• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.1034-1041
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• 2013

Liquidated Damages is damages that have to be paid when a debtor could usually work off that which they owe, but didn't due to causes imputable. However, currently the Defense Acquisition Program Administration contracts with domestic businesses in case of delay of implementation occurs; they have to pay damages of deferment unlimitedly as a penalty concept, not in compensation about delay. With this in account, conflicts between the two continuesly happen. DAPA wastes administration and counter business costs increasingly burdening their budget. Defense and military procurement need to revise the compensation of deferment system. This paper analyzes the problems about that system, which is applied to domestic business, and also compares it with that of industrialized countries and suggests measures of set price caps in compensation of the deferment system.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.168-175
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• 2003

Until now, substring selectivities have been estimated by two steps. First step is to build up a count-suffix tree, which has statistical information about substrings, and second step is to estimate substring selectivity using it. However, it's actually impossible to build up a count-suffix tree from biological sequences because their lengths are too long. So, this paper proposes a novel data structure, count q-gram tree, consisting of fixed length substrings. The Count q-gram tree retains the exact counts of all substrings whose lengths are equal to or less than q and this tree is generated in 0(N) time and in site not subject to total length of all sequences, N. This paper also presents an estimation technique, k-MO. k-MO can choose overlapping length of splitted substrings from a query string, and this choice will affect accuracy of selectivity and query processing time. Experiments show k-MO can estimate very accurately.

• Journal of KIISE:Information Networking
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• v.32 no.1
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• pp.34-50
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• 2005

Recently, various proposals for supporting network mobility, which provides efficient Internet access when a network formed within a vehicle moves around as a unit, have emerged. The schemes in those proposals, though, manifest some major drawbacks with respect to scalability: If the number of mobile nodes within a mobile network is large, the handoff latency would increase greatly, causing communication disruption; Data delivery to a node within a nested mobile network nay suffer extremely inefficient pinball routing. We propose a scalable network mobility supporting mechanism named SNEMOS (Scalable NEtwork Mobility Support), which resolves the above two major problems of the existing schemes. The performance of SNEMOS is compared with the existing schemes through extensive simulations. The numerical results show that SNEMOS outperforms the existing schemes with respect to handoff latency hop counts of routing paths, packet delivery time, header overhead in data packets, and signaling overhead.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6708-6714
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• 2015

Various types of multimedia contents have been widely spread and distributed with the Internet that is easy to use. Meanwhile, Multimedia contents can bright a social problem because juveniles can access such harmful contents easily through the Internet. This paper proposes a method to determine if an input image is harmful or not, using an neural network. The proposed method first detects a face region from an input image through MCT features. The method then extracts skin color regions using color features and obtains candidate nipple areas from the extracted skin regions. Subsequently, we determine if the input image is harmful, by filtering out non-nipple regions using the artificial neural network. Experimental results show that the proposed method can effectively determine the harmfulness of input images.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.41-49
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• 2008

Fingerprint classification is useful to reduce the matching time of a huge fingerprint identification system by categorizing fingerprints into predefined classes according to their global features. Although global features are distributed diversly because of the uniqueness of a fingerprint, previous fingerprint classification methods extract global features non-adaptively from the fixed region for every fingerprint. We propose an novel method that extracts features adaptively for each fingerprint in order to classify various fingerprints effectively. It extracts ridge directional values as feature vectors from the region after searching the feature region by calculating variations of ridge directions, and classifies them using support vector machines. Experimental results with NIST4 database show that we have achieved a classification accuracy of 90.3% for the five-class problem and 93.7% for the four-class problem, and proved the validity of the proposed adaptive method by comparison with non-adaptively extracted feature vectors.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.297-300
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• 2015

In medical ultrasonography, transit time and contrast enhancement patterns are considered as important parameters to analyze liver diseases. In many recent researches, time-intensity curves(TIC) have been used for calculating the transit time of the contrast agents. However, the intensity curve may include the variations which are caused by the micro-bubble effect of contrast agents. In this paper, we propose a complementary approach to diagnostic parameter extraction which utilizes a density information as well as the intensity data. The proposed technique improves the accuracy in extraction of the transit time and velocity of contrast agents for detection and characterization of focal liver lesions. Through the experiments using a set of clinical data, we show that the proposed methods can improve the reliability of the parametric image data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1702-1709
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• 1994

In the postprocessing of Hangul recognition system, the storage structure of contextual information is an important matter for the recognition rate and speed of the entire system. Trie in general is used to represent the context as word dictionary, but the memory space efficiency of the structure is low. Therefore we propose a new structure for word dictionary that has better space efficiency and the equivalent merits of trie. Because Hangul is a compound language, the language can be represented by phonemes or by characters. In the representation by phonemes(P-mode) the retrieval is fast, but the space efficiency is low. In the representation by characters(C-mode) the space efficiency is high, but the retrieval is slow. In this paper the two representation methods are combined to form a hybrid representation(H-mode). At first an optimal level for the combination is selected by two characteristic curves of node utilization and dispersion. Then the input words are represented with trie structure by P-mode from the first to the optimal level, and the rest are represented with sequentially linked list structure by C-mode. The experimental results for the six kinds of word set show that the proposed structure is more efficient. This result is based on the fact that the retrieval for H-mode is as fast as P-mode and the space efficiency is as good as C-mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1518-1527
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• 1994

An algorithm for BPSK demodulation of which channel is an electric distribution line is developed, and realized in this paper. To realize the BPSK demodulation by microprocessor, BPSK signal that is received through the distribution line must be converted to digital signal. A hardware which converts BPSK signal to digital one has been designed in this paper, and an algorithm for BPSK demoduation of which channel is distribution line has been also developed in algorithm for BPSK demoduation of which channel is distribution line has been also developed in this paper by paying the attention to the fact that a modulated point appears up and down according to the rising edge and falling edge of the modulated binary signal if the carrier frequency is even times to the modulated binary signal, and by paying the attention to the fact that the signal duration or modulated point is twice of the other point. The microprocessor demodulation system with the algorithm has been realized. The system proved to have 0.02%(or less) bit error rate in real BPSK demodulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1942-1950
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• 2013

This paper suggests a new method of detecting attacks of network traffic by visualizing original traffic data and applying multi-class SVM (support vector machine). The proposed method first generates 2D images from IP and ports of transmitters and receivers, and extracts linear patterns and high intensity values from the images, representing traffic attacks. It then obtains variance of ports of transmitters and receivers and extracts the number of clusters and entropy features using ISODATA algorithm. Finally, it determines through multi-class SVM if the traffic data contain DDoS, DoS, Internet worm, or port scans. Experimental results show that the suggested multi-class SVM-based algorithm can more effectively detect network traffic attacks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.475-481
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• 2019

The importance of performance-based design feedback is being emphasized when it comes to the potential impact that affects all the lifecycle of the building. However, the latency and disconnection of domain expert in the sector of AEC/FM remain current obstacles between design and performance feedback. It is hard to utilize performance feedback information for design exploration and support design decision making during the conceptual phase of design. Using parametric design, this paper proposes various design alternatives from a set of rules and constraints defined by algorithms for the geometric configurations of an Office Building. A Building Performance Analysis (BPA) was to developed using Autodesk® Revit® 2019 which integrates Autodesk® Green Building Studio® to predict its sufficient daylighting conditions of the LEED v4's Daylighting Autonomy (DA). The parametric-based performance feedback of this study outlines potential design improvements for further exploration in application to the early design process.