• 제목/요약/키워드: redundant methods

검색결과 212건 처리시간 0.029초

Visualization of Dynamic Simulation Data for Power System Stability Assessment

  • Song, Chong-Suk;Jang, Gil-Soo;Park, Chang-Hyun
    • Journal of Electrical Engineering and Technology
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    • 제6권4호
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    • pp.484-492
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    • 2011
  • Power system analyses, which involve the handling of massive data volumes, necessitate the use of effective visualization methods to facilitate analysis and assist the user in obtaining a clear understanding of the present state of the system. This paper introduces an interface that compensates for the limitations of the visualization modules of dynamic security assessment tools, such as PSS/e and TSAT, for power system variables including generator rotor angle and frequency. The compensation is made possible through the automatic provision of dynamic simulation data in visualized and tabular form for better data intuition, thereby considerably reducing the redundant manual operation and time required for data analysis. The interface also determines whether the generators are stable through a generator instability algorithm that scans simulation data and checks for an increase in swing or divergence. The proposed visualization methods are applied to the dynamic simulation results for contingencies in the Korean Electric Power Corporation system, and have been tested by power system researchers to verify the effectiveness of the data visualization interface.

단일칩 컴퓨터의 결함허용 스케쥴링 성능 분석 (Performance Analysis of Fault-Tolerant Scheduling in a Uniprocessor Computer)

  • 김성수
    • 한국정보처리학회논문지
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    • 제5권6호
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    • pp.1639-1651
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    • 1998
  • 본 논문에서는 RESO(REcomputation with Shifted Operands)와 같은 시간 결함허용 기법을 이용한 단일칩 컴퓨터의 결함허용성을 평가하기 위한 분석 및 시뮬레이션 모델을 제안한다. 단일칩으로 들어오는 모든 작업은 이중화 처리된다고 가정하고 1차 작업과 2차 작업의 효율적인 처리를 위한 세가지 스케쥴링 방법들을 제안하고 분석한다. 고안된 스케쥴링 방법들은 결함과 결함허용으로 인한 응답시간 지연이 시스템의 비용에 미치는 영향을 단일칩의 부하와 결함발생율에 따라서 평가한다. 제안된 모델을 사용하면 비용, 단일칩의 부하 및 결함발생율과 같은 실험 파라미터에 기초한 최적 지연($\kappa$)를 가지는 결함허용 스케쥴을 구할 수 있다.

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다중기기 취약도곡선의 지진상관계수 조합 절차 (Combination Procedure for Seismic Correlation Coefficient in Fragility Curves of Multiple Components)

  • 김정한;김시영;최인길
    • 한국지진공학회논문집
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    • 제24권3호
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    • pp.141-148
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    • 2020
  • For the important safety system, two or more units of identical equipment or redundant components with similar function were installed to prevent abnormal failure. If the failure probability of such equipment is independent, this redundancy could increase the system safety remarkably. However, if the failure of each component is highly correlated by installing in a structure or experiencing an earthquake event, the expected redundancy effect will decrease. Therefore, the seismic correlation of the equipment should be evaluated quantitatively for the seismic probabilistic safety assessment. The correlation effect can be explained in the procedure of constructing fragility curves. In this study, several methodologies to quantify the seismic correlation in the failure probability calculation for multiple components were reviewed and two possible ways considering the realistic situation were selected. Simple examples were tested to check the applicability of these methods. The conversion method between these two methods was suggested to render the evaluation using the advantages of each method possible.

체계신뢰성에 기초한 교량의 시스템여용성 및 저항강도 평가 (SYSTEM RELIABILITY-BASED EVALUATION OF BRIDGE SYSTEM REDUNDANCY AND STRENGTH)

  • 조효남;이승재;임종권
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1993년도 가을 학술발표회논문집
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    • pp.240-247
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    • 1993
  • The precise prediction of reserved carrying capacity of bridge as a system is extremely difficult especially when the bridges are highly redundant and significantly deteriorated or damaged. This paper is intended to propose a new approach for the evaluation of reserved system carrying capacity of bridges in terms of equivalent system-strength, which may be defined as a bridge system-strength corresponding to the system reliability of the bridge. This can be derived from an inverse process based on the concept of FOSM form of system reliability index. It may be emphasized that this approach is very useful for the evaluation of the deterministic system redundancy and reserve strength which are measured in terms of either probabilistic system redundancy factor and reserve factor or deterministic system redundancy factor and reserve factor. The system reliability of bridges is formulated as a parallel-series model obtained from the FAM(Failure Mode Approach) based on the major failure mechanisms. AFOSM and IST methods are used for the reliability analysis of the proposed models. The proposed approach and method for the system redundancy and reserve safety/strength are applied to the safety assessment of actual RC and steel box-girder bridges. The results of the evaluation of reserved system safety or bridge system-strength in terms of the system redundancy and the system safety/strength are significantly different from those of element reliability-based or conventional methods.

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Feature Selection to Mine Joint Features from High-dimension Space for Android Malware Detection

  • Xu, Yanping;Wu, Chunhua;Zheng, Kangfeng;Niu, Xinxin;Lu, Tianling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권9호
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    • pp.4658-4679
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    • 2017
  • Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

PRM과 포텐셜 필드 기법에 기반한 다자유도 머니퓰레이터의 충돌회피 경로계획 (Collision-Free Path Planning for a Redundant Manipulator Based on PRM and Potential Field Methods)

  • 박정준;김휘수;송재복
    • 제어로봇시스템학회논문지
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    • 제17권4호
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    • pp.362-367
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    • 2011
  • The collision-free path of a manipulator should be regenerated in the real time to achieve collision safety when obstacles or humans come into the workspace of the manipulator. A probabilistic roadmap (PRM) method, one of the popular path planning schemes for a manipulator, can find a collision-free path by connecting the start and goal poses through the roadmap constructed by drawing random nodes in the free configuration space. The path planning method based on the configuration space shows robust performance for static environments which can be converted into the off-line processing. However, since this method spends considerable time on converting dynamic obstacles into the configuration space, it is not appropriate for real-time generation of a collision-free path. On the other hand, the method based on the workspace can provide fast response even for dynamic environments because it does not need the conversion into the configuration space. In this paper, we propose an efficient real-time path planning by combining the PRM and the potential field methods to cope with static and dynamic environments. The PRM can generate a collision-free path and the potential field method can determine the configuration of the manipulator. A series of experiments show that the proposed path planning method can provide robust performance for various obstacles.

An Efficient Complex Event Processing Algorithm based on Multipattern Sharing for Massive Manufacturing Event Streams

  • Wang, Jianhua;Lan, Yubin;Lu, Shilei;Cheng, Lianglun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권3호
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    • pp.1385-1402
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    • 2019
  • Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

A Configurable Software-based Approach for Detecting CFEs Caused by Transient Faults

  • Liu, Wei;Ci, LinLin;Liu, LiPing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권5호
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    • pp.1829-1846
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    • 2021
  • Transient faults occur in computation units of a processor, which can cause control flow errors (CFEs) and compromise system reliability. The software-based methods perform illegal control flow detection by inserting redundant instructions and monitoring signature. However, the existing methods not only have drawbacks in terms of performance overhead, but also lack of configurability. We propose a configurable approach CCFCA for detecting CFEs. The configurability of CCFCA is implemented by analyzing the criticality of each region and tuning the detecting granularity. For critical regions, program blocks are divided according to space-time overhead and reliability constraints, so that protection intensity can be configured flexibly. For other regions, signature detection algorithms are only used in the first basic block and last basic block. This helps to improve the fault-tolerant efficiency of the CCFCA. At the same time, CCFCA also has the function of solving confusion and instruction self-detection. Our experimental results show that CCFCA incurs only 10.61% performance overhead on average for several C benchmark program and the average undetected error rate is only 9.29%. CCFCA has high error coverage and low overhead compared with similar algorithms. This helps to meet different cost requirements and reliability requirements.

저전력 움직임 추정을 위한 데이터 재사용 스캔 방법 (Data Reusable Search Scan Methods for Low Power motion Estimation)

  • 김태선;선우명훈
    • 전자공학회논문지
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    • 제50권9호
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    • pp.85-91
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    • 2013
  • 본 논문은 저전력 움직임 추정장치를 구현하기 위한 전역 탐색 및 고속 탐색용 데이터 재사용 스캔 방법을 제안한다. 제안하는 최적화된 소 구역 분할방법은 탐색 영역을 여러 개의 소 구역으로 나누어 기존의 smart snake scan 방법과 비교 하였을때 같은 양의 데이터 재사용에 필요한 재구성 가능한 레지스터 어레이를 반으로 줄일 수 있다. 또한 제안하는 중심 편향 탐색 스캔방법은 다양한 고속탐색 알고리즘의 데이터 재사용 가능성을 향상 시킬 수 있다. 제안하는 탐색 순서는 기존의 래스터 스캔과 snake scan 방법에 비해 평균적으로 각각 26%와 16.1%의 반복된 데이터 로딩을 줄일 수 있다. 따라서 제안하는 스캔 방법은 메모리의 접근 횟수를 줄일 수 있기 때문에 저전력과 고성능의 움직임 추정 구현에 적합하다.

기계학습 접근법에 기반한 유전자 선택 방법들에 대한 리뷰 (A review of gene selection methods based on machine learning approaches)

  • 이하정;김재직
    • 응용통계연구
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    • 제35권5호
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    • pp.667-684
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    • 2022
  • 유전자 발현 데이터는 각 유전자에 대해 mRNA 양의 정도를 나타내고, 그러한 유전자 발현량에 대한 분석은 질병 발생에 대한 메커니즘을 이해하고 새로운 치료제와 치료 방법을 개발하는데 중요한 아이디어를 제공해오고 있다. 오늘날 DNA 마이크로어레이와 RNA-시퀀싱과 같은 고출력 기술은 수천 개의 유전자 발현량을 동시에 측정하는 것을 가능하게 하여 고차원성이라는 유전자 발현 데이터의 특징을 발생시켰다. 이러한 고차원성으로 인해 유전자 발현 데이터를 분석하기 위한 학습 모형들은 과적합 문제에 부딪히기 쉽고, 이를 해결하기 위해 차원 축소 또는 변수 선택 기술들이 사전 분석 단계로써 보통 사용된다. 특히, 사전 분석 단계에서 우리는 유전자 선택법을 이용하여 부적절하거나 중복된 유전자를 제거할 수 있고 중요한 유전자를 찾아낼 수도 있다. 현재까지 다양한 유전자 선택 방법들이 기계학습의 맥락에서 개발되어왔다. 본 논문에서는 기계학습 접근법을 사용하는 최근의 유전자 선택 방법들을 집중적으로 살펴보고자 한다. 또한, 현재까지 개발된 유전자 선택 방법들의 근본적인 문제점과 앞으로의 연구 방향에 대해 논의하고자 한다.