• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.335-341
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• 2007

In this study, we present an approach to parallelizing OPF that is suitable for distributed implementation and is applicable to very large inter-connected power systems. The approach could be used by utilities for optimal economy interchange without disclosing details of their operating costs to competitors. It could also be used to solve several other computational tasks, such as state estimation and power flow, in a distributed manner. The proposed algorithm was demonstrated with several case study systems.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.412-415
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• 2005

The recent requirement for faster and more frequent solutions has encouraged the consideration of parallel implementations using decentralized processors. Distributed multi-processor environments can potentially greatly increase the available computational capacity and decrease the communication burden, allowing for faster Optimal Power Flow (OPF) solutions. This paper presents a mathematical approach to implementing distributed OPF using the alternating direction method (ADM) to parallelize the OPF. Several IEEE Reliability Test Systems were adopted to demonstrate the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1258-1261
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• 1993

This paper presents a methodology of path planning and navigation for an autonomous mobile robot. A fast algorithm using decomposition technique, which computes the optimal paths between all pairs of nodes, is proposed for real-time calculation. The robot is controlled by fuzzy approximation reasoning. Our new methodology has been implemented on a mobile robot. The results show that the robot successfully navigates to its destination following the optimal path.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.237-246
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• 2014

Researches on the elimination of sulfur and nitrogen oxides with catalysts and absorbents reported many problems related with elimination efficiency and complex devices. In this study, decomposition efficiency of harmful gases was investigated. It was found that the efficiency rate can be increased by moving the harmful gases together with SPCP reactor and the catalysis reactor. Calcium hydroxide($Ca(OH)_2$), CaO, and $TiO_2$ were used as catalysts. Harmful air polluting gases such as $SO_2$ were measured for the analysis of decomposition efficiency, power consumption, and voltage according to changes to the process variables including frequency, concentration, electrode material, thickness of electrode, number of electrode winding, and additives to obtain optimal process conditions and the highest decomposition efficiency. The standard sample was sulfur oxide($SO_2$). Harmful gases were eliminated by moving them through the plasma generated in the SPCP reactor and the $Ca(OH)_2$ catalysis reactor. The elimination rate and products were analyzed with the gas analyzer (Ecom-AC,Germany), FT-IR(Nicolet, Magna-IR560), and GC-(Shimazu). The results of the experiment conducted to decompose and eliminate the harmful gas $SO_2$ with the $Ca(OH)_2$ catalysis reactor and SPCP reactor show 96% decomposition efficiency at the frequency of 10 kHz. The conductivity of the standard gas increased at the frequencies higher than 20 kHz. There was a partial flow of current along the surface. As a result, the decomposition efficiency decreased. The decomposition efficiency of harmful gas $SO_2$ by the $Ca(OH)_2$ catalysis reactor and SPCP reactor was 96.0% under 300 ppm concentration, 10 kHz frequency, and decomposition power of 20 W. It was 4% higher than the application of the SPCP reactor alone. The highest decomposition efficiency, 98.0% was achieved at the concentration of 100 ppm.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.98-101
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• 1988

A non load level decomposition algorithm is presented for power system reactive source planning. The fuel cost is introduced to performance index in optimal operation problem. The investment variables are all reactive sources such as capacitance or inductance. Experiment showed a desirable result and the computation time reduced considerably.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.795-801
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• 2011

In machine learning and statistics it is often the case that some variables are not important, while some variables are more important than others. We propose a novel algorithm for selecting such relevant variables in the kernel Cox regression. We employ the weighted version of ANOVA decomposition kernels to choose optimal subset of relevant variables in the kernel Cox regression. Experimental results are then presented which indicate the performance of the proposed method.

• The Pure and Applied Mathematics
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• v.2 no.2
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• pp.133-140
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• 1995

The D-optimal design criterion for precise parameter estimation in nonlinear regression analysis is called the determinant criterion because the determinant of a matrix is to be maximized. In this thesis, we derive the gradient and the Hessian of the determinant criterion, and apply a QR decomposition for their efficient computations. We also propose an approximate form of the Hessian matrix which can be calculated from the first derivative of a model function with respect to the design variables. These equations can be used in a Gauss-Newton type iteration procedure.

• ETRI Journal
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• v.38 no.4
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• pp.746-756
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• 2016

Owing to the intermittent power generation of renewable energy sources (RESs), future wireless cellular networks are required to reliably aggregate power from retailers. In this paper, we propose a distributed power allocation (DPA) scheme for base stations (BSs) powered by retailers with heterogeneous RESs in order to deal with the unreliable power supply (UPS) problem. The goal of the proposed DPA scheme is to maximize our well-defined utility, which consists of power satisfaction and unit power costs including added costs as a non-subscriber, based on linear and quadratic cost models. To determine the optimal amount of DPA, we apply dual decomposition, which separates the master problem into sub-problems. Optimal power allocation from each retailer can be obtained by iteratively coordinating between the BSs and retailers. Finally, through a mathematical analysis, we show that the proposed DPA can overcome the UPS for BSs powered from heterogeneous RESs.

• Journal of Korean Association for Spatial Structures
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• v.13 no.1
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• pp.59-67
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• 2013

This paper presents a new numerical method to analyse tensegrity structures by using singular value decomposition and force method. The tensegrity system consisting of compressive and tensle elements are pin-jointed system. Tensegrity structures, unlike the general structure should be preceded by form-finding. Tensegrity structures form-finding of the self-equilibrium stress stability, seeking to have the process. In this study, tensegrity structures when subjected to external loads, find the optimal pre-stress values was studied.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.9-11
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• 2010

Multiple-input multiple-output (MIMO) systems assisted by multi-relays with single antenna are considered. Signal transmission consists of two hops. In the first hop, the source node broadcasts the vector symbols to all relays, then all relays forward the received signals multiplied by each power gain to the destination simultaneously. Unlike the case of full cooperation between relays such as single relay with multiple antennas, in our case there is no closed form solution for optimal relay power gain with respect to minimum mean square error (MMSE). Thus we propose an alternative approach in which we use an approximation of the cost function based on rank-one matrix decomposition. As a cost function, we choose the trace of MSE matrix. We give several simulation results to validate that our proposed method obtains a negligible performance loss compared to optimal solution obtained by exhaustive search.