• Title/Summary/Keyword: redundant processing

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The Development of a Highly Portable and Low Cost SPOT Image Receiving System

  • Choi, Wook-Hyun;Shin, Dong-Seok;Kim, Tag-Gon
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.25-30
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    • 1999
  • This paper covers the development of a highly portable and low cost SPOT image data receiving system. We followed two design approaches. One is the software-based approach by which most of the real-time processing is handled by software. With the complete software-based design, it is simple to add a function for receiving any additional satellite data. Satellite-specific format handlers including error correction, decompression and decryption can easily be accommodated. On the other approach. we used a general hardware platform, IBM-PC and a low cost SCSI RAID (Redundant Away of Independent Disks), and therefore, we can make a low cost system.

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Detection and Diagnosis Solutions for Fault-Tolerant VSI

  • Cordeiro, Armando;Palma, Joao C.P.;Maia, Jose;Resende, Maia J.
    • Journal of Power Electronics
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    • v.14 no.6
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    • pp.1272-1280
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    • 2014
  • This paper presents solutions for fault detection and diagnosis of two-level, three phase voltage-source inverter (VSI) topologies with IGBT devices. The proposed solutions combine redundant standby VSI structures and contactors (or relays) to improve the fault-tolerant capabilities of power electronics in applications with safety requirements. The suitable combination of these elements gives the inverter the ability to maintain energy processing in the occurrence of several failure modes, including short-circuit in IGBT devices, thus extending its reliability and availability. A survey of previously developed fault-tolerant VSI structures and several aspects of failure modes, detection and isolation mechanisms within VSI is first discussed. Hardware solutions for the protection of power semiconductors with fault detection and diagnosis mechanisms are then proposed to provide conditions to isolate and replace damaged power devices (or branches) in real time. Experimental results from a prototype are included to validate the proposed solutions.

A Study on Configuration Method of TMR Control System for Turbine Control (터빈제어용 3중화 디지털 제어시스템의 구성방식에 관한 연구)

  • Jeong, Chang-Ki;Shin, Yoon-Oh
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.731-733
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    • 1999
  • Distributed Control System has been used for large scale and critical system control such as aerospace industries, chemical and power plant and so on. It is very impotant factors for design of the control system to be reliable and fault-tolerant. These control systems have backup or redundant processing modules for minimizing the time of failure and improving reliability. But such methods have changeover duration from faulty module to healthy one. During that interval, feedback control loop raises bumper and performance of the system become worse. TMR(Triple Modular Redundancy) control system is one of the best reliable ones that can overcome such a mortal drawback. This paper analyzes the components of TMR system functionally and proposes practical and cost effective configuration method for turbine control of thermal power plant.

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Feature Selection Algorithms in Intrusion Detection System: A Survey

  • MAZA, Sofiane;TOUAHRIA, Mohamed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.5079-5099
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    • 2018
  • Regarding to the huge number of connections and the large flow of data on the Internet, Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and redundant features influence on the quality of IDS precisely on the detection rate and processing cost. Feature Selection (FS) is the important technique, which gives the issue for enhancing the performance of detection. There are different works have been proposed, but a map for understanding and constructing a state of the FS in IDS is still need more investigation. In this paper, we introduce a survey of feature selection algorithms for intrusion detection system. We describe the well-known approaches that have been proposed in FS for IDS. Furthermore, we provide a classification with a comparative study between different contribution according to their techniques and results. We identify a new taxonomy for future trends and existing challenges.

Adaptive Sampling for ECG Detection Based on Compression Dictionary

  • Yuan, Zhongyun;Kim, Jong Hak;Cho, Jun Dong
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.13 no.6
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    • pp.608-616
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    • 2013
  • This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

Effect on Preprocessing in SAT with Sudoku Puzzle (수도쿠 퍼즐을 통해서 살펴본 SAT에서 전처리 효과)

  • Kwon, Gi-Hwon
    • Journal of Information Technology Services
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    • v.7 no.2
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    • pp.127-135
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    • 2008
  • The concept of preprocessing is widely used in various computer science area such as compiler and software engineering for the purpose of macro processing and optimization. In addition, preprocessing is also used in SAT solvers in order to eliminate redundant literals and clauses to speed up its solving time before searching the state space. However, there is an unexpected run-time error such as stack-overflow during this step, in case the size of a given set of clauses is huge which impedes SAT solvers. In this case, the preprocessing should be applied at the encoding time to optimize its size. In this paper this idea is applied to several Sudoku problems. As a result, significant improvements are obtained with respect to the number of variables and clauses as well as the solving time compared to the previous works.

Optimizing Speed For Adaptive Local Thresholding Algorithm U sing Dynamic Programing

  • Due Duong Anh;Hong Du Tran Le;Duan Tran Duc
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.438-441
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    • 2004
  • Image binarization using a global threshold value [3] performs at high speed, but usually results in undesired binary images when the source images are of poor quality. In such cases, adaptive local thresholding algorithms [1][2][3] are used to obtain better results, and the algorithm proposed by A.E.Savekis which chooses local threshold using fore­ground and background clustering [1] is one of the best thresholding algorithms. However, this algorithm runs slowly due to its re-computing threshold value of each central pixel in a local window MxM. In this paper, we present a dynamic programming approach for the step of calculating local threshold value that reduces many redundant computations and improves the execution speed significantly. Experiments show that our proposal improvement runs more ten times faster than the original algorithm.

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File Replication and Workload Allocation for a Locally Distributed Database

  • Gil sang Jang
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.24 no.64
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    • pp.1-20
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    • 2001
  • In distributed databases, file replication and workload allocation are important design issues. This paper solves these two issues simultaneously, The primary objective is to minimize the system response time that consists of local processing and communication overhead on a local area network. Workload (query transactions) is assigned among any sites in proportion to the remaining file request service rate of the each server The problem is presented in the form of a nonlinear integer programming model. The problem is proved to be NP-complete and thus an efficient heuristic is developed by employing its special structure. To illustrate its effectiveness, it is shown that the proposed heuristic is based on the heuristic of a non-redundant allocation that was provided to be effective. The model and heuristics are likely to provide more effective distributed database designs.

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RB 복소수 필터구조와 DLMS 알고리듬을 이용한 Pipelined ADFE의 설계

  • 안병규;신경욱
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.11a
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    • pp.534-537
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    • 1999
  • This paper describes a design of pipelined adaptive decision-feedback equalizer (PADFE) for high bit-rate wireless digital communication systems. To enhance the throughput rate of ADFE, two pipeline stages are inserted into the critical path of ADFE by using delayed least-mean-square (DLMS) algorithm. Redundant binary (RB) arithmetic is applied to all the data processing of ADFE including filter laps and coefficient update blocks. When compared with conventional methods based on two's complement arithmetic, the proposed approach reduces arithmetic complexity, as well as results in a very simple complex-valued filter structure, thus suitable for VLSI implementation. The design parameters (filter tap, coefficient and internal bit-width, etc.) and equalization performance (bit error rate, convergence speed, etc.) are analyzed by algorithm-level simulation using COSSAP. The PADFE was designed using VHDL and Synopsys, and mapped into two ALTERA FLEX10k100 FPGAs.

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ModifiedFAST: A New Optimal Feature Subset Selection Algorithm

  • Nagpal, Arpita;Gaur, Deepti
    • Journal of information and communication convergence engineering
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    • v.13 no.2
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    • pp.113-122
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    • 2015
  • Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.