• 전기의세계
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• v.30 no.6
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• pp.375-385
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• 1981

New algorithms are derived for nonlinear programming problems which are characterized by their large variables and equality and inequality constraints. The algorithms are based upon the introduction of the Dependent-Variable-Elimination method, Independent-Variable-Reduction method, Optimally-Ordered-Triangular-Factorization method, Equality-Inequality-Sequential-Satisfaction method, etc. For a case study problem relating to the optimal determination of load flow in a 10-bus, 13-line sample power system, several approaches are undertaken, such as SUMT, Lagrange's Multiplier method, sequential applications of linear and quadratic programming method. For applying the linear programming method, the conventional simplex algorithm is modified to the large-system-oriented one by the introduction of the Two-Phase method and Variable-Upper-Bounding method, thus resulting in remarkable savings in memory requirements and computing time. The case study shows the validity and effectivity of the algorithms presented herein.

• Applied Microscopy
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• v.46 no.4
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• pp.171-175
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• 2016

A distinctive neuronal network in the brain is believed to make us unique individuals. Electron microscopy is a valuable tool for examining ultrastructural characteristics of neurons, synapses, and subcellular organelles. A recent technological breakthrough in volume electron microscopy allows large-scale circuit reconstruction of the nervous system with unprecedented detail. Serial-section electron microscopy-previously the domain of specialists-became automated with the advent of innovative systems such as the focused ion beam and serial block-face scanning electron microscopes and the automated tape-collecting ultramicrotome. Further advances in microscopic design and instrumentation are also available, which allow the reconstruction of unprecedentedly large volumes of brain tissue at high speed. The recent introduction of correlative light and electron microscopy will help to identify specific neural circuits associated with behavioral characteristics and revolutionize our understanding of how the brain works.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.143-151
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• 2005

This paper considers a robust decentralized $H_\infty$ control problem for uncertain large-scale interconnected systems. The uncertainties are assumed to be time-invariant, norm-bounded, and exist in subsystems. A design method based on the bounded real lemma is developed for a dynamic output feedback controller, which is reduced to a feasibility problem for a nonlinear matrix inequality (NMI). It is proposed to solve the NMI iteratively by the idea of homotopy, where some of the variables are fixed alternately on each iteration to reduce the NMI to a linear matrix inequality (LMI). A decentralized controller for the nominal system is computed first by imposing structural constraints on the coefficient matrices gradually. Then, the decentralized controller is modified again gradually to cope with the uncertainties. A given example shows the efficiency of this method.

• Smart Structures and Systems
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• v.11 no.5
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• pp.511-531
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• 2013

Recent advances in low-cost remote monitoring systems have made it possible and practical to perform structural health monitoring (SHM) on a large scale. However, it is difficult for a single remote monitoring system to cover a wide range of SHM applications due to the amount of specialization required. For the remote monitoring system to be flexible, sustainable, and robust, this article introduces a new cost-effective, advanced remote monitoring and inspection system named DuraMote that can serve as a next generation supervisory control and data acquisition (SCADA) system for civil infrastructure systems. To evaluate the performance of DuraMote, we conduct experiments at two representative counterpart sites: a bridge and water pipelines. The objectives of this article are to improve upon the existing SCADA by integrating the remote monitoring system (i.e., DuraMote), to describe a prototype SCADA for civil engineering structures, and to validate its effectiveness with long-term field deployment results.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.99-102
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• 2008

In terms of operation profiles and building characteristics, Schools, as public facilities, are one of the most suitable buildings for small scale Renewable energy systems since they have its energy demand on daytime mostly and large open area, roof surface available for the installation of Renewable energy systems such as solar collectors or Photovoltaic pannels. This paper presents a methodology of the feasibility test for Renewable energy systems to be intalled at schools. The methodology is based on the analysis of the demand/supply profiles dynamic matching. a case study is also presented to test the applicability of the proposed assessment methodology.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.108-114
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• 2001

Petri nets have been introduced as a powerful analyzing and design tool for the discrete systems such as sequential control systems. However, one of the important problems in its applications is that the model can be analyzed hardly when we deal with large scale systems because of increase of the number of Petri net components. To overcome this problem, some methods for dividing or reducing of Petri net have been suggested. In this paper, an approach for hierarchical expression of Petri net based on Sequential function Chart(SFC) and Bottom Up oriented Mehodology(BUM) is proposed. Especially, some definitions and rules are defined in order to divide and compose sub Petri nets. A measuring tank system will be described as a typical kind of discrete systems and modeled by some sub Petri nets based on the SFC and BUM by the proposed method in this paper.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.209-217
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• 2012

In the present, Wireless Sensor Network(WSN) has been used for the purpose of the military operation with surveillance systems and for collecting useful information from the natural environment. Basically, low-power, easy deployment and low cost are the most important factors to be deployed for WSNs. Lots of researches have been studied to meet those requirements, especially on the node capacity and battery lifetime improvements. Recently, the study of wireless mesh networks applied into the surveillance systems has been proceeded as a solution of easy deployment. In this paper, we proposed large-scale intelligent multi-layer surveillance systems based on QoS assuring Wireless Mesh Networks and implemented them in the real testbed environment. The proposed system explains functions and operations for each subsystem as well as S/W and H/W architectures. Experimental results are shown for the implemented subsystems and the performance is satisfactory for the surveillance system. We can identify the possibility of the implemented multi-layer surveillance system to be used in practice.

• Asia pacific journal of information systems
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• v.2 no.1
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• pp.57-76
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• 1992

Material Requirement Planning(MRP) has been the most widely implemented large scale production management system in the manufacturing industry. Computerization of MRP systems involves, in general, Bill Of Material(BOM) explosion algolithms which usually takes heavy computation time. In order to improve the effectiveness of the MRP systems, we propose to build a logical BOM database in advance, which reflects the Join operations for the BOM explosion. It reduces the response time for the BOM indented explosion. It reduces the MRP processing time. It also increased main memory utilization.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1066-1070
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• 1990

This paper presents a method for the optimal control of the distributed parameter systems (DPSs) by a hierarehical computational procedure. Approximate lumped parameter systems (LPSs) are derived by using the Galerkin method employing the Legendre polynomials as the basis functions. The DPSs however, are transformed into the large scale LPSs. And thus, the hierarchical control scheme is introduced to determine the optimal control inputs for the obtained LPSs. In addition, an approach to block pulse functions is applied to solve the optimal control problems of the obtained LPSs. The proposed method is simple and efficient in computation for the optimal control of DPSs.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1075-1085
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• 1990

This paper presents a new method for the optimal control of the distributed parameter systems by a decentralized computational procedure. Approximate lumped parameter models are derived by using the Galerkin method employing the Legendre polynomials as the basis functions. The distributed parameter systems, however, are transformed into the large scale lumped parameter models. And thus, the decentralized control scheme is introduced to determine the optimal control inputs for the obtained lumped parameter models. In addition, an approach to block pulse functions is applied to solve the optimal control problems of the obtained lumped parameter models. The proposed method is simple and efficient in computation for the optimal control of distributed paramter systems. Illustrative examples given to demonstrate the validity of the presently proposed method.