• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1072-1077
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• 2017

Mean-reverting analysis refers to a way of estimating the underlining tendency after new data has evoked the variation in the equilibrium state. In this paper, we propose a new method to interpret the specular portraits of Premature Ventricular Contraction(PVC) arrhythmia by applying K-means unsupervised learning algorithm on electrocardiogram(ECG) data. Aiming at this purpose, we applied a mean-reverting model to analyse Heart Rate Variability(HRV) in terms of the modified poincare plot by considering PVC rhythm as the component of disrupting the homeostasis state. Based on our experimental tests on MIT-BIH ECG database, we can find the fact that the specular patterns portraited by K-means clustering on mean-reverting HRV data can be more clearly visible and the Euclidean metric can be used to identify the discrepancy between the normal sinus rhythm and PVC beats by the relative distance among cluster-centroids.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.575-587
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• 2004

In this paper. a new Fast Expectation-Maximization algorithm(FEM) is proposed. Firstly the K-means algorithm is modified to reduce the number of iterations for finding the initial values that are used as the initial values in EM process. Conventionally the Initial values in K-means clustering are chosen randomly. which sometimes forces the process of clustering converge to some undesired center points. Uniform partitioning method is added to the conventional K-means to extract the proper initial points for each clusters. Secondly the effect of posterior probability is emphasized such that the application of Maximum Likelihood Posterior(MLP) yields fast convergence. The proposed FEM strengthens the characteristics of conventional EM by reinforcing the speed of convergence. The superiority of FEM is demonstrated in experimental results by presenting the improvement results of EM and accelerating the speed of convergence in parameter estimation procedures.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2015.11a
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• pp.242-243
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• 2015

Fault detection using optical emission spectra with modified K-means cluster analysis and principal component anal ysis are demonstrated for inductive coupl ed pl asma cl eaning processes. The optical emission spectra from optical emission spectroscopy (OES) are used for measurement. Furthermore, Principal component analysis and K-means cluster analysis algorithm is modified and applied to real-time detection and sensitivity enhancement for fluorocarbon cleaning processes. The proposed techniques show clear improvement of sensitivity and significant noise reduction when they are compared with single wavelength signals measured by OES. These techniques are expected to be applied to various plasma monitoring applications including fault detections as well as chamber cleaning endpoint detection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1316-1332
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• 2012

Formation flying is an important technology that enables high cost-effective organization of outer space aircrafts. The ad-hoc wireless network based on direct-sequence ultra-wideband (DS-UWB) techniques is seen as an effective means of establishing wireless communication links between aircrafts. In this paper, based on the theory of matched filter and error bits correction, a hybrid detection algorithm is proposed for realizing multiuser detection (MUD) when the DS-UWB technique is used in the ad-hoc wireless network. The matched filter is used to generate a candidate code set which may contain several error bits. The error bits are then recognized and corrected by an novel error-bit corrector, which consists of two steps: code mapping and clustering. In the former step, based on the modified optimum MUD decision function, a novel mapping function is presented that maps the output candidate codes into a feature space for differentiating the right and wrong codes. In the latter step, the codes are clustered into the right and wrong sets by using the K-means clustering approach. Additionally, in order to prevent some right codes being wrongly classified, a sign judgment method is proposed that reduces the bit error rate (BER) of the system. Compared with the traditional detection approaches, e.g., matched filter, minimum mean square error (MMSE) and decorrelation receiver (DEC), the proposed algorithm can considerably improve the BER performance of the system because of its high probability of recognizing wrong codes. Simulation results show that the proposed algorithm can almost achieve the BER performance of the optimum MUD (OMD). Furthermore, compared with OMD, the proposed algorithm has lower computational complexity, and its BER performance is less sensitive to the number of users.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.529-538
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• 2006

Separating a reentry vehicle into warhead and body is a conventional and efficient means of producing a huge decoy and increasing the kinetic energy of the warhead. This procedure causes the radar to track the body, whose radar cross section is larger, and ignore the warhead, which is the most important part of the reentry vehicle. However, the procedure is difficult to perform using standard tracking criteria. This study presents a novel tracking algorithm by integrating input estimation and modified probabilistic data association filter to solve this difficulty in a clear environment. The proposed algorithm with a new defined association probability in this filter provides a good tracking capability for the warhead ignoring the radar cross section. The simulation results indicate that the errors between the estimated and the warhead trajectories are reduced to a small interval in a short time. Therefore, the radar can produce a beam to illuminate to the right area and keep tracking the warhead all the way. In conclusion, this algorithm is worthy of further study and application.

• Journal of KIISE
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• v.45 no.1
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• pp.61-68
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• 2018

The identification of genes that contribute to the prediction of prognosis in patients with cancer is one of the challenges in providing appropriate therapies. To find the prognostic genes, several classification models using gene expression data have been proposed. However, the prediction accuracy of cancer prognosis is limited due to the heterogeneity of cancer. In this paper, we integrate microarray data with biological network data using a modified PageRank algorithm to identify prognostic genes. We also predict the prognosis of patients with 6 cancer types (including breast carcinoma) using the K-Nearest Neighbor algorithm. Before we apply the modified PageRank, we separate samples by K-Means clustering to address the heterogeneity of cancer. The proposed algorithm showed better performance than traditional algorithms for prognosis. We were also able to identify cluster-specific biological processes using GO enrichment analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.550-555
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• 2007

This paper is concerned with the active vibration control of building structure by means of the active tuned mass damper and the modified positive position feedback controller. To this end, one-degree-of-freedom spring-mass-damper system equipped with ATMD is considered. The stability condition for the addressed system when applying the proposed PPF controller is derived by Routh-Hurwitz stability criterion. The stability condition shows that the modified PPF controller is absolutely stable if the controller gain is positive, so that the modified PPF controller can be used without difficulty. Theoretical study shows that the modified PPF controller can effectively suppress vibrations as the original PPF controller does in smart structure applications. To investigate the validity of the modified PPF controller, a simple experimental structure with an ATMD system driven by DC motor was built. The modified PPF control algorithm was implemented on Atmel 128 microcontroller. The experimental result shows that the modified PPF controller can also suppress vibrations for the real structure.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.224-230
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• 2008

This paper is concerned with the active vibration control of building structure by means of the active tuned mass damper and the modified positive position feedback controller. To this end, one-degree-of-freedom spring-mass-damper system equipped with ATMD is considered. The stability condition for the addressed system when applying the proposed PPF controller is derived by Routh-Hurwitz stability criterion. The stability condition shows that the modified PPF controller is absolutely stable if the controller gain is positive. so that the modified PPF controller can be used without difficulty. Theoretical study shows that the modified PPF controller can effectively suppress vibrations as the original PPF controller does in smart structure applications. To investigate the validity of the modified PPF controller, a simple experimental structure with an ATMD system driven by DC motor was built. The modified PPF control algorithm was implemented on Atmel 128 microcontroller. The experimental result shows that the modified PPF controller can also suppress vibrations for the real structure.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.32-35
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• 2007

Bioinformatics의 목표는 생물학적인 질의를 해결하는 것과 생물학자들이 수집된 데이터를 분석하고 검색을 하여 생물학자들이 정확한 일을 수행하는 것이다. 인터넷은 여러 조사 그룹의 데이터베이스에 동시에 접근가능한 수단을 제공했으나 이러한 분산 환경에서 많은 양의 데이터는 전송 시의 시간 지연 문제와 최종 검색시의 느린 검색 속도 문제를 나타낸다. 데이터 클러스터링은 데이터의 검색시 이러한 문제점을 해결하기 위하여 이용될 수 있는 방법이지만 단순 적용시에는 데이터의 양에 비례하는 실행 시간이 또 다른 문제를 발생시킨다. 본 논문에서는 바이오데이터의 효율적인 클러스터링을 위한 개선된 분산 클러스터링 시나리오와 이를 위해 수정된 K-means 알고리즘을 제시한다. 최종 실험 결과는 20% 이상 향상된 실행 속도를 보여준다.