• Title/Summary/Keyword: Large-scale optimization

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Improved Large-Scale Refolding Techniques for Inclusion Body Proteins (내포체 단백질의 개선된 대규모 재접힘 기술)

  • 김인호;정봉현
    • KSBB Journal
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    • v.16 no.1
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    • pp.11-14
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    • 2001
  • Techniques for protein refolding from inclusion body are discussed in view of its engineering application to large scale protein purification. Among the techniques, dilution and dialysis are mainly utilized due to simple operation. Membrane reactor, gel filtration chromatography, and continuous tank operation are emerging tools for their process-scale possibility in refolding. Reaction engineering approaches could be used to analyze the kinetic behaviour in the process scale refolding reactor. The kinetic analysis is helpful in the optimization of refolding yield in the refolding reactor.

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An implementation of network optimaization system using GIS (GIS를 이용한 네트워트 최적화 시스템 구축)

  • 박찬규;이상욱;박순달;성기석;진희채
    • Korean Management Science Review
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    • v.17 no.1
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    • pp.55-64
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    • 2000
  • By managing not only geographical information but also various kinds of attribute data. GIS presents useful information for decision-makings. Most of decision-making problems using GIS can be formulated into network-optimization problems. In this study we deal with the implementation of network optimization system that extracts data from the database in GIS. solves a network optimization problem and present optimal solutions through GIS' graphical user interface. We design a nitwork optimization system and present some implementation techniques by showing a prototype of the network optimization system. Our network optimization system consists of three components : the interface module for user and GIS the basic network the program module the advanced network optimization program module. To handle large-scale networks the program module including various techniques for large sparse networks is also considered, For the implementation of the network optimization system we consider two approaches : the method using script languages supported by GIS and the method using client tools of GIS. Finally some execution results displayed by the prototype version of network optimization system are given.

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Parallelized Topology Design Optimization of the Frame of Human Powered Vessel (인력선 프레임의 병렬화 위상 최적설계)

  • Kim, Hyun-Suk;Lee, Ki-Myung;Kim, Min-Geun;Cho, Seon-Ho
    • Journal of the Society of Naval Architects of Korea
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    • v.47 no.1
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    • pp.58-66
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    • 2010
  • Topology design optimization is a method to determine the optimal distribution of material that yields the minimal compliance of structures, satisfying the constraint of allowable material volume. The method is easy to implement and widely used so that it becomes a powerful design tool in various disciplines. In this paper, a large-scale topology design optimization method is developed using the efficient adjoint sensitivity and optimality criteria methods. Parallel computing technique is required for the efficient topology optimization as well as the precise analysis of large-scale problems. Parallelized finite element analysis consists of the domain decomposition and the boundary communication. The preconditioned conjugate gradient method is employed for the analysis of decomposed sub-domains. The developed parallel computing method in topology optimization is utilized to determine the optimal structural layout of human powered vessel.

Emergency Service Restoration and Load Balancing in Distribution Networks Using Feeder Loadings Balance Index (피더부하 균등화지수를 이용한 배전계통의 긴급정전복구 및 부하균등화)

  • Choe, Sang-Yeol;Jeong, Ho-Seong;Sin, Myeong-Cheol
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.5
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    • pp.217-224
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    • 2002
  • This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

A Magnet Pole Shape Optimization of a Large Scale BLDC Motor Using a RSM With Design Sensitivity Analysis (민감도기법과 RSM을 이용한 대용량 BLDC 전동기 영구자석의 형상 최적화)

  • Shin, Pan-Seok;Chung, Hyun-Koo;Woo, Sung-Hyun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.735-741
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    • 2009
  • This paper presents an algorithm for the permanent magnet shape optimization of a large scale BLDC(Brushless DC) motor to minimize the cogging torque. A response surface method (RSM) using multiquadric radial basis function is employed to interpolate the objective function in design parameter space. In order to get a reasonable response surface with relatively small number of sampling data points, additional sampling points are added on the basis of design sensitivity analysis computed by using FEM. The algorithm has 2 stages: the first stage is to determine the PM arc angle, and the 2nd stage is to optimize the magnet pole shape. The developed algorithm is applied to a 5MW BLDC motor to get a minimum cogging torque. After 3 iterations with 4 design parameters, the cogging torque is reduced to 13.2% of the initial one.

A FRAMEWORK FOR QUERY PROCESSING OVER HETEROGENEOUS LARGE SCALE SENSOR NETWORKS

  • Lee, Chung-Ho;Kim, Min-Soo;Lee, Yong-Joon
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.101-104
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    • 2007
  • Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

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River Pollution Control Using Hierarchical Optimization Technique (계층적 최적화 기법을 이용한 강의 수질오염 제어)

  • 김경연;감상규
    • Journal of Environmental Science International
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    • v.4 no.1
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    • pp.71-80
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    • 1995
  • A discrete state space model for a multiple-reach river system is formulated using the dynamics of biochemical oxygen demand(BOD) and dissolved oxygen(DO). A hierarchical optimization technique, which is applicable to large-scale systems with time-delays in states, is also described to control stream quality in a river as an optimal manner based on the interaction prediction method. The steady state tracking error of the proposed method is determined analytically and a necessary and sufficient condition on which a constant target tracking problem has zero steady-state error is derived. Computer simulations for the river pollution model illustrate the algorithm.

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An Optimization Method using Evolutionary Computation in Large Scale Power Systems (진화연산을 이용한 대규모 전력계통의 최적화 방안)

  • You, Seok-Ku;Park, Chang-Joo;Kim, Kyu-Ho;Lee, Jae-Gyu
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.714-716
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    • 1996
  • This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.

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Query Optimization on Large Scale Nested Data with Service Tree and Frequent Trajectory

  • Wang, Li;Wang, Guodong
    • Journal of Information Processing Systems
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    • v.17 no.1
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    • pp.37-50
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    • 2021
  • Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

Large Scale Cooperative Coevolution Differential Evolution (대규모 협동진화 차등진화)

  • Shin, Seong-Yoon;Tan, Xujie;Shin, Kwang-Seong;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.665-666
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    • 2022
  • Differential evolution is an efficient algorithm for continuous optimization problems. However, applying differential evolution to solve large-scale optimization problems quickly degrades performance and exponentially increases runtime. To overcome this problem, a new cooperative coevolution differential evolution based on Spark (referred to as SparkDECC) is proposed. The divide-and-conquer strategy is used in SparkDECC.

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