• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.143-150
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• 2012

A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.1-9
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• 2010

In this paper, we propose a methodology in which a power-delay product of a binary adder is optimized based on the heterogeneous adder architecture. We formulate the power-delay product of the heterogeneous adder by using integer linear programming(ILP). For the use of ILP optimization, we adopt a transformation technique in which the initial non-linear expression for the power-delay product is converted into linear expression. The experimental result shows the superiority of the suggested method compared to the cases in which only conventional adder is used.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.27-34
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• 2023

This paper studied the 3D modeling process for the restoration of the 'Three-story Stone Pagoda of Bulguksa Temple in Gyeongju', a stone pagoda from the Unified Silla Period, using artificial intelligence (AI). Existing 3D modeling methods generate numerous verts and faces, which takes a considerable amount of time for AI learning. Accordingly, a method of performing more efficient 3D modeling by lowering the number of verts and faces is required. To this end, in this study, the structure of the stone pagoda was deeply analyzed and a modeling method optimized for AI learning was studied. In addition, it is meaningful to propose a new 3D modeling methodology for the restoration of stone pagodas in Korea and to secure a data set necessary for artificial intelligence learning.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.396-397
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• 2022

본 논문에서는 등기하 해석법을 이용하여 선형 탄성문제에 대한 형상 최적설계 기법을 개발하였다. 실용적인 공학문제에 대한 많은 최적설계 문제에서는 초기의 데이터가 CAD 모델로부터 주어지는 경우가 많다. 그러나 대부분의 설계 최적화 도구들은 유한요소법에 기초하고 있기 때문에 설계자는 이에 앞서 CAD 데이터를 유한요소 데이터로 변환해야 한다. 이 변환과정에서 기하 모델의 근사화에 따른 수치적 오류가 발생하게 되고, 이는 응답 해석뿐만 아니라 설계민감도 해석에 있어서도 정확도 문제를 발생시킨다. 이러한 점에서 등기하 해석법은 형상 최적설계에 있어서 유망한 방법론중 하나가 될 수 있다. 등기하 해석법의 핵심은 해석에 사용되는 기저 함수와 기하 모델을 구성하는 함수가 정확히 일치한다는 것이다. 이러한 기하학적으로 정확한 모델은 설계민감도 해석 및 형상 최적설계에 있어서도 사용된다. 이로 인해 높은 정확도의 설계민감도를 얻을 수 있으며, 이는 설계구배 기반의 최적화에 있어서 매우 중요하게 작용한다. 수치 예제를 통하여 본 논문에서 제시된 등기하 해석 기반의 형상 최적설계 방법론이 타당함을 확인하였다. 본 논문에는 등기하 해석법을 이용하여 선형 탄성문제에 대한 형상 최적설계 하였다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.8 no.2
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• pp.162-170
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• 1984

대부분의 동적댐퍼들은 주구조물의 진동진폭을 정해진 주파수 변위내에서 최대로 줄이는 것을 목 표로 한다. 그러나 공작기계의 안정성은 시편과 공구사이의 상대변위와 절삭력에 의해 결정되는 전달함수의 최대크기에 의해서보다는 실수부분의 최소치에 의해 결정된다는 것이 잘 알려져 있 다. 본 논문에서는 이 사실에 착안하여 공작기계에서 발생하는 채터를 흡수하기 위한 최적의 댐 퍼를 설계하는 절차를 제시하고 1 자유도로 대표될 수 있는 구조물의 경우에 대하여 구체적인 방 법을 예시하였다. 종래의 최적 댐퍼의 성질을 구하는 방법에 비해 수학적인 절차가 약간 복잡해 지기는 하나 전산기를 이용하여 큰 어려움이 없이 최적의 설계자료를 얻을 수 있다. 댐퍼 질량이 정해졌을 때 감쇠율과 스프링 계수를 변수로 하는 목표함수가 하나의 식으로 유도될 수 없기 때 문 에 간단한 최적화 방법으로 이변수 황금분할법을 사용하였다. 수치적인 예를 통하여 종래의 다른 방법에 의한 결과와 비교하고 제안된 방법론의 타당성을 입증하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.151-157
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• 2003

OLS로 알려진 기존의 주절 방법은 변수수의 증가에 따라 다중공선성(Multicollinearity)의 문제와 더불어 해석력(Interpretability)이 떨어지는 문제를 가지게 된다. 본 연구에서는 파라미터의 절대값의 크기(L1-Norm)에 제약을 줌으로써 이와 같은 OLS의 문제를 해결할 수 있는 동시에, 잔차의 제곱합대신 절대오차를 사용하는 Least Absolute Value(LAV) 방법을 사용함으로써 이상치에 로버스트한 결과를 주는 방법론을 제안한다. 또한. 본 연구에서 제안하는 방법이 선형계획법에 의해 모델처럼 될 수 있는 특성으로 인해 제약조건이 있는 이차 형태의 최적화 문제보다 수행 속도면에서 뛰어난 결과를 주는 것을 수치예제을 통해 보인다.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.463-471
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• 2021

Since 2016, National Institute of Standards and Technology (NIST) has been conducting a post quantum cryptography standardization project in preparation for a quantum computing environment. Three rounds are currently in progress, and most of the candidates (5/7) are lattice-based. Lattice-based post quantum cryptography is evaluated to be applicable even in an embedded environment where resources are limited by providing efficient operation processing and appropriate key length. Among them, SABER KEM provides the efficient modulus and Toom-Cook to process polynomial multiplication with computation-intensive tasks. In this paper, we present the optimized implementation of evaluation and interpolation in Toom-Cook algorithm of SABER utilizing ARM/NEON in ARMv8-A platform. In the evaluation process, we propose an efficient interleaving method of ARM/NEON, and in the interpolation process, we introduce an optimized implementation methodology applicable in various embedded environments. As a result, the proposed implementation achieved 3.5 times faster performance in the evaluation process and 5 times faster in the interpolation process than the previous reference implementation.

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.67-68
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• 2013

저가형 저전력 LED 구동회로에서는 종종 직렬 저항을 이용한 전류 밸런스 회로를 사용한다. 이러한 회로에서 밸런싱 저항은 양산시 생기는 LED 순방향 전압의 편차에 관계없이 LED 스트링간의 전류 밸런싱을 유지시키는 역할을 한다. 본 논문에서는 직렬 저항의 공칭값과 공급 전압값을 최적설계 하기위한 효과적인 설계 알고리즘을 제안한다. 제안한 알고리즘은 몬테카를로 기법을 사용하여 순방향 전압의 통계적인 산포와 직렬저항 소자의 상용값 및 공차를 동시에 고려하고, 비용함수를 도입하여 회로 최적화를 진행한다. 기존의 설계 방법 대비 성능 개선 정도를 구체적인 설계사례를 통해 비교 분석함으로써 제안 방법을 검증한다.