• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제22권1호
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• pp.15-28
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• 2018

Recently Machine Learning algorithms are widely used to process Big Data in various applications and a lot of these applications are executed in run time. Therefore the speed of Machine Learning algorithms is a critical issue in these applications. However the most of modern iteration Machine Learning algorithms use a successive iteration technique well-known in Numerical Linear Algebra. But this technique has a very low convergence, needs a lot of iterations to get solution of considering problems and therefore a lot of time for processing even on modern multi-core computers and clusters. Tchebychev iteration technique is well-known in Numerical Linear Algebra as an attractive candidate to decrease the number of iterations in Machine Learning iteration algorithms and also to decrease the running time of these algorithms those is very important especially in run time applications. In this paper we consider the usage of Tchebychev iterations for acceleration of well-known K-Means and SVM (Support Vector Machine) clustering algorithms in Machine Leaning. Some examples of usage of our approach on modern multi-core computers under Apache Spark framework will be considered and discussed.

• 설비공학논문집
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• 제14권4호
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• pp.350-357
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• 2002

Optimal control algorithms for the full storage ice cooling system were developed by using a dynamic simulation program. Control algorithms for the storage charging mode were developed for the chiller outlet temperature setpoint control and the chiller capacity control. Control algorithms for the storage discharging mode were developed for the proper mode selection, the storage-only mode control, and the storage-priority chiller-shared mode control. Two different cases of the expected outdoor air temperature profile and the expected cooling load profile were used to analyze the effectiveness of these algorithms. Simulation results show the energy savings and the satisfactory controls of the ice storage system. Therefore, control algorithms developed for this study may effectively be used for the improved control of the ice storage cooling system.

• 제어로봇시스템학회논문지
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• 제15권10호
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• pp.1047-1055
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• 2009

Since nuclear and chemical materials could damage people and disturb battlefield missions in a wide region, nuclear/chemical reconnaissance systems utilizing multiple mobile robots are highly desirable for rapid and safe reconnaissance. In this paper, we design a nuclear/chemical reconnaissance system including mobile robots. Also we propose time-efficient trajectory planning algorithms using grid coverage and contour finding methods for reconnaissance operation. For grid coverage, we performed in analysis on time consumption for various trajectory patterns generated by straight lines and arcs. We proposed BCF (Bounded Contour Finding) and BCFEP (Bounded Contour Finding with Ellipse Prediction) algorithms for contour finding. With these grid coverage and contour finding algorithms, we suggest trajectory planning algorithms for single, two or four mobile robots. Various simulations reveal that the proposed algorithms improve time-efficiency in nuclear/chemical reconnaissance missions in the given area. Also we conduct basic experiments using a commercial mobile robot and verify the time efficiency of the proposed contour finding algorithms.

• ETRI Journal
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• 제38권3호
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• pp.540-550
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• 2016

Spectral clustering is a powerful tool for exploratory data analysis. Many existing spectral clustering algorithms typically measure the similarity by using a Gaussian kernel function or an undirected k-nearest neighbor (kNN) graph, which cannot reveal the real clusters when the data are not well separated. In this paper, to improve the spectral clustering, we consider a robust similarity measure based on the shared nearest neighbors in a directed kNN graph. We propose two novel algorithms for spectral clustering: one based on the number of shared nearest neighbors, and one based on their closeness. The proposed algorithms are able to explore the underlying similarity relationships between data points, and are robust to datasets that are not well separated. Moreover, the proposed algorithms have only one parameter, k. We evaluated the proposed algorithms using synthetic and real-world datasets. The experimental results demonstrate that the proposed algorithms not only achieve a good level of performance, they also outperform the traditional spectral clustering algorithms.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 춘계종합학술대회
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• pp.144-147
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• 2001

ATM 망에서는 전송률 기반의 ABR 흐름제어를 위해 다수의 알고리즘들이 제안되고 있다. 이 알고리즘들의 주 목적은 셀 손실률을 회피하고 미사용중인 대역폭을 ABR 트래픽에 의해 사용되게 하는 것이다. 이리한 알고리즘들은 EFCI와 ER 스위치에서 동작하여 ABR 트래픽을 제어하는데 사용된다. 본 논문에서는 이러한 알고리즘들이 다양한 scale network에 적용하여 각 알고리즘들의 특성에 대해 분석하고, 각 알고리즘들의 셀 손실률을 도시하여 그 성능을 비교, 분석하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.315-318
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• 2001

기준신호를 필요로 하지 않는 블라인드 방식의 새로운 LMS 및 MMSE 알고리즘을 제안한다. 디지털 신호의 Finite Constellation 특성을 이용하여 Projection 방식으로 본 알고리즘을 구현했다. 제안 알고리즘의 성능을 증명하기 위해서, AWGN 채널과 다중경로 Rayleigh Fading 채널상황에서 시뮬레이션을 수행하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.331-335
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• 2001

블라인드 형태의 새로운 LMS 알고리즘을 제안한다. 기존의 LMS 알고리즘의 스텝사이즈를 지수를 이용하여 가변시켜서 수렴속도가 향상되도록 한 두가지 방식을 보여준다. 본 제안방식은 디지털 신호의 Finite Constellation 특성을 이용하여 Projection 방식을 이용했다. 제안알고리즘의 성능을 증명하기 위해서, AWGN 채널과 다중경로 Rayleigh Fading 채널상황에서 시뮬레이션을 수행하였다.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.221-232
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• 2021

In recent years, with the existence of huge amounts of data stored in huge databases, the need for developing accurate tools for analyzing data and extracting information and knowledge from the huge and multi-source databases have been increased. Hence, new and modern techniques have emerged that will contribute to the development of all other sciences. Knowledge discovery techniques are among these technologies, one popular technique of knowledge discovery techniques is data mining which aims to knowledge discovery from huge amounts of data. Such modern technologies of knowledge discovery will contribute to the development of all other fields. Data mining is important, interesting technique, and has many different and varied algorithms; Therefore, this paper aims to present overview of data mining, and clarify the most important of those algorithms and their uses.

• 정보보호학회논문지
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• 제12권4호
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• pp.99-114
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• 2002

실행시간이나 전력 소모량 분석 등과 같은 부가채널 공격에 안전하면서도 보다 효율적인 새로운 타원곡선 상수배 알고리즘을 제안한다. 먼저 기존 방식들을 분석하여 잠재적인 문제점들을 지적하고, 이런 문제점들을 제거할 수 있는 간단한 $\pm$1-이진 부호화 방식을 제안한다. 또한 제안 부호화 방식을 이용한 이진 및 고정 윈도우 알고리즘을 기술하고 안전성과 효율성을 분석한다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.1493-1496
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• 2011

Research results for LMS-based algorithms performances using real records of the traffic noise are discussed. The various algorithms based on LMS method are studied regarding their convergence speed and noise reduction index. Most effective algorithms are chosen for implementation in the active noise control barriers. The optimal step size, and number of adaptive filter taps are addressed during parametric study of the algorithms.