• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.1013-1032
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• 2000

At present, the scale of Electronic Commerce through internet has been rapidly increasing due to the development of information & communication technology, and aggregated to 2.4 billion dollar in America last year (1998). The market scale of worldwide electronic commerce is also presumed to be about 130 billion dollar in 2000, and to occupy more than 20% of the whole world trade in world 2020. Since the right of trademark, despite of being effective only in registered nations on the principle of territorialism, is unified on the cyber space of internet without domestic barrier or local limitation which make it easier to conduct the distribution of information rapidly through the address-internet domain name, those are very important that the systematic dispute-solving plan on problems such as decision of its Act and international jurisdiction to be established, in an effort to prevent the newly emerging dispute instances such as trademark infringement and improper competitiveness. In addition, it is natural that on the threshold of the electronic commerce age which formed with an unified area without the worldwide specific regulation, each country including us makes haste with the enactment of "electronic commerce Act" aiming at coming into force in 1999, in keeping with getting through "non-tariff law on electronic commerce" by U. S. parliament on May, 1998. In view of the properties of electronic commerce transactions through internet, there are the large curtailment of distributive channel, surmounting of restrictions on transaction area, space and time and the easy feedback with consumer and the cheap-required capital, from which the problems may arise - registration of trademark, the trademark infringement of domain name and the protection of prestigious trademark. Therefore, it is necessary to take the counter-measure, with a view of reviewing the infringement of trademark and domain name and the instances of each national precedent and to preventing the disputes. The improvement of the persistent system should be needed to propel the harmonious protection of those holding trademark right's credit and demanders' expectant profit by way of the righteous use of trademark.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.133-146
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• 2001

In a dynamic load distribution policies, each node gathers the current system sates information before making a decision on load balancing. Load balancing policies based on this strategy can suffer from processor thrashing. In this paper, we propose a new algorithm which attempts to decrease the frequency of the processor thrashing, the algorithm is based on the integration of three components. The first, the algorithm of which determine the size of jobs be transferred. The second, negotiation protocol with obtains a mutual agreement between a sender and a receiver on the transferring job size. And the third, a symmetrically-initiated location policy. The algorithm proposed in this paper used Siman IV as simulation tool to prove the improvement of performance. I analyzed the result of simulation, and compared with related works. The mean response time shows that there are no difference with existing policy, but appear a outstanding improvement in high load. The thrashing coefficient that shows the average response time, CPU overhead and the thrashing ratio at both the receiving and sending node has been used in the analysis. A significant improvement in the average response time and the CPU overhead ratio was detected using our algorithm when an overhead occurred in the system over other algorithm. The thrashing coefficient differed in the sending node and the receiving node of the system. Using our algorithm, the thrashing coefficient at the sending node showed more improvement when there was an overhead in the system, proving to be more useful. Therefore, it can be concluded that the thrashing ratio can be reduce by properly setting the maximum and minimum value of the system’s threshold queue.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.546-554
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• 2011

Near targets in the infrared (IR) images have the steady feature for inner region and the transient feature for the boundary region. Based on these features, this paper proposes a new method to extract the fine target shape of near targets in the IR images. First, we detect the boundary region of the candidate targets using the local variance weighted information entropy (WIE) of the original images. And then, a coarse target region can be estimated based on the labeling of the boundary region. For the coarse target region, we use the opening filter with an adaptive structure element to extract the fine target shape. The decision of the adaptive structure element size is optimized for the width information of target boundary by calculating the average WIE in the enlarged windows. The experimental results show that a proposed method has better extraction performance than the previous threshold algorithms.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.25-32
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• 2015

With the increased frequency of crime such as assaults and sexual violence, the reliance on CCTV in arresting criminals has increased as well. However, CCTV, which should be monitored by human labor force at all times, has limits in terms of budget and man-power. Thereby, the interest in intelligent security system is growing nowadays. Expanding the techniques of an objects behavior recognition in previous studies, we propose a system to detect forms of violence between 2~3 objects from images obtained in CCTV. It perceives by detecting the object with the difference operation and the morphology of the background image. The determinant criteria to define violent behaviors are suggested. Moreover, provable decision metric values through measurements of the number of violent condition are derived. As a result of the experiments with the threshold values, showed more than 80% recognition success rate. A future research for abnormal behaviors recognition system in a crowded circumstance remains to be developed.

• Atmosphere
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• v.24 no.2
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• pp.151-158
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• 2014

This study investigated a method for the discrimination of precipitation type using thickness of geopotential height at 1000~850 hPa and improved Matsuo's scheme over South Korea using 7 upper-level observations data during winter time from 2003 to 2008. With this research, it was suggested that thickness between snow and rain should range from 1281 to 1297 gpm at 1000~850 hPa. This threshold was suitable for determining precipitation type such as snow, sleet and rain and it was verified by investigation at 7 upper-level observation and 10 surface observation data for 3 years (2009~2011). In addition, precipitation types were separated properly by Matsuo's scheme and its improved one, which is a fuction of surface air temperature and relative humidity, when they lie in mixed sectors. Precipitation types in the mixed sector were subdivided into 5 sectors (rain, rain and snow, snow and rain, snow, and snow cover). We also present the decision table for monitoring and predicting precipitation types using model output of Korea Local Analysis and Prediction System (KLAPS) and observation data.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.100-105
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• 2017

This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.3
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• pp.1-8
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• 2000

This paper presents a simulation model of the Quadrature detector to demodulate FSK signal, which is widely used in wireless paging system for its simple hardware implementation and economics of It fabrication. Quadrature detecter has nonlinear phase characteristic for changes linear changes of input signal frequency. So until now Quadrature detector system analysis remained a difficult problem and performance analysis has not been carried out adequately On these backgrounds, this paper presents the FSK signal demodulation process using Quadrature detector and optimal performance derived from digital simulation technique. First, PSN(Phase Shift Network) which is composed of analog RLC tank circuit is transformed into its equivalent digital transfer function using First-order-hold theorem. Though the demodulated outputs of the Quadrature detector for 4FSK are 4-level signals, only 2 comparators are used and it is shown that optimal performance can be obtained by choosing operation parameter Q value and threshold level decision which are proposed herein.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1406-1411
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• 2012

An energy detection based spectrum sensing has been found to be vulnerable to the noise power uncertainty. A cooperative spectrum sensing with an energy detector has appeared as one of the solutions to alleviate this difficulty. However, its performance analysis in a fading environment has not been reported yet in the literature. Motivated by this, this paper presents the performance analysis of the scheme by extending our previous work on evaluating the performance of an energy detector in the presence of noise power uncertainty. The analysis shows that the false alarm probability and detection probability gets higher as the sensing time and/or the number of the secondary users in the OR based cooperative spectrum sensing scheme increase when the noise power uncertainty exists.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.450-460
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• 2017

T wave is cardiac parameters that represent ventricular repolarization, it is very important to diagnose arrhythmia. Several methods for detecting T wave have been proposed, such as frequency analysis and non-linear approach. However, detection accuracy is at the lower level. This is because of the overlap of the P wave and T wave depending on the heart condition. We propose T wave detection algorithm based on target area extraction through QRS cancellation and moving average. For this purpose, we detected Q, R, S wave from noise-free ECG(electrocardiogram) signal through the preprocessing method. And then we extracted P, T target area by applying decision rule for four PAC(premature atrial contraction) pattern another arrhythmia through moving average and detected T wave using RT interval and threshold of RR interval. The performance of T wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 95.32%.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.145-161
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• 2014

Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.