• Title/Summary/Keyword: update strategy

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A Finite Element Formulation for the Inverse Estimation of an Isothermal Boundary in Two-Dimensional Slab (상단 등온조건을 갖는 이차원 슬랩에서의 경계위치 역추정을 위한 유한요소 정식화)

  • Kim, Sun-Kyoung;Hurh, Hoon;Lee, Woo-Il
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.25 no.6
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    • pp.829-836
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    • 2001
  • A dependable boundary reconstruction technique is proposed. The finite element method is used for the analysis of the direct heat conduction problem to realize the deformable grid system. An appropriate strategy for grid update is suggested. A complete sensitivity analysis is performed to obtain the derivatives required for restoration of the optimal boundary. With the result of the sensitivity analysis, the unknown boundary is sought using the sequential quadratic programming. The method is applied to reconstruction of boundaries with sinusoidal, step, and cavity form. The overall performance of the proposed method is examined by comparison between the estimated the exact boundaries.

EXTENDED ONLINE DIVISIVE AGGLOMERATIVE CLUSTERING

  • Musa, Ibrahim Musa Ishag;Lee, Dong-Gyu;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.406-409
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    • 2008
  • Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

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An algorithm for pattern recognition of multichannel ECG signals using AI (AI기법을 이용한 멀티채널 심전도신호의 패턴인식 알고리즘)

  • 신건수;이병채;황선철;이명호
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.575-579
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    • 1990
  • This paper describes an algorithm that can efficiently analyze the multichannel ECG signal using the frame. The input is a set of significant features (points) which have been extracted from an original sampled signal by using the split-and-merge algorithm. A signal from each channel can be hierarchical ADN/OR graph on the basis of the priori knowledge for ECG signal. The search mechanisms with some heuristics and the mixed paradigms of data-driven hypothesis formation are used as the major control mechanisms. The mutual relations among features are also considered by evaluating a score based on the relational spectrum. For recognition of morphologies corresponding to OR nodes, an hypothesis modification strategy is used. Other techniques such as instance, priority update of prototypes, and template matching facility are also used. This algorithm exactly recognized the primary points and supporting points from the multichannel ECG signals.

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A Profile-Based Binding Update Strategy in Mobile IPv6 (Mobile IPv6에서 프로파일 기반의 바인딩 갱신 전략)

  • 양순옥;송의성;남성헌;윤태명;황종선
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10c
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    • pp.286-288
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    • 2001
  • 미래에는 Mobile IP의 이동 노드 사용자가 증가할 것이기 때문에 보다 효율적인 이동성 관리 기법이 필요할 것이다. 특히 이동 노드의 수가 증가함에 따라 이동성을 지원하기 위한 바인딩 갱신 메시지 수는 증가한다. 따라서 , 본 논문에서는 이동 노드의 이동성 패턴의 지역적 특성이 반영된 프로파일 정보를 이용하여 네트워크 상에서 바인딩 갱신 메시지의 라이프타임 값을 조정함으로써 바인딩 갱신 메시지의 수를 감소시킬 수 있는 프로과일 기반의 전략을 제안한다. 본 논문에서는 이동 노드의 과거 이동성 패턴 정보를 이용하여 이동 노드가 가지고 있는 프로파일의 평균 상주시간 정보를 라이프타임 값으로 설정하는 적응적 라이프타임과 이동성 정보가 없는 경우에 기존 Mobile IPv6에서 사용하는 라이프타임 값을 그대로 사용하는 디폴트 라이프타임이 존재한다. 그리고, Mobile IPv6에서의 효율적인 라우팅을 위해 프로파일 정보에 기반한 두개의 라이프타임을 효율적으로 관리함으로써 바인딩 갱신 메시지와 바인딩 요청 메시지의 수를 감소시킬 수 있으며, 상당한 통신비용 절감효과를 기대할 수 있다.

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Incentive-Compatible Priority Pricing and Transfer Analysis in Database Services

  • Kim, Yong J.
    • The Journal of Information Technology and Database
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    • v.4 no.2
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    • pp.21-32
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    • 1998
  • A primary concern of physical database design has been efficient retrieval and update of a record because predictable performance of a DBMS is indispensable to time-critical missions. To maintain such phenomenal performance, database manages often spends more than or as much as the goal of an organization can warrant. The motivation of this research stems from the fact that even predictable performance of a physical database can be hampered by stochastic query processing time, physical configurations of a database, and random arrival processes of queries. They all together affect the overall performance of a DBMS. In particular, if there are queuing delays due to limited capacity or during on-peak congestion, this paper suggest to prioritize database services. A surprising finding of this paper is that such a transition from a non-priority system to a corresponding priority-based system can be Pareto-improving in the sense that no users in the system will be worse off after the transition. Thus prioritizing database services can be a viable option for efficient database management.

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PID Type Iterative Learning Control with Optimal Gains

  • Madady, Ali
    • International Journal of Control, Automation, and Systems
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    • v.6 no.2
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    • pp.194-203
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    • 2008
  • Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

A Comparative Analysis on Page Caching Strategies Affecting Energy Consumption in the NAND Flash Translation Layer (NAND 플래시 변환 계층에서 전력 소모에 영향을 미치는 페이지 캐싱 전략의 비교·분석)

  • Lee, Hyung-Bong;Chung, Tae-Yun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.13 no.3
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    • pp.109-116
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    • 2018
  • SSDs that are not allowed in-place update within the allocated page cause another allocation of a new page that will replace the previous page at the moment data modification occurs. This intrinsic characteristic of SSDs requires many changes to the existing HDD-based IO theory. In this paper, we conduct a performance comparison of FTL caching strategy in perspective of cache hashing (Global vs. grouped) and caching algorithm (LRU vs. NUR) through a simulation. Experimental results show that in terms of energy consumption for flash operation the grouped management of cache is not suitable and NUR algorithm is superior to LRU algorithm. In particular, we found that the cache hit ratio of LRU algorithm is about 10% point higher than that of NUR algorithm while the energy consumption of LRU algorithm is about 32% high.

A Study on the Application of S Model Automata for Multiple Objective Optimal Operation of Power Systems (다목적을 고려한 전력 시스템의 최적운용을 위한 S 모델 Automata의 적용 연구)

  • Lee, Byeong-Ha;Park, Jong-Geun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.4
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    • pp.185-194
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    • 2000
  • The learning automaton is an automaton to update systematically the strategy for enhancing the performance in response to the output results, and several schemes of learning automata have been presented. In this paper, S-model learning automata are applied in order to achieve the best compromise solution between an optimal solution for economic operation and an optimal solution for stable operation of the power system under the circumstance that the loads vary randomly. It is shown that learning automata are applied satisfactorily to the multiobjective optimization problem for obtaining the best tradeoff among the conflicting economy and stability objectives of power systems.

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A Database Approach for Modeling and Querying XML Documents

  • Panseop Shin;Kim, Jeong-Eun;Lee, Jaeho;Haechull Lim
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.703-706
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    • 2000
  • In recent years. XML applications are being developed in diverse area. Especially, development of XML document repository system associated with database is carrying out widely. The previous researches of XML repository system have several defects which are update and retrieval limitations for the XML document, design limitation for a formal retrieval algorithm and data redundancy. In order to solve the above problems. in this paper, we suggest relational database schemes for overcoming limitations of updating, retrieving, and rebuilding document. And suggest query translation strategy using two-phase translation that consists of pattern analyzing phase and SQL generating phase.

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Distributed Constrained Power Control with Non stationary Relaxation Factor in CDMA Cellular systems (CDMA 셀룰라 시스템에서 변동 경감 요소를 가지는 제한적 분산 전력제어)

  • Oh, Do-Chang;Lee, Moo-Young;Lee, Dong-Gi;Her, Yong-Do
    • Journal of Information Technology Applications and Management
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    • v.13 no.4
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    • pp.291-302
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    • 2006
  • The current paper proposes fast distributed constrained power control (FDCPC) with a non stationary relaxation factor as the next power update for CDMA cellular power control systems. A review is also given of unconstrained control algorithms: distributed power control (DPC), unconstrained second order power control (USOPC), and DPC with a stationary relaxation factor (DPCSRF) To improve the performance of outage probability convergence, DCPC with a non stationary relaxation factor (FDCPC) is proposed. Under constrained conditions, the convergence rate of FDCPC is shown to outperform that of DCPC and constrained second order power control(CSOPC).

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