• Title/Summary/Keyword: Sequential system

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Cooperative Spectrum Sensing Via Sequential Detection: A Method to Reduce the Sensing Time

  • Thanh, Truc Tran;Kong, Hyung-Yun
    • Journal of electromagnetic engineering and science
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    • v.12 no.3
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    • pp.196-202
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    • 2012
  • Spectrum sensing is one of the most important functions in cognitive radio systems. In this paper, we focus on reducing the sensing time in a cooperative spectrum sensing paradigm. In the proposed scheme, a sequential detection technique is employed to provide a robust and quick detection system. Each of the secondary users measures the log-likelihood probability of the received signals and then sequentially reports to the base station. Here, the maximum ratio combining (MRC) technique is employed to reduce the average sample number (ASN) in order to reduce the sensing time. This proposed scheme is analyzed and simulated to illustrate the performance in comparison with the other given methods. Analysis and simulation are provided to validate the proposed method.

Development of an Evaluation Technique for Incentive Level of Direct Load Control using Sequential Monte Carlo Simulation (몬테카를로 시뮬레이션을 이용한 직접부하제어의 적정 제어지원금 산정기법 개발)

  • Jeong, Yun-Won;Kim, Min-Soo;Park, Jong-Bae;Shin, Joong-Rin;Kim, Byung-Seop
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.636-638
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    • 2003
  • This paper presents a new approach which is able to determine the reasonable incentive levels of direct load control using sequential Monte Carlo simulation techniques. The economic analysis needs to determine the reasonable incentive level. However, the conventional methods have been based on the scenario methods because they had not considered all cases of the direct load control situations. To overcome there problems, this paper proposes a new technique using sequential Monte Carlo simulation. The Monte Carlo method is a simple and flexible tool to consider large scale systems and complex models for the components of the system. To show its effectiveness, numerical studies were performed to indicate the possible applications of the proposed technique.

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On The Development of the Color Sequential LCD

  • Liu, Chia-Lin;Okita, Masaya;Huang, Chi-Fang;Mo, Chi-Neng;Tai, Wen-Chih;Chen, Kuang-Lang
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1172-1174
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    • 2009
  • Color sequential display is a well know technology. Hower, due to the slow response time of LC,the CSD has not been used in LCD. We have developed a unique LC color display, which can improve LC response time, improve the driving system, improve the gamma drive issue and increase the color gamut to more than NTSC120%.It also can get very low power consumption merit.

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Anaerobic-aerobic granular system for high-strength wastewater treatment in lagoons

  • Hamza, Rania A.;Iorhemen, Oliver T.;Tay, Joo H.
    • Advances in environmental research
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    • v.5 no.3
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    • pp.169-178
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    • 2016
  • This study aimed at determining the treatability of high-strength wastewater (chemical oxygen demand, COD>4000 mg/L) using combined anaerobic-aerobic granular sludge in lagoon systems. The lagoon systems were simulated in laboratory-scale aerated and non-aerated batch processes inoculated with dried granular microorganisms at a dose of 0.4 g/L. In the anaerobic batch, a removal efficiency of 25% was not attained until the 12th day. It took 14 days of aerobic operation to achieve sCOD removal efficiency of 94% at COD:N:P of 100:4:1. The best removal efficiency of sCOD (96%) was achieved in the sequential anaerobic-aerobic batch of 12 days and 2 days, respectively at COD:N:P ratio of 200:4:1. Sequential anaerobic-aerobic treatment can achieve efficient and cost effective treatment for high-strength wastewater in lagoon systems.

An Algorithm for Sequential Sampling Method in Data Mining (데이터 마이닝에서 샘플링 기법을 이용한 연속패턴 알고리듬)

  • 홍지명;김낙현;김성집
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.45
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    • pp.101-112
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    • 1998
  • Data mining, which is also referred to as knowledge discovery in database, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information (such as knowledge rules, constraints, regularities) from data in databases. The discovered knowledge can be applied to information management, decision making, and many other applications. In this paper, a new data mining problem, discovering sequential patterns, is proposed which is to find all sequential patterns using sampling method. Recognizing that the quantity of database is growing exponentially and transaction database is frequently updated, sampling method is a fast algorithm reducing time and cost while extracting the trend of customer behavior. This method analyzes the fraction of database but can in general lead to results of a very high degree of accuracy. The relaxation factor, as well as the sample size, can be properly adjusted so as to improve the result accuracy while minimizing the corresponding execution time. The superiority of the proposed algorithm will be shown through analyzing accuracy and efficiency by comparing with Apriori All algorithm.

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An Algorithm to Reduce the Number of Nodes in Active Spectrum Sensing Via Cooperative Sequential Detection

  • Truc, Tran Thanh;Kong, Hyung-Yun
    • Journal of electromagnetic engineering and science
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    • v.12 no.2
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    • pp.148-154
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    • 2012
  • In this paper, we propose an algorithm to conserve resources of the common control channel in a cognitive radio network by rejecting the redundant users using cooperative spectrum sensing. The proposed scheme is investigated under the paradigm of active spectrum sensing and a sequential detection technique. The algorithm is based on the J-divergence between the hypotheses of non primary user operation and the otherwise case. We select the most significant eigenvalues, which primarily affect the global statistical test. For the case where interference is from a secondary system transmission, a match filter is first employed to remove the degradation, and then the proposed algorithm is employed to remove the cooperative sensing nodes. Numerical results are provided and compared with conventional cases in order to validate the performance of the proposed algorithm.

A Sequential Approximate Optimization Technique Using the Previous Response Values (응답량 재사용을 통한 순차 근사최적설계)

  • Hwang Tae-Kyung;Choi Eun-Ho;Lim O-Kaung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.1 s.232
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    • pp.45-52
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    • 2005
  • A general approximate optimization technique by sequential design domain(SDD) did not save response values for getting an approximate function in each step. It has a disadvantage at aspect of an expense. In this paper, previous response values are recycled for constructing an approximate function. For this reason, approximation function is more accurate. Accordingly, even if we did not determine move limit, a system is converged to the optimal design. Size and shape optimization using approximate optimization technique is carried out with SDD. Algorithm executing Pro/Engineer and ANSYS are automatically adopted in the approximate optimization program by SDD. Convergence criterion is defined such that optimal point must be located within SDD during the three steps. The PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information in the direction finding problem and uses the active set strategy.

Product Recommendation System on VLDB using k-means Clustering and Sequential Pattern Technique (k-means 클러스터링과 순차 패턴 기법을 이용한 VLDB 기반의 상품 추천시스템)

  • Shim, Jang-Sup;Woo, Seon-Mi;Lee, Dong-Ha;Kim, Yong-Sung;Chung, Soon-Key
    • The KIPS Transactions:PartD
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    • v.13D no.7 s.110
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    • pp.1027-1038
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    • 2006
  • There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

Parameter identification for nonlinear behavior of RC bridge piers using sequential modified extended Kalman filter

  • Lee, Kyoung Jae;Yun, Chung Bang
    • Smart Structures and Systems
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    • v.4 no.3
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    • pp.319-342
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    • 2008
  • Identification of the nonlinear hysteretic behavior of a reinforced concrete (RC) bridge pier subjected to earthquake loads is carried out based on acceleration measurements of the earthquake motion and bridge responses. The modified Takeda model is used to describe the hysteretic behavior of the RC pier with a small number of parameters, in which the nonlinear behavior is described in logical forms rather than analytical expressions. Hence, the modified extended Kalman filter is employed to construct the state transition matrix using a finite difference scheme. The sequential modified extended Kalman filter algorithm is proposed to identify the unknown parameters and the state vector separately in two steps, so that the size of the problem for each identification procedure may be reduced and possible numerical problems may be avoided. Mode superposition with a modal sorting technique is also proposed to reduce the size of the identification problem for the nonlinear dynamic system with multi-degrees of freedom. Example analysis is carried out for a continuous bridge with a RC pier subjected to earthquake loads in the longitudinal and transverse directions.

Progressive Quadratic Approximation Method for Effective Constructing the Second-Order Response Surface Models in the Large Scaled System Design (대형 설계 시스템의 효율적 반응표면 근사화를 위한 점진적 이차 근사화 기법)

  • Hong, Gyeong-Jin;Kim, Min-Su;Choe, Dong-Hun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.12
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    • pp.3040-3052
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    • 2000
  • For effective construction of second-order response surface models, an efficient quad ratic approximation method is proposed in the context of trust region model management strategy. In the proposed method, although only the linear and quadratic terms are uniquely determined using 2n+1 design points, the two-factor interaction terms are mathematically updated by normalized quasi-Newton formula. In order to show the numerical performance of the proposed approximation method, a sequential approximate optimizer is developed and solves a typical unconstrained optimization problem having 2, 6, 10, 15, 30 and 50 design variables, a gear reducer system design problem and two dynamic response optimization problems with multiple objectives, five objectives for one and two objectives for the other. Finally, their optimization results are compared with those of the CCD or the 50% over-determined D-optimal design combined with the same trust region sequential approximate optimizer. These comparisons show that the proposed method gives more efficient than others.