• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.669-678
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• 2009

Real-time image georeferencing technologies are required to generate spatial information promptly from the image sequences acquired by a multi-sensor system. We thus derive a sequential adjustment algorithm based on the combined adjustment model. By adopting the sequential adjustment model, we develop a sequential AT(Aerial Triangulation) algorithm to georeference image sequences in real-time. The proposed algorithm enables to perform AT rapidly with the minimum computation at the current stage by using the results computed at the previous stage whenever a new image is added. Experiments with simulated data were conducted to verify the effectiveness of the proposed algorithm. The results of the experiments show that the georeferencing of each image took very short time and its accuracy was determined within ${\pm}4cm$ on the ground control points comparing to the results of the existing simultaneous AT.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.5
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• pp.380-388
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• 2002

This paper describes the optimum design for low-pressure steam turbine rotor of 1,000 MW nuclear power plant by using a combined genetic algorithm, which uses both a genetic algorithm and a local concentrate search algorithm (e.g. simplex method). This algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The objective is to minimize the resonance response (Q factor) and total weight of the shaft, and to separate the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables. The results show that the proposed algorithm can improve the Q factor and reduce the weight of the shaft and the 1st critical speed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.76-82
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• 2001

This paper presents a approach for a service restoration and optimal reconfiguration of distribution network using Genetic algorithm(GA) and Tabu search(TS) method. Restoration and reconfiguration problems in distribution network are difficult to solve in short times, because distribution network supplies power for customers combined with many tie-line switches and sectionalizing switches. Furthermore, the solutions of these problems have to satisfy radial operation conditions and reliability indices. To overcome these time consuming and sub-optimal problem characteristics, this paper applied Genetic-Tabu algorithm. The Genetic-Tabu algorithm is a Tabu search combined with Genetic algorithm to complement the weak points of each algorithm. The case studies with 7 bus distribution network showed that not the loss reduction but also the reliability cost should be considered to achieve the economic service restoration and reconfiguration in the distribution network. The results of suggested Genetic-Tabu algorithm and simple Genetic algorithm are compared in the case study also.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.585-591
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• 2013

Recently, the combined attack which is a combination of side channel analysis and fault attack has been developed to extract the secret key during the cryptographic processes using a security device. Unfortunately, an attacker can find the private key of RSA cryptosystem through one time fault injection and power signal analysis. In this paper, we diagnosed SPA/FA resistant BNP(Boscher, Naciri, and Prouff) exponentiation algorithm as having threats to a similar combined attack. And we proposed a simple countermeasure to resist against this combined attack by randomizing the private key using error infective method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1455-1464
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• 1994

A new and efficient algorithm for the integration of the thermal-elasto-plastic constitutive equation is proposed. While it falls into the category of the return mapping method, the algorithm adopts the three point approximation of plastic corrector within one time increment step. The results of its application to a von Mises-type thermal-elasto-plastic model with combined hardening and temperature-dependent material properties show that the accurate iso-error maps are obtained for both angular and radial errors. The accuracy achieved is because the predicted stress increment in a single step calculation follows the exact value closely not only at the end of the step but also through the whole path. Also, the comparison of the computational time for the new and other algorithms shows that the new one is very efficient.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.204-211
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• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.79-87
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• 2023

In this paper, we propose a novel genetic algorithm to reduce the overall span time by optimizing the skid insertion sequence in the shipyard subassembly process. We represented a solution by a permutation of a set of skid ids and applied genetic operators suitable for such a representation. In addition, we combined the genetic algorithm and the existing heuristic algorithm called UniDev which is properly modified to improve the search performance. In particular, the slow skid search part in UniDev was changed to a greedy algorithm. Through extensive large-scaled simulations, it was observed that the span time of our method was stably minimized compared to Multi-Start search and a genetic algorithm combined with UniDev.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.36-47
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• 2020

The improved belief-propagation-based algorithms, such as normalized min-sum algorithm (NMSA) or offset min-sum algorithm (OMSA), are widely used to decode LDPC(Low-Density Parity-Check) codes because they are less computationally complex and work well even at low SNR(Signal-to-Noise Ratio). However, these algorithms work well only when an appropriate normalization factor or offset value is used. A new method that uses a CMD(Check Node Message Distribution) chart and least-square method, which has been recently proposed, has advantages on computational complexity over other approaches to get optimal coefficients. Furthermore, this method can be used to derive coefficients for each iteration. In this paper, we apply this method and propose an algorithm to derive a combination of normalization factor and offset value for a combined normalized and offset min-sum algorithm to further improve the decoding of LDPC codes. Simulations on the next-generation broadcasting standards, ATSC 3.0 LDPC codes, prove that a combined normalized and offset min-sum algorithm which takes the proposed coefficients as correction coefficients shows the best BER performance among other decoding algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.2
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• pp.61-70
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• 2012

Recently due to the increasing of the importance on the green energy is getting higher by implementing EERS(Energy Efficiency Resource Standards) and NA(Negotiated Agreement) such as lacks of natural resources and The United Nations Framework Convention on Climate Change. And the most practical solution is CHP(Combined Heat and Power) which performs the best energy efficiency. This paper developed optimal operation mechanism of CES(Community Energy System) for enhancement of energy efficiency using CHP(Combined Heat and Power), PLB(Peak Load Boiler) and ACC(ACCumulator) capacities. This method optimally operated these capacities calculated the maximum profits by Dynamic Programing. Through the case studies, it is verified that the proposed algorithm of can evaluate availability.