• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.458-467
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• 1994

It has been well known that the assumption of full state availability is one of the most important restrictions to the practical realization of VSCS. And several attempts to alleviate the assumption had been made. however, it is not easy to find a positive scheme among them. Recently, an output feedback variable structure control system(OFVSCS) was proposed and the effectiveness of the scheme was validated for the disturbance free systems. The purpose of this study is to propose a robust OFVSCS that have the robust properties against process parameter variations and external disturbances by extending the basic OFVSCS and to evaluate its control performances. The ROFVSES is composed of dynamic switching function and output feedback switching control inputs that are constructed by the use of the unknown vector modeling technique. With the proposed schems, existence of sliding mode is guaranteed and any nonzero bias can be suppressed in the face of disturbances and process parameter variations as far as well-known matching condition is satisfied. Due to the fact that the ROFVSCS is driven by small number of measured informations, the practical application of VSCS for the systems with unmeasurable states and for high order systems, the conventional schemes cannot be applied, is possible with the proposed scheme. It is noticeable that the implementation cast of VSCS can be considerably reduced without sacrifice of control performances by adopting ROFVSCS since there is no need to measure the states with high measurement cost.

• ETRI Journal
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• v.29 no.5
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• pp.545-558
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• 2007

This paper presents an efficient semantic service discovery scheme called UbiSearch for a large-scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.

• Journal of International Society for Simulation Surgery
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• v.3 no.1
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• pp.22-27
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• 2016

Background Craniosynostosis management using distraction osteogensis represent a challenge for surgeons due to the great variability of the skull deformity even within the same etiology. The ability to apply the simulation surgery for improving the preoperative planning for distraction osteogensis could improve the results.Planning and Simulation 14 patients presented with craniosynostosis had been subjected to simulation surgery prior to real surgery. 3D CT scans was obtained upon patient admission. Adjustment of all skull position to Frankfort horizontal plane was done. 3 different distraction osteogensis plans were done for each patient according to the skull morphology. For each plane, movement for each bone segment was done according to the pre-planned distraction vectors. Also the distances of distractions were pre-determined according to the cephalic index as well as brain volume. Intraoperatively, we choose the most appropriate plan for the patient by the surgeon. At the end of distraction, 3D CT scan was obtained, and was compared to the simulation plan. Also the distance and the direction of distraction was compared to that of the plan. Accordingly, the distance was almost matching that of the simulation surgery, however the vector of distraction was not matched.Conclusion Preoperative stimulation planning for craniosynostosis patient is very valuable tool in the surgical management of craniosynostosis patients.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.433-435
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• 1993

The purpose of this study is to propose a robust OFVSCS that have the robust properties against process parameter variations and external disturbances by extending the basic OFVSCS and to evaluate its control performances. The ROFVSCS is composed of dynamic switching surfaces and output feedback switching control inputs that are constructed by the use of the unknown vector modeling technique. With the proposed scheme. existence of sliding mode is guaranteed and any nonzero bias can be suppressed in the face of disturbances and process parameter variations as far as well-known matching condition is satisfied. Due to the fact that the ROFVSCS is driven by small number of measured information, the practical application of VSCS for the systems with unmeasurable states and for high order systems. that conventional schemes cannot be applied, is possible with the proposed scheme. It is noticeable that implementation cost or VSCS can be considerably reduced without sacrifice of control performances by adopting ROFVSCS since there is no need to measure the states with high measurement cost.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.145-149
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• 2014

In this study, using X-ray cargo container scanning device and to differentiate the concept of three-dimensional information extraction applied for X-ray scanning device as an ingredient in the rotation of the X-Ray Linear Pushbroom Stereo System by introducing the geometric How to model was introduced. Three-dimensional information obtained through the matching of a single voxel space filled with a random vector operations for each voxel in the three dimensional shape reconstruction algorithm using the definition, and in time, the time required for each step were analyzed. Using OpenCV in each step by applying parallelization techniques approximately 1.8 times improvement in the processing time of the check, but do not meet the target within one minute levels. The other hand, X-ray images by the primary process to convert the point View the results of real-time stereo through a three-dimensional could feel the comfort level.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.516-525
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• 2005

Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.162-165
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• 2017

The proposed paper extracts the region of interest from the x-lay input image and compares it with the reference image. The x-ray image has the same shape, but the size, direction and position of the object are photographed differently. In this way, we measure the erection difference of darkness and darkness using the similarity measurement method for the same object. Distance measurement also calculates the distance between two points with vector coordinates (x, y, z) of x-lay data. Experimental results show that the proposed method improves the accuracy of ROI extraction and the reference image matching time is more efficient than the conventional method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.99-104
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• 2021

The technology of estimating a movement trajectory using a monocular camera such as a smartphone and composing a surrounding 3D image is key not only in indoor positioning but also in the metaverse service. The most important thing in this technique is to estimate the coordinates of the moving camera center. In this paper, a new algorithm for geometrically estimating the moving distance is proposed. The coordinates of the 3D object point are obtained from the first and second photos, and the movement distance vector is obtained using the matching feature points of the first and third photos. Then, while moving the coordinates of the origin of the third camera, a position where the 3D object point and the feature point of the third picture coincide is obtained. Its possibility and accuracy were verified by applying it to actual continuous image data.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.1
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• pp.13-21
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• 2006

Though authentication using biometric techniques has conveniences for people, security problems like the leakage of personal bio-information would be serious. Even if cancelable biometric is a good solution for the problems, only a few biometric authentication scheme with cancelable feature has been published. In this paper, we suggest a face authentication scheme with two security factors: password and face image. Using matching algorithm in the permuted domain, our scheme is designed to be cancelable in the sense that templates that is composed of permutation and weight vector can be changed freely.