99.5% of productivity and 83.3% of accuracy. The presented methods can be effectively applied to analyze statistical information.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.461-467
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• 2011

Accurate classification of input signals is the key prerequisite for variable bit-rate coding, which has been introduced in order to effectively utilize limited communication bandwidth. Especially, recent surge of multimedia services elevate the importance of speech/music classification. Among many speech/music classifier, the ones based on support vector machine (SVM) have a strong selling point, high classification accuracy, but their computational complexity and memory requirement hinder their way into actual implementations. Therefore, techniques that reduce the computational complexity and the memory requirement is inevitable, particularly for embedded systems. We first analyze implementation of an SVM-based classifier on embedded systems in terms of execution time and energy consumption, and then propose two techniques that alleviate the implementation requirements: One is a technique that removes support vectors that have insignificant contribution to the final classification, and the other is to skip processing some of input signals by virtue of strong correlations in speech/music frames. These are post-processing techniques that can work with any other optimization techniques applied during the training phase of SVM. With experiments, we validate the proposed algorithms from the perspectives of classification accuracy, execution time, and energy consumption.