• Journal of information and communication convergence engineering
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• 제6권1호
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• pp.1-5
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• 2008

In this paper, we propose and analyze the AMC (Adaptive Modulation and Coding) system with efficient turbo coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique. The proposed algorithm adopts extrinsic information from a MAP (Maximum A Posteriori) decoder with iterative decoding as a priori probability in two decoding procedures of V-BLAST scheme; the ordering and the slicing. Also, we consider the AMC system using the conventional turbo coded V-BLAST technique that simply combines the V-BLAST scheme with the turbo coding scheme. And we compare the proposed decoding algorithm to a conventional V-BLAST decoding algorithm and a ML (Maximum Likelihood) decoding algorithm. In addition, we apply a STD (Selection Transmit Diversity) scheme to the systems for better performance improvement. Results indicate that the proposed systems achieve better throughput performance than the conventional systems over the entire SNR range. In terms of transmission rate performance, the suggested system is close in proximity to the conventional system using the ML decoding algorithm.

• Industrial Engineering and Management Systems
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• 제8권4호
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• pp.228-238
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• 2009

This paper first presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first involves a number of location known retailers choosing one factory to supply their demands from a number of factories whose locations are to be determined. The goal is to minimize the transportation and manufacturing cost to satisfy the demands. The problem is then augmented into the second problem, where the procurement cost of the raw materials from a chosen material supplier (from a number of suppliers) is considered for each factory. Economic beneficial is taken into account in the cost evaluation. Therefore, the partner selections will influence the cost of the supply chain significantly. To solve these problems, an agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM consecutively and alternatively enable and disable the advancement of agent gaming and the evolution of genetic computation. Computation results on solving a number of examples by the AGGAHM were compared with those from methods of a general genetic algorithm and a mutual frozen genetic algorithm. Results showed that the AGGAHM outperforms the methods solely using genetic algorithms. In addition, various parameter settings are tested and discussed to facilitate the supply chain designs.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2004년도 제22회 춘계학술대회논문집
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• pp.15-25
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• 2004

This paper outlines a new convergence acceleration de-signed to solve scramjet flowfields with zones of re-circulation. Named the “marching-window”, the algorithm consists of performing pseudo-time iterations on a minimal width subdomain composed of a sequence of cross-stream planes of nodes. The upstream boundary of the subdomain is positioned such that all nodes upstream exhibit a residual smaller than the user-specified convergence threshold. The advancement of the downstream boundary follows the advancement of the upstream boundary, except in zones of significant streamwise ellipticity where a streamwise ellipticity sensor ensures its continuous progress. Compared to the standard pseudo-time marching approach, the march-ing-window is here seen to decrease the work required for convergence by up to 24 times for supersonic flows with little streamwise ellipticity and by up to 8 times for supersonic flows with large streamwise separated regions. The memory requirements are observed to be reduced sixfold by not allocating memory to the nodes not included in the computational subdomain. The marching-window satisfies the same convergence criterion as the standard pseudo-time stepping methods, hence resulting in the same converged solution within the tolerance of the user-specified convergence threshold. The extension of the marching-window to the weakly-ionized Navier-Stokes equations is also discussed.

• 한국컴퓨터정보학회논문지
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• 제12권6호
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• pp.139-146
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• 2007

컴퓨터시스템에서 메모리시스템은 계층적인 구조를 갖는다. 외부기억장치에 해당하는 디스크는 용량이 크고 가격이 저렴하지만 동작은 기계적인 특성에 기반을 두고 있어 주기억장치에 비하여 매우 느리고 디스크의 성능 향상도 매우 느리게 이루어지고 있지만 처리기는 반도체기술의 발전으로 속도향상이 매우 빠르게 이루어지고 있다. 따라서 저속의 디스크 입출력서브시스템은 컴퓨터시스템의 전체 성능에 병목(bottle neck)을 일으키고 있다. 컴퓨터시스템내의 디스크 입출력 서브시스템의 성능을 개선함으로 컴퓨터시스템의 전체 성능개선을 실현하는 연구가 이루어지고 있다. 본 논문에서는 처리기가 필요로 할 가능성이 높은 디스크블록을 버퍼캐시와 디스크 캐시에 효율적으로 유지하여 디스크블록 평균접근시간을 줄임으로 컴퓨터시스템의 성능을 향상시키는 개선된 알고리즘인 multi-level LRU 기법을 제안하였고 이를 버퍼캐시와 디스크 캐시를 가지는 시스템에 적용하였다. 시뮬레이션을 통하여 제안된 방안의 성능을 평가하였다.

• 대한안전경영과학회지
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• 제7권5호
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• pp.1-8
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• 2005

The consequences of rapid industrial advancement, diversified types of business and unexpected industrial accidents have caused a lot of damage to many unspecified persons both in a human way and a material way Although various previous studies have been analyzed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. The main objective of this study is to find an optimal algorithm for data analysis of industrial accidents and this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and AnswerTree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work chosen from 19,574 data related to construction industries during three years ($2002\sim2004$) in Korea.

• 전기학회논문지P
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• 제53권2호
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• pp.43-50
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• 2004

Percentage differential characteristic relaying(PDR) has been recognized as the principal basis for power transformer protection. Second harmonic restraint PDR has been widely used for magnetizing inrush in practice. Nowadays, relaying signals can contain 2nd harmonic component to a large extent even in a normal state, and 2nd harmonic ratio indicates a tendency of relative reduction because of the advancement of material. Further, as the power system voltage becomes higher and more underground cables are used, larger 2nd harmonic component in the differential current under internal fault is observed. And then, conventional 2nd harmonic restraint PDR exposes some doubt in reliability. It is, therefore, necessary to develop a new algorithm for performance improvement of conventional protective relaying. This paper proposes an advanced protective relaying algorithm by using voltage-current trend and flux-differential current slope characteristic. To evaluate the performance of the proposed algorithm, we have made comparative studies of PDR, fuzzy relaying and DWT relaying. The paper is constructed power system model including power transformer, utilizing the WatATP, and data collection is made through simulation of various internal faults and inrush. As the results of test, the new proposed algorithm was proven to be faster and more reliable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1674-1688
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• 2023

The remarkable advancement of quantum steganography offers enhanced security for quantum communications. However, there is a significant concern regarding the potential misuse of this technology. Moreover, the current research on identifying malicious quantum steganography is insufficient. To address this gap in steganalysis research, this paper proposes a specialized quantum steganalysis algorithm. This algorithm utilizes quantum machine learning techniques to detect steganography in general quantum secure communication schemes that are based on pure states. The algorithm presented in this paper consists of two main steps: data preprocessing and automatic discrimination. The data preprocessing step involves extracting and amplifying abnormal signals, followed by the automatic detection of suspicious quantum carriers through training on steganographic and non-steganographic data. The numerical results demonstrate that a larger disparity between the probability distributions of steganographic and non-steganographic data leads to a higher steganographic detection indicator, making the presence of steganography easier to detect. By selecting an appropriate threshold value, the steganography detection rate can exceed 90%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2316-2332
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• 2024

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XESformatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a userfriendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.64-74
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• 2015

Because of the burgeoning demand of the energy, the countries are finding sustainable solutions for these emerging challenges. Demand Side Management is playing a significant role in managing the demand with an aim to support the electrical grid during the peak hours. However, advancement in controls and communication technologies, the aggregators are appearing as a third party entity in implementing demand response program. In this paper, a detailed mathematical framework is discussed in which the aggregator acts as an energy service provider between the utility and the consumers, and facilitate the consumers to actively participate in demand side management by introducing the new concept of demand reduction bidding (DRB) under constrained direct load control. Paper also presented an algorithm for the proposed framework and demonstrated the efficacy of the algorithm by considering few case studies and concluded with simulation results and discussions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.345-350
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• 2002

In this study, researchers classifying the artificial flaws in semiconductor packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method fur entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.