• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.1
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• pp.61-69
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• 2006

SSO (Single Sign On), which allows users to have an access to a various systems through a single authentication, has been receiving much attention from many enterprises due to the user convience through a single authentication and the recent security features based on PKI. An emerging authentication management system called EAM has further enhanced the efficiency and stability of the enterprise IT infrastructrure systems. In this article, the basic concept and characteristics of the existing SSO systems are analyzed and a new SSO model, based on PKI where authentication load is balanced via multiple circulators, is presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.333-336
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• 1996

The sign language is a method of communication for deaf person. For sign communication, sign language and manual alphabet are used continuously. In this paper is proposed a system which recognize Korean sign language(KSL) and Korean manual alphabet(KMA) continuously. For recognizing KSL and KMA, basic elements for sign language, namely, the 14 hand directions, 23 hand postures, and 14 hand orientations are used. At first, this system recognize current motion state using speed and change of speed in motion by state automata. Using state, basic element classifiers using Fuzzy Min-Max Neural Network and Fuzzy Rule are executed. Meaning of signed gesture is selected by using basic elements which was recognized.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.105-110
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• 2022

Traffic sign recognition plays an important role in solving traffic-related problems. Traffic sign recognition and classification systems are key components for traffic safety, traffic monitoring, autonomous driving services, and autonomous vehicles. A lightweight model, applicable to portable devices, is an essential aspect of the design agenda. We suggest a lightweight convolutional neural network model with residual blocks for traffic sign recognition systems. The proposed model shows very competitive results on publicly available benchmark data.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1128-1140
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• 2009

In this paper, we present a patient real-time vital sign information transmission system to effectively support developing real-time communication service by using a real-time object model named TMO (Time-Triggered Message-Triggered Object). Also, we describe the application environment as the ICU(Intensive Care Unit) to guarantee real-time service message with TMO structure in distributed network systems. We have to design to obtain useful vital sign information, which is generated at parsing data receiver modulor of HIS with TMO structure, that is offered by the central monitor. Vital sign informations of central monitor is composed of the raw data of several bedsite patient monitors. We are willing to maintain vital sign information of real time and continuity that is generated from the bedsite patient monitor. It is able to apply to remote medical examination and treatment. we proposed integration method between a vital sign database systems and hospital information systems. In the real time simulation techniques based on TMO object modeling, We have observed several advantages to the TMO structuring scheme. TMO object modeling has a strong traceability between requirement specification and design.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.178-186
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• 2006

We propose and analyze a robust adaptive fuzzy controller for nonlinear systems without a priori knowledge of the sign of the input gain function. No assumptions are made about the type of nonlinearities of the system, except that such nonlinearities are smooth. The uncertain nonlinearities are captured by the fuzzy systems that have been proven to be universal approximators. The proposed control scheme completely overcomes the singularity problem that occurs in the indirect adaptive feedback linearizing control. Projection in the estimated parameters and switching in the control input are both not required. The stability of the closed-loop system is guaranteed in the Lyapunov viewpoint.

• Korea Science and Art Forum
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• v.19
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• pp.281-292
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• 2015

For this study, I conducted a survey investigating current situation, user preference, and field experiment. Hospitals utilizing digital sign systems at least five years were selected, which are connected with visual elements (layout, typo, color) used in waiting areas and elements of the systems (time, video time line). The results obtained from the field survey showed that digital sign systems used the color of typo and background contrasted to one another to increase explicitness and to ensure easy understanding of contents. In addition, the Gothic typo with relatively high legibility was adopted. Time and video timeline, which characterize digital sign systems, showed the advertising screens of the hospitals and the guidance of medical treatment at regular intervals. Moreover, survey results on user satisfaction showed that a majority of respondents indicated they had difficulty in understanding digital information conveyed from digital sign systems due to time setting for rotational speed or the small size of typo although most of the users had previous experience with digital sign systems. The highest proportion of respondents (n=86, 86%) answered that information related to medical departments was what they sought most frequently and that this kind of information should be importantly considered in digital sign systems. For the experiment, new samples with restructured contents of current digital sign systems were created and tested while keeping its design unchanged as well as applying these new samples. Study participants were in their 20s through 50s. When the size of typo was larger under the same conditions for all age groups, study participants found the desired information approximately 3.5 seconds faster. In addition, those in their 20-30s and 40-50s showed the time difference of 4.7 seconds for small typo and 6 seconds for large typo, which suggested that there was a difference by age in the amount of time taken in the experiment to find the desired information from the rotating digital sign system regardless of age and the size of typo.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.105.2-105
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• 2001

This paper studies continuous Korean Sign Language (KSL) recognition using color vision. In recognizing gesture words such as sign language, it is a very difficult to segment a continuous sign into individual sign words since the patterns are very complicated and diverse. To solve this problem, we disassemble the KSL into 18 hand motion classes according to their patterns and represent the sign words as some combination of hand motions. Observing the speed and the change of speed of hand motion and using state automata, we reject unintentional gesture motions such as preparatory motion and meaningless movement between sign words. To recognize 18 hand motion classes we adopt Hidden Markov Model (HMM). Using these methods, we recognize 5 KSL sentences and obtain 94% recognition ratio.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.47-55
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• 2000

In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.