• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.259-274
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• 2002

Recently, a great deal of corporations have adopted knowledge management system with eagerness to enhance the company competitiveness. However, since the main feature of knowledge management system is not just a simple information system but another entity creating intangible assets tailed "knowledge", we need to develop a new approach to investigating the performance and acceptance of knowledge management systems from a perspective allowing knowledge-sensitive constructs. In this regard, we develop new constructs like knowledge schema and several knowledge circulation-related activities. As a research model, we adopt a famous technology acceptance model or TAM by Davis (1989), and extend it into incorporating knowledge schema. With the statistically valid and usable questionnaire survey data collected from 886 respondents in a big corporation typically using knowledge management system, we induced a robust result empirically, saying that knowledge schema and knowledge circulation activities are valid determinants of performance and acceptance of knowledge management systems.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.231-236
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• 2002

The classification of the speech-sound block comes from the multi-resolution analysis property of the discrete wavelet transform, which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract vapid speech-sounds in terms of position and frequency range. It performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising signal-to-noise ratio and a useful system tuning for the system implementation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.620-626
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• 2008

We propose a feature map method to detect a collision for a motion-based game. The feature map can be made an optimally reduced motion data using subtraction image and virtual ball images according to image size and condition. And we calculate the overlapped ratio between moving image data and objects. This ratio is an invariant for detection even though image size is changed. And we compare this ration with collision detection constant, the feature map can detect fast collisions as well as the collided direction. To evaluate the method, we implemented a motion-base game that consists of a web cam, a player, an enemy, and some virtual balls, and we obtained some valid results for our method for the collision detection. The results demonstrated that the proposed approach is robust, and they can be used as a basic collide detection algorithm for a motion-based game where the size and the position of characters are continuously changing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.881-895
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• 2023

Modern image inpainting techniques based on deep learning have achieved remarkable performance, and more and more people are working on repairing more complex and larger missing areas, although this is still challenging, especially for facial image inpainting. For a face image with a huge missing area, there are very few valid pixels available; however, people have an ability to imagine the complete picture in their mind according to their subjective will. It is important to simulate this capability while maintaining the identity features of the face as much as possible. To achieve this goal, we propose a three-stage network model, which we refer to as the identity and structure feature refinement network (ISFRNet). ISFRNet is based on 1) a pre-trained pSp-styleGAN model that generates an extremely realistic face image with rich structural features; 2) a shallow structured network with a small receptive field; and 3) a modified U-net with two encoders and a decoder, which has a large receptive field. We choose structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), L1 Loss and learned perceptual image patch similarity (LPIPS) to evaluate our model. When the missing region is 20%-40%, the above four metric scores of our model are 28.12, 0.942, 0.015 and 0.090, respectively. When the lost area is between 40% and 60%, the metric scores are 23.31, 0.840, 0.053 and 0.177, respectively. Our inpainting network not only guarantees excellent face identity feature recovery but also exhibits state-of-the-art performance compared to other multi-stage refinement models.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.72-75
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• 2004

In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger-clicking of a wearable input device, called $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click discrimination part, and cross-talk avoidance part. Two types of MEMS inertial sensors are embedded into the wearable input device to measure the angular velocity of a hand (hand movement) and the acceleration rates at the ends of fingers (finger-click motion). The experiment applied to the $SCURRY^{TM}$ device shows the improved stability and performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.17-27
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• 1996

More fuzzy hardware are expected to be utilized in the future to construct fuzzy logic controllers (FLCs). It is hard to find an existing fuzzy hardware which is adopting advanced functions such as self-tuning algorithm in addition to the conventional inference calculation. That is mainly because conventional self-tuning algorithms designed to implement with some hardware circuits is required for fuzzy hardwares to have self-tuning capability. As a first step toward the feature, a novel self-tuning algorithm is proposed in this paper. Based on the search method, the main idea of the proposed algorithm is to detemine valid ranges of input variables of an FLC in order to maximize performance indices fo the control system. The performance indices are so ismple as to be realized by hardware circuit. in dadditon to the conventional scaling-factor adjustment, the algorithm adjusts offset values as well, which, in effect, modifies fuzzy rules of the FLC. To justify the performance of the proposed algorithm, a simulation study is executed.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.50
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• pp.61-85
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• 2011

The agreement to arbitrate is a central feature of commercial arbitration and the lack of a valid arbitration agreement is recognised as a reason why any arbitral award may not be recognized as binding by the courts or may be set aside. The purpose of this paper is to clarify the China's present arbitration law and practice in respect of determination of the validity of international commercial arbitration agreement. Most arbitration laws only require an arbitration agreement to be "in writing". But the arbitration law of the China require an arbitration agreement shall contain the following: 1. The expression of application for arbitration. 2. Matters for arbitration. 3. The arbitration commission chosen. And China's present arbitration law and practice in respect of determination of the validity of international commercial arbitration agreement are somewhat different from the other nations.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1871-1874
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• 2003

Knowledge-based numeric open caption recognition is proposed that can recognize numeric captions generated by character generator (CG) and automatically superimpose a modified caption using the recognized text only when a valid numeric caption appears in the aimed specific region of a live sportscast scene produced by other broadcasting stations. in the proposed method, mesh features are extracted from an enhanced binary image as feature vectors, then a valuable information is recovered from a numeric image by perceiving the character using a multiplayer perceptron (MLP) network. The result is verified using knowledge-based hie set designed for a more stable and reliable output and then the modified information is displayed on a screen by CG. MLB Eye Caption based on the proposed algorithm has already been used for regular Major League Base-ball (MLB) programs broadcast five over a Korean nationwide TV network and has produced a favorable response from Korean viewer.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.129-140
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• 2006

Quantity Flexibility contract coordinates individually motivated supplier and buyer to the systemwide optimal outcome by effectively allocating the costs of market demand uncertainty. The main feature of the contract is to couple the buyer's commitment to purchase no less than a certain percentage below the forecast with the supplier's guarantee to deliver up to a certain percentage above. In this paper we refine the previous models by adding some realistic features including the upper and lower limits of the purchase. We also incorporate purchase and canceling costs in a cost function to reflect the real world contracting process more accurately. To obtain the solution of the model, we derive a condition for extreme points using the Leibniz's rule and construct an algorithm for finding the optimal solution of the model. Several examples illustrating the algorithm show that the approach is valid and efficient.