• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1089-1103
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• 2000

A Problem of relevant interest to some industries is that of obtaining optimum two-dimensional layout. To solve this provlem, one is given a number of rectangular sheets and an order for a specified number of each of certain types of two-dimensional regular and irregular shapes. The aim is to cut the the shapes out of the sheets in such a way as to minimize the amount of waste produced. A DCS (Distributed Control System) is an integrated system which applies the decentralization concept to a control system handling both sequential and analog control. A DCS performs many operations such as data gathering, data processing, data storing and monitoring the operatin conditions for the operator. IN this paper, we propose a genetic algorithm based on rotation parameters from which the best pattern of layout is found as well as a layout method for better performance time. A DCS for the plate cutting process system, which is performed by a virtual system, is also identified.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.1-10
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• 2000

With every passing month a number of new virtual enterprises emerge on the internet. Many companies have responded to the idea of distributed manufacturing in which the value adding activities comprising a finished product are dispersed geographically in a remote place. This study suggests an idea for selecting suppliers in a distributed manufacturing environment which enables machining companies to share their capacities. A mathematical model is constructed to show how to minimize the sum of the operation and transportation costs based on alternative process plans considering several kinds of operation characteristics in the real world. Four heuristic algorithms are developed to get an optimal or near-optimal solution using tabu search since the model is proven NP-hard. Example problems are tested to illustrate their procedure and performance.

• 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).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1284-1286
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• 2003

There is a growing demand on remotely sensed and GIS data services in modern society. However, conventional WEB applications based on client/server pattern can not meet the criteria in the future . Grid computing provides a promising resolution for establishing spatial information system toward future applications. Here, a new architecture of the distributed environment for remotely sensed data processing based on the middleware technology was proposed. In addition, in order to utilize the new environment, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. Experiment of the algorithm was implemented, and the results show that the new environmental can achieve high speedups for applications compared with conventional implementation.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.176-187
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• 2002

This paper focuses on the study of simulation and evolution of Micro Air Vehicles. Micro Air Vehicles or MAVs are small flying robots that are used for surveillance, search and rescue, and other missions. The simulated robots are designed based on realistic characteristics and the brains (controllers) of the robots are generated using genetic algorithms, i .e., simulated evolution. The objective for the experiments is to investigate the effects of robot team size and topology (simulation environment) on the evolution of simulated robots. The testing of team sizes deals with finding an ideal number of robots to be deployed for a given mission. The goal of the topology experiments is to see if there is an ideal topology (environment) to evolve the robots in order to increase their utility in most environments. We compare the results of the various experiments by evaluating the fitness values of the robots i .e., performance measure. In addition, evolved robot teams are tested in different situation in order to determine if the results can be generalized, and statistical analysis is performed to evaluate the evolved results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1207-1215
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.164-175
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• 2017

Dual response surface optimization (DRSO) attempts to optimize mean and variability of a process response variable using a response surface methodology. In general, mean and variability of the response variable are often in conflict. In such a case, the process engineer need to understand the tradeoffs between the mean and variability in order to obtain a satisfactory solution. Recently, a Posterior preference articulation approach to DRSO (P-DRSO) has been proposed. P-DRSO generates a number of non-dominated solutions and allows the process engineer to select the most preferred solution. By observing the non-dominated solutions, the DM can explore and better understand the trade-offs between the mean and variability. However, the non-dominated solutions generated by the existing P-DRSO is often incomprehensive and unevenly distributed which limits the practicability of the method. In this regard, we propose a modified P-DRSO using multiple objective genetic algorithms. The proposed method has an advantage in that it generates comprehensive and evenly distributed non-dominated solutions.

• ETRI Journal
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• v.34 no.3
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• pp.330-340
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• 2012

In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules, and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms, namely, the max-min, min-min, and opportunistic load balancing algorithms, is used.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.491-502
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• 2014

In this paper we present some research results on computing intensive applications using modern high performance architectures and from the perspective of high computational needs. Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there are applications based on simulations, aiming to maximize system resources for processing large computations for simulation. In this research work, we consider an application that simulates scheduling and resource allocation in a Grid computing system using Genetic Algorithms. In such application, a rather large number of simulations is needed to extract meaningful statistical results about the behavior of the simulation results. We study the performance of Oracle Grid Engine for such application running in a Cluster of high computing capacities. Several scenarios were generated to measure the response time and queuing time under different workloads and number of nodes in the cluster.