• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.653-662
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• 2006

In ubiquitous computing that is to build computing environments to provide proper services according to user's context, human being's emotion recognition based on facial expression is used as essential means of HCI in order to make man-machine interaction more efficient and to do user's context-awareness. This paper addresses a problem of rigidly basic emotion recognition in context-sensitive facial expressions through a new Bayesian classifier. The task for emotion recognition of facial expressions consists of two steps, where the extraction step of facial feature is based on a color-histogram method and the classification step employs a new Bayesian teaming algorithm in performing efficient training and test. New context-sensitive Bayesian learning algorithm of EADF(Extended Assumed-Density Filtering) is proposed to recognize more exact emotions as it utilizes different classifier complexities for different contexts. Experimental results show an expression classification accuracy of over 91% on the test database and achieve the error rate of 10.6% by modeling facial expression as hidden context.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.35-39
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• 2020

DNN error is small compared to the conventional speech recognition system, DNN is difficult to parallel training, often the amount of calculations, and requires a large amount of data obtained. In this paper, we generate a phoneme unit to estimate the GMM parameters with each phoneme model parameters from the GMM to solve the problem efficiently. And it suggests ways to improve performance through clustering for a specific vocabulary to effectively apply them. To this end, using three types of word speech database was to have a DB build vocabulary model, the noise processing to extract feature with Warner filters were used in the speech recognition experiments. Results using the proposed method showed a 97.9% recognition rate in speech recognition. In this paper, additional studies are needed to improve the problems of improved over fitting.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.53-63
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• 2018

Since warfare surroundings getting complex and diverse in the future, it is not simple to make appropriate structures and organizations for military groups along the phenomenon. Therefore, this study proposes a methodology of verification for army staff's structure and organization by units in the future using System Dynamics(SD). The procedure of using SD for the verification is a calculation of database(DB), the design of causal loop diagram, and the simulation and analysis. First, DB such as individuals' workload and time is calculated through observation after a real group of staff. Second, the causal loop diagram is considered by a flow of task, and it is modeled. Third, the DB is entered into the model and simulated for analyzing of appropriacy. This study used Powersim program for designing the SD model. One of the weaknesses of the methodology of this study is possibilities of a different result by the DB by observers and perspectives by analysts. As supplementation for the weakness, this study includes research analysis and surveys for the total analysis. The meaning of this study is that it suggests a methodology of warfighting experimentation to analyze structure and organization of military groups with quantifying suitability in the scientific method.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.543-548
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• 2014

Multiple-model based speech recognition framework (MMSR) has been known to be very successful in speech recognition. Since it uses multiple hidden Markov modes (HMMs) that corresponds to various noise types and signal-to-noise ratio (SNR) values, the selected acoustic model can have a close match with the test noisy speech. However, since the number of HMM sets is limited in practical use, the acoustic mismatch still remains as a problem. In this study, we experimentally determined the optimal SNR mapping between the test noisy speech and the HMM set to mitigate the mismatch between them. Improved performance was obtained by employing the SNR mapping instead of using the estimated SNR from the test noisy speech. When we applied the proposed method to the MMSR, the experimental results on the Aurora 2 database show that the relative word error rate reduction of 6.3% and 9.4% was achieved compared to a conventional MMSR and multi-condition training (MTR), respectively.

• Archives of design research
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• v.19 no.2 s.64
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• pp.5-14
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• 2006

Visual perception is ability that analyze visual information about things accepting through eyes in central nervous system. That is, it is ability that recognize and discriminates a visual stimulus, and analyzes by combining such stimulus with previous experience. At today, work which clears visual perception obstacle's cause through visual perception test and grasps all special quality of visual perception obstacle's is used method of treating that improve visual perception obstacle by visual perception training program. Present, visual perception test tools using the paper and pens are used mainly on psychological consultation of welfare facilities and education for the handicapped or occupational therapy, but a lot of problems are discovered in it. Therefore, purpose of this paper is to develop prototype of web-based visual perception test program that can construct to database to solve existing problem, and to design graphic item. As a result, classified measurement pattern that can diagnose visual perception by three, and illustrated development direction of graphic item for examination with this. Also, extracted check list item that should consider for design and construction of visual perception test program and the variable for feasibility study of believability, and presented process for prototype development.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.79-85
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• 2004

The GIS(Geographic Information System) projects require big initial investment and cost of maintenance. Decision makers would not launch GIS projects unless they are convinced of the benefits of the projects. Therefore the purpose of this paper is to develop an appropriate model for GIS project evaluation. We proposed a GIS project evaluation model and summarize the steps involved in Cost-Benefit Analysis(CBA). The costs of a GIS implementation include hardware and software cost, costs of database development, training expenses, annual maintenance expenses, and other annual expenses. The benefit by using GIS has been assessed into Type I(direct benefits), Type II(indirect benefits), Type III(benefits that result from the sale of information services), Type IV(intangible benefits).

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.681-687
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• 2007

Face recognition technique is very popular for a personal information security and user identification in recent years. However, the face recognition system is very hard to be implemented due to the difficulty where change in illumination, pose and facial expression. In this paper, we consider that an illumination change causing the variety of face appearance, virtual image data is generated and added to the D-LDA which was selected as the most suitable feature extractor. A less sensitive recognition system in illumination is represented in this paper. This way that consider nature of several illumination directions generate the virtual training image data that considered an illumination effect of the directions and the change of illumination density. As result of experiences, D-LDA has a less sensitive property in an illumination through ORL, Yale University and Pohang University face database.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.

• Journal of Information Management
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• v.36 no.3
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• pp.127-165
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• 2005

This study is focused on the quality of the Web databases which has been produced in science. For the quality evaluation of NDSL, PubMed, Scopus, and WoS, 10 evaluating criteria are developed on the basis of literature review. The evaluation results show that NDSL and PubMed are superior in the currentness and cost. Scopus and WoS are superior in the information of citing and the analysis tool. It is needed for purchasing, user training, and library service based on the above evaluation results.