• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.372-379
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• 2015

The latest video compression standard (such as H.264/AVC and HEVC) utilizes quarter-pel accuracy motion estimation in order to retain detailed motion information. Many sub-pixel motion estimation algorithms used in the spatial domain usually encounters increment of computational complexity due to embedded interpolation algorithm. In this paper, an approach to measure sub-pixel accuracy motion estimation in frequency domain using shifting matrix is proposed. Complexity can be reduced utilizing shifting matrix algorithm in frequency domain and simulation results demonstrate not only higher PSNR but lower bit rates than spatial domain algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.536-541
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• 2008

This paper proposes a mobility prediction algorithm for the effective handover among hybrid networks. The proposed algorithm is consisted of two mechanisms to predict a mobile terminal's path. First, the mobile terminal will be checking its received signal power level. Then the mobile terminal will judge its path in some network. Second, if the mobile terminal change its path suddenly, it will be dealing with this situation appropriately using the mobile terminal's speed. This paper introduces existing researches and the proposed algorithm. Finally, our algorithm is compared with existing approaches in terms of the handover delay by using the network simulator OPNet version 10.0.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1728-1729
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• 2011

본 연구에서는 안정적인 물 공급과 에너지의 효율적 사용을 위한 단기 물 수요예측알고리즘 개발에 있어서, 지방 소도시 지역의 물 공급패턴에 대한 영향인자를 도출하기 위하여 기상환경인자와 과거 물 공급량에 대한 상관성 분석을 실시하였다. 그리고, 신경회로망 이론 중 ELM알고리즘을 적용한 단기 물 수요예측알고리즘을 개발하여 현장 적용성을 검토하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.93-93
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• 2023

최근 범지구적인 기후변화로 인해 도시유역의 홍수 발생 빈도가 빈번하게 발생하고 있다. 이로 인해 불투수성이 큰 도시지역의 침수 등의 자연재해 증가로 인명 및 재산피해가 발생하고 있다. 이에 따라 하수도의 제 기능을 수행하고 있다면 문제가 없지만 이상기후로 인한 기록적인 폭우에 의해 침수가 발생하고 있다. 홍수 및 집중호우와 같은 극치사상의 발생빈도가 증가됨에 따라 강우 사상의 변동에 따른 하수관로의 수위를 예측하고 침수에 대해 대처하기 위해 과거 수위에 따른 수위 예측은 중요할 것으로 판단된다. 본 연구에서는 수위 예측 연구에 많이 활용되고 있는 시계열 학습에 탁월한 LSTM 알고리즘을 활용한 하수관로 수위 예측을 진행하였다. 데이터의 학습과 검증을 수행하기 위해 실제 하수관로 수위 데이터를 수집하여 연구를 수행하였으며, 대상자료는 서울특별시 강동구에 위치한 하수관로 수위 자료를 활용하였다. 하수관로 수위 예측에는 딥러닝 알고리즘 RNN-LSTM 알고리즘을 활용하였으며, RNN-LSTM 알고리즘은 하천의 수위 예측에 우수한 성능을 보여준 바 있다. 1분 뒤 하수관로 수위 예측보다 5분, 10분 뒤 또는 1시간 3시간 등 다양한 분석을 실시하였다. 데이터 분석을 위해 하수관로 수위값 변동이 심한 1주일을 선정하여 분석을 실시하였다. 연구에는 Google에서 개발한 딥러닝 오픈소스 라이브러리인 텐서플로우를 활용하였으며, 하수관로 수위 고유번호 25-0001을 대상으로 예측을 하였다. 학습에는 2012년 ~ 2018년의 하수관로 수위 자료를 활용하였으며, 모형의 검증을 위해 결정계수(R square)를 이용하여 통계분석을 실시하였다.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2782-2784
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• 2001

최대수요전력 제어기의 실시간 부하전력예측을 위하여 Newton 보외법을 적용하였다. 기존의 선형기법에 비하여 실제 데이터에 가까운 부하전력을 예측할 수 있었다. 이 새로운 알고리즘을 적용함으로써 부하예측을 보다 정확히 할 수 있어 빈번한 부하차단이나 우발적인 차단을 방지하여 설비 운용의 신뢰성을 높일 수 있다. 개선된 알고리즘은 마이컴으로 제어되는 실제 시스템에 적용하여 보다 나은 성능을 얻을 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.655-660
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• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.65-73
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• 2007

This study devotes to compare the accuracy of Top-N recommendations of items transacted on the web site for customers with the accuracy of rank conformity of the real ratings with estimated ratings for customers preference about items generated from two types of collaborative filtering algorithms. One is Neighborhood Based Collaborative Filtering Algorithm(NBCFA) and the other is Correspondence Mean Algorithm(CMA). The result of this study shows the accuracy of Top-N recommendations and the rank conformity of real ratings with estimated ratings generated by CMA are better than that of NBCFA. It would be expected that the customer's satisfaction in Recommender System is more improved by using the prediction result from CMA than NBCFA, and then Using CMA in collaborative filtering recommender system is more efficient than using NBCFA.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.19-23
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• 2017

Energy is a vital resource for the economic growth and the social development for any country. As the industry becomes more sophisticated and the economy more grows, the electricity demand is increasing. So forecasting electricity demand is an important for electricity suppliers. Forecasting electricity demand makes it possible to distribute electricity demand. As the market for Negawatt market began to grow in Korea from 2014, the prediction of electricity consumption demand becomes more important. Moreover, power consumption forecasting provides a way for demand management to be directly or indirectly participated by consumers in the electricity market. We use Genetic Algorithms to predict the energy demand of the fishing industry in Jeju Island by using GDP, per capita gross national income, value add, and domestic electricity consumption from 1999 to 2011. Genetic Algorithm is useful for finding optimal solutions in various fields. In this paper, genetic algorithm finds optimal parameters. The objective is to find the optimal value of the coefficients used to predict the electricity demand and to minimize the error rate between the predicted value and the actual power consumption values.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.259-266
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• 2003

In this paper, we propose a multi-level block matching algorithm using motion information in blocks. In the proposed algorithm, the block-level is decided by the motion degree in the block before motion searching procedure, and then adequate motion searching performs according to the block-level. This improves computational efficiency by eliminating the unnecessary searching Process in no motion or low motion regions, and brings more accurate estimation results by deepening motion searching Process in high motion regions. Simulation results show that the proposed algorithm brings the lower estimation error about 20％ MSE reduction with the fewer blocks pet frame and the operation number was reduced to 56% compared to TSSA and 98% compared to FS -BMA with constant block size.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.24-32
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• 2006

In this paper, we proposed the multimedia call admission control algorithm with the bandwidth reservation based on the prediction of wireless terminal's location to guarantee quality of service for multimedia applications in cellular networks. This algorithm aims at minimizing possible errors In predicting the moving direction of terminals using a mobility prediction scheme. This prediction reduces the size of bandwidth reserved redundantly. In order to evaluate the performance of the algorithm, the blocking rate of new calls and the forced termination rate of hand-off calls are measured and compared the results with those of existing schemes. The results of the experiment revealed that the algorithm presented in this paper achieved better performance with lower call blocking rates and forced-termination rates than those of other methods.