• Journal of KIISE:Databases
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• v.34 no.5
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• pp.448-464
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• 2007

Location-Based Services (LBSs) provide results to queries according to the location of the client issuing the query. In LBS, techniques such as caching and prefetching are effective approaches to reducing the data transmission from a server and query response time. However, they can lead to cache inefficiency and network overload due to the client's mobility and query pattern. To solve these drawbacks, we propose a semantic prefetching (SP) scheme using prefetching segment concept and improved cache replacement policies. When a mobile client enters a new service area, called semantic prefetching area, proposed scheme fetches the necessary semantic information from the server in advance. The mobile client maintains the information in its own cache for query processing of location-dependent data (LDD) in mobile computing environment. The performance of the proposed scheme is investigated in relation to various environmental variables, such as the mobility and query pattern of user, the distributions of LDDs and applied cache replacement strategies. Simulation results show that the proposed scheme is more efficient than the well-known existing scheme for range query and nearest neighbor query. In addition, applying the two queries dynamically to query processing improves the performance of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.108-115
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• 2009

In this paper, we propose a novel true-motion estimation technique supporting efficient frame error concealment for error-resilient video coding. In general, it is important to accurately obtain the true-motion of objects in video sequences for effectively recovering the corrupted frame due to transmission errors. However, the conventional motion estimation (ME) technique, which minimizes a sum of absolute different (SAD) between pixels of the current block and the motion-compensated block, does not always reflect the true-movement of objects. To solve this problem, we introduce a new metric called an absolute difference of motion vectors (ADMV) which is the distance between motion vectors of the current block and its motion-compensated block. The proposed ME method can prevent unreliable motion vectors by minimizing the weighted combination of SAD and ADMV. In addition, the proposed ME method can significantly improve the performance of error concealment at the decoder since error concealment using the ADMV can effectively recover the missing motion vector without any information of the lost frame. Experimental results show that the proposed method provides similar coding efficiency to the conventional ME method and outperforms the existing error-resilient method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.1-8
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• 2008

The belief propagation method that has been studied recently yields good performance in disparity extraction. The method in which a target function is modeled as an energy function based on Markov random field(MRF), solves the stereo matching problem by finding the disparity to minimize the energy function. MRF models provide robust and unified framework for vision problem such as stereo and image restoration. the belief propagation method produces quite correct results, but it has difficulty in real time implementation because of higher computational complexity than other stereo methods. To relieve this problem, in this paper, we propose a fast algorithm of the belief propagation method. Energy function consists of a data term and a smoothness tern. The data term usually corresponds to the difference in brightness between correspondences, and smoothness term indicates the continuity of adjacent pixels. Smoothness information is created from messages, which are assigned using four different message arrays for the pixel positions adjacent in four directions. The processing time for four message arrays dominates 80 percent of the whole program execution time. In the proposed method, we propose an algorithm that dramatically reduces the processing time require in message calculation, since the message.; are not produced in four arrays but in a single array. Tn the last step of disparity extraction process, the messages are called in the single integrated array and this algorithm requires 1/4 computational complexity of the conventional method. Our method is evaluated by comparing the disparity error rates of our method and the conventional method. Experimental results show that the proposed method remarkably reduces the execution time while it rarely increases disparity error.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1821-1828
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• 2010

Laser shock peening(LSP) is an innovative surface treatment technique, and it has been successfully used to improve the fatigue performance of metallic components. It is widely known, that cracks caused by metal fatigue occur only at the location where the metal is subject to tension, and not at the location where the metal is subjected to compression. Therefore, LSP can be employed to improve fatigue life because it generates a high-magnitude compressive residual stress on the surface and interior of metallic components. In this study, we analyzed the applicability of the LSP method in improving fatigue performance and evaluated the various parameters that influence the compressive residual stress. Further, we analyzed the change in the mechanical properties such as surface dynamic stress and the compressive residual stress on the surface and interior of metallic components.

• The KIPS Transactions:PartA
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• v.19A no.2
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• pp.101-112
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• 2012

In recently years, distributed real-time software has performed important roles in various areas. Real-time applications should be performed with satisfying strict constraints on response time. Usually real-time applications are developed on the real-time supporting middleware such as TMO(Time-triggered, Message-triggered Object), CORBA/RT, and RTAI. However, it is not easy to develop applications using them since these real-time middleware are unfamiliar to programmers. In this paper, we propose an automatic code generator for real-time application based on TMO in order to reduce development costs. For increasing or reflecting the characteristics of TMO into the design model, SpM and SvM methods are added into the class diagram, which have time constraints as their properties. And behaviors of them are represented as separated regions on state machine diagram in different abstract level. These diagrams are inputted into TMO-based code automatic generator, which generates details of the TMO class. Our approach has advantages for decreasing effort and time for making real time software by automatically generating TMO codes without detailed knowledge of TMO.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.1-6
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• 2001

Eigenface method in face recognition is useful due to its insensitivity to large variations in facial expression and facial details. However its low recognition rate necessitates additional researches. In this paper, we present an efficient method for improving the recognition rate in face recognition using eigenface feature. For this, we performs a comparative study of three different classifiers which are i) a single prototype (SP) classifier, ii) a nearest neighbor (NN) classifier, and iii) a standard feedforward neural network (FNN) classifier. By evaluating and analyzing the performance of these three classifiers, we shows that the distribution of eigenface features of face image is not compact and that selections of classifier and sample training data are important for obtaining higher recognition rate. Our experiments with the ORL face database show that 1-NN classifier outperforms the SP and FNN classifiers. We have achieved a recognition rate of 91.0% by selecting sample trainging data properly and using 1-NN classifier.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.467-476
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• 2017

In this paper, we analyze Generalized Feistel Network(GFN) Type I, Type II, Type III that round function use SP update function, secret S-box and $k{\times}k$ MDS matirx. In this case an attacker has no advantage about S-box. For each type of GFN, we analyze and restore secret S-box in 9, 6, 6 round using the basis of integral cryptanalysis with chosen plaintext attack. Also we restore secret S-box in 16 round of GFN Type I with chosen ciphertext attack. In conclusion, we need $2^{2m}$ data complexity and ${\frac{2^{3m}}{32k}},{\frac{2^{3m}}{24k}},{\frac{2^{3m}}{36k}}$ time complexity to restore m bit secret S-box in GFN Type I, Type II, Type III.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.538-547
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• 2001

Currently, 2D real-time image coding techniques had great developments and many related products were commercially developed. However, these techniques lack the capability of handling 3D actuality, occurred by the advent of virtual reality, because they handle only the temporal transmission for 2D image. Besides, many 3D virtual reality researches have been studied in computer graphics. Since the graphical researches were limited to the application of artificial models, the 3D actuality for real scene images could not be managed also. Therefore, a new 3D model extraction method based on stereo vision, that can deal with real scene virtual reality, is proposed in this paper. The proposed method adapted a compact genetic algorithm using population-based incremental learning (PBIL) to matching environments, in order to reduce memory consumption and computational time of conventional genetic algorithms. Since the PBIL used a probability vector and competitive learning, the matching algorithm became simple and the computation load was considerably reduced. Moreover, the matching quality was superior than conventional methods. Even if the characteristics of images are changed, stable outputs were obtained without the modification of the matching algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.1-11
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• 2006

In this paper, we propose the novel video retrieval algorithm using non-parametric based motion classification in the shot-based video indexing structure. The proposed system firstly gets the key frame and motion information from each shot segmented by scene change detection method, and then extracts visual features and non-parametric based motion information from them. Finally, we construct real-time retrieval system supporting similarity comparison of these spatio-temporal features. After the normalized motion vector fields is created from MPEG compressed stream, the extraction of non-parametric based motion feature is effectively achieved by discretizing each normalized motion vectors into various angle bins, and considering a mean, a variance, and a direction of these bins. We use the edge-based spatial descriptor to extract the visual feature in key frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures.