• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.48-57
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• 2009

This paper presents optimal design of direct-driven PM wind generator using MADS (Mesh Adaptive Direct Search). Optimal design of the direct-driven PM Wind Generator, combined with MADS and FEM (Finite Element Method), has been performed to maximize the Annual Energy Production (AEP) over the whole wind speed characterized by the statistical model of the wind speed distribution. In particular, the newly applied MADS contributes to reducing the computation time when compared with Genetic Algorithm (GA) implemented with the parallel computing method.

• Water for future
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• v.11 no.2
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• pp.54-61
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• 1978

An attemption of synthesizing and forecasting of monthly river flow has been made by employing a linear stochastic difference equation model. As one of the linear stochestic difference equation model, an ARIMA Type is tested to find the suitability of the model to the monthly river flows. On the assumption of the stationary covariacne of differenced monthly river flows the model is identrfield and is evaluated so that the residuale have the minimum variance. Finally a test is performed to finld the residerals beings White noise. Monthly river flows at six stations in Han River Basin are applied for case studies. It was found that the difference operator is a good measure of forecasting the monthly river flow.

• KNOM Review
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• v.24 no.2
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• pp.48-55
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• 2021

Ethereum is an open software platform based on blockchain technology that enables the construction and distribution of distributed applications. Ethereum uses a fully distributed connection method in which all participating nodes participate in the network with equal authority and rights. Ethereum networks use Kademlia-based node discovery protocols to retrieve and store node information. Ethereum is striving to stabilize the entire network topology by implementing node discovery protocols, but systems for monitoring are insufficient. This paper develops a WireShark dissector that can receive packet information in the Ethereum node discovery process and provides network packet measurement results. It can be used as basic data for the research on network performance improvement and vulnerability by analyzing the Ethereum node discovery process.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.510-519
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• 2011

Intra mode decision is a useful coding tool in Distributed Video Coding (DVC) for improving DVC coding efficiency for video sequences having fast motion. A major limitation associated with the existing intra mode decision methods, however, is that its efficiency highly depends on user-specified thresholds or modeling parameters. This paper proposes an entropy-based method to address this problem. The probabilities of intra and Wyner?Ziv (WZ) modes are determined firstly by examining correlation of pixels in spatial and temporal directions. Based on these probabilities, entropy of the intra and the WZ modes are computed. A comparison based on the entropy values decides a coding mode between intra coding and WZ coding without relying on any user-specified thresholds or modeling parameters. Experimental results show its superior rate-distortion performance of improvements of PSNR up to 2 dB against a conventional Wyner?Ziv coding without intra mode decision. Furthermore, since the proposed method does not require any thresholds or modeling parameters from users, it is very attractive for real life applications.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.389-393
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• 2008

Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.69-79
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• 2009

Today's Internet is one of the necessaries of our life. Anomalies of the Internet provoke social problems. For that reason, Internet Measurement which studies characteristics on Internet traffic attracts pubic attention. Recently, Traffic Dispersion Graph (TDG), a novel traffic analysis method, was proposed. The TDG is not a statistical analysis method but a graphical visualization method on interactions among network components. In this paper, we propose a new anomaly detection paradigm and its technique using TDG. The existing studies have focused on detecting anomalous packets of flows. On the other hand, we focus on detecting the sources of anomalous traffic. To realize our paradigm, we designed the TDG Clustering method. Through this method, we could classify anomalous hosts infected by various worm viruses. We obtained normal traffic through dropping traffic of the anomalous hosts. Especially, we expect that the TDG clustering method can be applied to real-time anomaly detection because calculations of the method are fast.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.259-265
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• 2012

Recently, many research works are focusing on DVC (Distributed Video Coding) system for low complexity encoder. Most DVC systems need feedback channel for parity bit control to achieve the good RD performances, however, this causes the system to have high decoding latency and is considered as one of the most critical problems for real implementation. In order to overcome this problem, this paper proposes an effective distributed video decoding method using adaptive LDPCA frame-based parity bit request estimation. The proposed method applies for the pixel-domain Wyner-Ziv system and exploits the statistical characteristics between adjacent LDPCA frames to estimate adaptively the parity bit request. Through computer simulations, it is shown that the proposed method achieves about 80% of latency reduction compared to the conventional no-estimation DVC system.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.279-288
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• 2000

The impact of land slope to the degree of flow divergence was considered employing distributional applications of slope exponents in the now directlOn algoriUnns. Lmear, exponential and ]X)wer law of distributional functIons were employed to address the variation of slope exponents m a terrain analysis. Dongok subwatershed at Wichun test watershed was selected as a study area. Digital Elevation Models of 20m, 30m, 40m and 50m grid size were made to perfonn the analysis. Various calcualtion methodologies of topographic index and the impact of grid sizes were investigated in terms of statistical and spatial aspects. DIstributional applications of slope e.xponents made it possible to represent the flow divergence and convergence about the ten-ain characteristics. The Monte~Carlo method was used to simulate six runoff events to check the impact of topographic factor in the runoff simulation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.3
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• pp.191-198
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• 2007

Marine accidents are increasing as time goes on, in spite of lots of efforts are given. Marine accidents can be classified 3 categories those are ship's condition, navigator's condition and weather condition. In this paper, statistical analysis were carried using marine accidents data from 1997 to 2006. In order to analyze accident rate by time zone, ship's speed and finding distant, SPSS variance analysis was carried out. Results are followed. There was significant difference between time zone 20${\sim}$04 hours and other time zones. The accident rate in daytime was bigger than that at night. In case of the speed at collision, the speed of 5${\sim}$10 knot has significant difference to other speed cases. In finding distant cases, the case of less than 1 mile has significant difference to other distant cases.