• Title/Summary/Keyword: Discrete Support

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Component Classification and Specification on Active Security Architecture (능동보안 아키텍쳐를 위한 컴포넌트 분류 및 명세방법)

  • 김상영;김재웅;황선명
    • Journal of Korea Multimedia Society
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    • v.7 no.1
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    • pp.113-125
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    • 2004
  • Active networks aim to provide a software framework that enables active network applications to customize the processing their communications. Active security component architecture focuses on the support of reuse system by active security component. The architecture is standard layer to acquire, understand, and assemble component, and it has to support a guideline for component identification, search and customization. In this paper we present the active security architecture as a standard model of discrete active network solution, and we propose the method for component classification and specification.

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Decision Support System by using Tunable Simulation for Optimally Mixed Systems (조정 가능한 시뮬레이션을 사용하여 최적 혼성 시스템을 찾아내기 위한 의사 결정 지원시스템 구축)

  • Kim, Sung-Soo
    • IE interfaces
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    • v.10 no.3
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    • pp.209-216
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    • 1997
  • This mixed push and pull production system defines that all stages are not ordered by either of the production systems. Some stages are ordered by a push-type production system and the other stages are ordered by a pull-type production system. A decision support system is built by using a combination of optimization program and the "tunable" SIMAN discrete-event simulation for the implementation of an optimally mixed production system. Finding this optimal system requires 6 CPU hours for the case study on a Pentium. Both the simulation and optimization model are validated with a case study of Phoenix company that manufactures transmitters. This paper uses survey from experts in this company for evaluation and validation of this system.

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Replacement Condition Detection of Railway Point Machines Using Data Cube and SVM (데이터 큐브 모델과 SVM을 이용한 철도 선로전환기의 교체시기 탐지)

  • Choi, Yongju;Oh, Jeeyoung;Park, Daihee;Chung, Yongwha;Kim, Hee-Young
    • Smart Media Journal
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    • v.6 no.2
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    • pp.33-41
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    • 2017
  • Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure caused by the aging effect can significantly affect railway operations with potentially disastrous consequences, replacement detection of point machine at an appropriate time is critical. In this paper, we propose a replacement condition detection method of point machine in railway condition monitoring systems using electrical current signals, after analyzing and relabeling domestic in-field replacement data by means of OLAP(On-Line Analytical Processing) operations in the multidimensional data cube into "does-not-need-to-be replaced" and "needs-to-be-replaced" data. The system enables extracting suitable feature vectors from the incoming electrical current signals by DWT(Discrete Wavelet Transform) with reduced feature dimensions using PCA(Principal Components Analysis), and employs SVM(Support Vector Machine) for the real-time replacement detection of point machine. Experimental results with in-field replacement data including points anomalies show that the system could detect the replacement conditions of railway point machines with accuracy exceeding 98%.

On methods for extending a single footfall trace into a continuous force curve for floor vibration serviceability analysis

  • Chen, Jun;Peng, Yixin;Ye, Ting
    • Structural Engineering and Mechanics
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    • v.46 no.2
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    • pp.179-196
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    • 2013
  • An experimentally measured single footfall trace (SFT) from a walking subject needs to be extended into a continuous force curve, which can then be used as load for floor vibration serviceability assessment, or on which further analysis like discrete Fourier transform can be conducted. This paper investigates the accuracy, applicability and parametrical sensitivity of four extension methods, Methods I to IV, which extends the SFT into a continuous time history by the walking step rate, stride time, double support proportion and the double support time, respectively. Performance of the four methods was assessed by comparing their results with the experimentally obtained reference footfall traces in the time and frequency domain, and by comparing the vibrational response of a concrete slab subjected to the extended traces to that of reference traces. The effect of the extension parameter on each method was also explored through parametrical analysis. This study finds that, in general, Method I and II perform better than Method III and IV, and all of the four methods are sensitive to their extension parameter. When reliable information of walking rate or gait period is available in the test, Methods I or II is a better choice. Otherwise, Method III, with the suggested extension parameter of double support time proportion, is recommended.

Improving Voice-Service Support in Cognitive Radio Networks

  • Homayounzadeh, Alireza;Mahdavi, Mehdi
    • ETRI Journal
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    • v.38 no.3
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    • pp.444-454
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    • 2016
  • Voice service is very demanding in cognitive radio networks (CRNs). The available spectrum in a CRN for CR users varies owing to the presence of licensed users. On the other hand, voice packets are delay sensitive and can tolerate a limited amount of delay. This makes the support of voice traffic in a CRN a complicated task that can be achieved by devising necessary considerations regarding the various network functionalities. In this paper, the support of secondary voice users in a CRN is investigated. First, a novel packet scheduling scheme that can provide the required quality of service (QoS) to voice users is proposed. The proposed scheme utilizes the maximum packet transmission rate for secondary voice users by assigning each secondary user the channel with the best level of quality. Furthermore, an analytical framework developed for a performance analysis of the system, is described in which the effect of erroneous spectrum sensing on the performance of secondary voice users is also taken into account. The QoS parameters of secondary voice users, which were obtained analytically, are also detailed. The analytical results were verified through the simulation, and will provide helpful insight in supporting voice services in a CRN.

Vehicle License Plate Extraction and Verification Using Compounded Feature Information and Support Vector Machines (복합 특성 정보와 SVM을 이용한 차량 번호판 추출 및 검증)

  • Kim, Ha-Young;Ahn, Myung-Seok;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.493-496
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    • 2005
  • In this paper, we propose a new approach to detect candidate area of vehicle license plate using compounded color and vertical edge information it's own. Also, we propose a verification course, to compressed image generated by Fast DCT, using SVM to increase accuracy of extracted vechicle license plate area. Proposed method is consider that vehicle's position, become a object of it's license plate recognition, has various angle, scale and include enough environment informations. As a experimental results, proposed method shows a superior performance compared with the case that not includes verification course using SVM.

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Comparison of support vector machines enabled WAVELET algorithm, ANN and GP in construction of steel pallet rack beam to column connections: Experimental and numerical investigation

  • Hossein Hasanvand;Tohid Pourrostam;Javad Majrouhi Sardroud;Mohammad Hasan Ramasht
    • Structural Engineering and Mechanics
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    • v.87 no.1
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    • pp.19-28
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    • 2023
  • This paper describes the experimental investigation of steel pallet rack beam-to-column connec-tions. Total behavior of moment-rotation (M-φ) curve and the effect of particular characteristics on the behavior of connection were studied and the associated load strain relationship and corre-sponding failure modes are presented. In this respect, an estimation of SPRBCCs moment and rotation are highly recommended in early stages of design and construction. In this study, a new approach based on Support Vector Machines (SVMs) coupled with discrete wavelet transform (DWT) is designed and adapted to estimate SPRBCCs moment and rotation according to four input parameters (column thickness, depth of connector and load, beam depth,). Results of SVM-WAVELET model was compared with genetic programming (GP) and artificial neural networks (ANNs) models. Following the results, SVM-WAVELET algorithm is helpful in order to enhance the accuracy compared to GP and ANN. It was conclusively observed that application of SVM-WAVELET is especially promising as an alternative approach to estimate the SPRBCCs moment and rotation.

Analysis of the failure mechanism and support technology for the Dongtan deep coal roadway

  • Chen, Miao;Yang, Sheng-Qi;Zhang, Yuan-Chao;Zang, Chuan-Wei
    • Geomechanics and Engineering
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    • v.11 no.3
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    • pp.401-420
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    • 2016
  • The stability of deep coal roadways with large sections and thick top coal is a typical challenge in many coal mines in China. The innovative Universal Discrete Element Code (UDEC) trigon block is adopted to create a numerical model based on a case study at the Dongtan coal mine in China to better understand the failure mechanism and stability control mechanism of this kind of roadway. The failure process of an unsupported roadway is simulated, and the results suggest that the deformation of the roof is more serious than that of the sides and floor, especially in the center of the roof. The radial stress that is released is more intense than the tangential stress, while a large zone of relaxation appears around the roadway. The failure process begins from partial failure at roadway corners, and then propagates deeper into the roof and sides, finally resulting in large deformation in the roadway. A combined support system is proposed to support roadways based on an analysis of the simulation results. The numerical simulation and field monitoring suggest that the availability of this support method is feasible both in theory and practice, which can provide helpful references for research on the failure mechanisms and scientific support designing of engineering in deep coal mines.

Dynamic Response and Vibration Characteristics of an Isolation Rail Track under a Traveling Mass (주행질량하의 방진 궤도레일의 동적응답 및 진동특성)

  • Oh, B.J.;Ryu, B.J.;Kim, J.H.;Lee, Y.S.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.4
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    • pp.365-373
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    • 2011
  • This paper presents the dynamic response and the vibration characteristics for a rail-track supported by discrete springs and dampers. Recently, automatic conveyer system, rail-track, rack-master system demand the soundproof facilities and vibration suppression measures in order to satisfy the strict environmental standards. The equations of motions of the dynamic characteristics for a vibration suppression rail-track under a traveling mass were derived by Galerkin's mode summation method considering gravity, centrifugal force, Coriolis force, inertia force of the moving mass, transverse inertia of the rail-track. Also, numerical results were calculated by Runge-Kutta integration method. In order to investigate vibration characteristics and dynamic responses, modal testing and measurement of the responses of the rail-track were performed. Through the experiment and numerical simulations, numerical results have a good agreement with experimental ones.

A Method of Analyzing ECG to Diagnose Heart Abnormality utilizing SVM and DWT

  • Shdefat, Ahmed;Joo, Moonil;Kim, Heecheol
    • Journal of Multimedia Information System
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    • v.3 no.2
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    • pp.35-42
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    • 2016
  • Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.