• 정보교육학회논문지
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• 제14권3호
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• pp.301-310
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• 2010

본 논문에서는 정보교과의 초등 프로그래밍기초교육에서 흐름도 중심의 프로그래밍 지도를 위해, 라인트레이서 로봇을 활용한 센서기반 초등로봇프로그래밍 PBL 문제를 제안하였다. 제안한 초등로봇프로그래밍 문제는 다양한 알고리즘을 답안으로 갖도록 설계되었다. 이를 위해 PBL기반 초등로봇프로그래밍 교육단계를 제시하였다. 그리고 라인트레이서 로봇 예제를 통해 제안한 PBL 문제들을 활용하여, 실제 수업에 적용한 결과를 난이도 할당의 적절성 및 학생들의 문제해결력 측면에서 분석하였다.

• Computers and Concrete
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• 제30권3호
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• pp.225-236
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• 2022

In this article, Multi-Gene Genetic Programming (MGGP) is proposed for the estimation of the compressive strength of concrete. MGGP is known to be a powerful algorithm able to find a relationship between certain input space features and a desired output vector. With respect to most conventional machine learning algorithms, which are often used as "black boxes" that do not provide a mathematical formulation of the output-input relationship, MGGP is able to identify a closed-form formula for the input-output relationship. In the study presented in this article, MGPP was used to predict the compressive strength of plain concrete, concrete with fly ash, and concrete with furnace slag. A formula was extracted for each mixture and the performance and the accuracy of the predictions were compared to the results of Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) algorithms, which are conventional and well-established machine learning techniques. The results of the study showed that MGGP can achieve a desirable performance, as the coefficients of determination for plain concrete, concrete with ash, and concrete with slag from the testing phase were equal to 0.928, 0.906, 0.890, respectively. In addition, it was found that MGGP outperforms ELM in all cases and its' accuracy is slightly less than ANN's accuracy. However, MGGP models are practical and easy-to-use since they extract closed-form formulas that may be implemented and used for the prediction of compressive strength.

• Structural Engineering and Mechanics
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• 제76권6호
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• pp.799-821
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• 2020

The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

• Asian-Australasian Journal of Animal Sciences
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• 제16권6호
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• pp.894-902
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• 2003

Prebiotics (peptides, N-acetyglucoamine, fructo-oligosaccharides, isomalto-oligosaccharides and galactooligosaccharides) were added to skim milk in order to improve the growth rate of contained Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium longum and Bifidobacterium bifidum. The purpose of this research was to study the potential synergy between probiotics and prebiotics when present in milk, and to apply modern optimization techniques to obtain optimal design and performance for the growth rate of the probiotics using a response surface-modeling technique. To carry out response surface modeling, the regression method was performed on experimental results to build mathematical models. The models were then formulated as an objective function in an optimization problem that was consequently optimized using a genetic algorithm and sequential quadratic programming approach to obtain the maximum growth rate of the probiotics. The results showed that the quadratic models appeared to have the most accurate response surface fit. Both SQP and GA were able to identify the optimal combination of prebiotics to stimulate the growth of probiotics in milk. Comparing both methods, SQP appeared to be more efficient than GA at such a task.

• 대한산업공학회지
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• 제27권1호
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• pp.1-10
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• 2001

In the reverse engineering, surfaces are modeled for new products by interpolating the digitized data points obtained by measuring the existing shapes. However, many measuring or deviation errors are happened during the measuring process. If these errors are ignored, designers could get undesirable results. Therefore, it is important to handle such errors and fairing procedure with the esthetics criteria is needed during surface modeling process. This paper presents algorithms for the fairing of B-spline surfaces. The algorithms are based on automatic repositioning of control points for B-spline surfaces. New positions of the control points are determined by solving a non-linear programming of which the objective functions are derived variously using derived surfaces and constraints are established by distance measures between the original and the modified control points. Changes in surface shapes are analyzed by illustrations of their shapes and continuous plotting of gaussian and mean curvatures.

• 디지털융복합연구
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• 제13권12호
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• pp.209-215
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• 2015

차량 등 객체를 추적하기 위한 많은 알고리즘들이 있지만 본 논문에서 제안하는 특징점 정합 알고리즘 분야는 지수 복잡도의 시간이 걸리는 작업이다. 더구나, 차량을 추적하기 위해 기존에 제안되었던 객체 추출 등 영상 전처리 알고리즘 또한 상당한 시간을 요구한다. 따라서 본 논문에서는 도로상에서 많은 차량들의 이동 궤적을 빠르고 효율적으로 추적하기 위한 방법을 2단계로 제안한다. 1단계로 객체 탐지가 아닌 번호판 영역을 먼저 탐지한 후 특징점을 추출하는 단계하고, 2단계로 특징점들을 정합하기 위한 비용산정식을 구한 후 동적계획법을 이용하여 효율적으로 차량을 추적할 수 있는 방법을 제안한다.

• 한국공간구조학회논문집
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• 제3권1호
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• pp.35-46
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• 2003

Conventional analysis and design of steel structures are performed using the assumption of a either fully rigid or pinned. However, every steel connection lies in between fully rigid and pinned connection. So, It is important to consider the connection for steel structure design. In this paper Computer-based second-order elastic analysis is used to calculate one story two bay and two story three bay for steel structures with semi-rigid connection. Genetic Algorithms(GAs) and Sequential Unconstrained Minized Technique(SUMT) dynamic programming is used to the method for optimum design of steel structures. The efficiency and validity of the developed continuous and discrete optimum design algorithm was verified by applying the algorithm to optimum design examples.

• 한국전자통신학회논문지
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• 제6권2호
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• pp.212-218
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• 2011

알고리즘과 프로그래밍 교육 과정은 전자공학 및 컴퓨터 관련학과를 비롯한 많은 이공계 학과에서 매우 중요한 교과목으로 인식된다. 본 논문에서는 프로그래밍 과정 중 기본 알고리즘에 대해 쉽게 익힐 수 있도록 기초 알고리즘을 활용한 프로그래밍 언어 학습 시스템의 효용성을 분석하였다. 그 결과 본 시스템을 사용한 실험 단체가 비실험 단체보다 학업성취도가 15점 이상 높았다. 그리고 실험 참가 학생들의 C 언어 프로그램에 대한 흥미도, 집중도, 이해도, 효과성, 편리성, 적합성, 다음 학기 수업 희망 사항 등에서도 5점 척도 평균값이 약 4점 이상으로 높게 나타났다.

• 전기학회논문지P
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• 제54권2호
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• pp.61-66
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• 2005

This paper presents an unified method which solves real and reactive power dispatch problems for the economic operation of power systems using evolutionary computation such as genetic algorithms(GA), evolutionary programming(EP), and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most of these approaches have the common defect of being caught to a local minimum solution. The proposed methods, applied to the IEEE 30-bus system, were run for 10 other exogenous parameters and composed of P-optimization module and Q-optimization module. Each simulation result, by which evolutionary computations are compared and analyzed, shows the possibility of applications of evolutionary computation to large scale power systems.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.438-441
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• 2004

Image binarization using a global threshold value [3] performs at high speed, but usually results in undesired binary images when the source images are of poor quality. In such cases, adaptive local thresholding algorithms [1][2][3] are used to obtain better results, and the algorithm proposed by A.E.Savekis which chooses local threshold using fore­ground and background clustering [1] is one of the best thresholding algorithms. However, this algorithm runs slowly due to its re-computing threshold value of each central pixel in a local window MxM. In this paper, we present a dynamic programming approach for the step of calculating local threshold value that reduces many redundant computations and improves the execution speed significantly. Experiments show that our proposal improvement runs more ten times faster than the original algorithm.