• KIPS Transactions on Computer and Communication Systems
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• v.7 no.9
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• pp.219-226
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• 2018

One of the systematic ways to generate the number of all cases is a combination to construct a combination tree, and its time complexity is O($2^n$). A combination tree is used for various purposes such as the graph homogeneity problem, the initial model for calculating frequent item sets, and so on. However, algorithms that must search the number of all cases of a combination are difficult to use realistically due to high time complexity. Nevertheless, as the amount of data becomes large and various studies are being carried out to utilize the data, the number of cases of searching all cases is increasing. Recently, as the GPU environment becomes popular and can be easily accessed, various attempts have been made to reduce time by parallelizing algorithms having high time complexity in a serial environment. Because the method of generating the number of all cases in combination is sequential and the size of sub-task is biased, it is not suitable for parallel implementation. The efficiency of parallel algorithms can be maximized when all threads have tasks with similar size. In this paper, we propose a method to efficiently collaborate between CPU and GPU to parallelize the problem of finding the number of all cases. In order to evaluate the performance of the proposed algorithm, we analyze the time complexity in the theoretical aspect, and compare the experimental time of the proposed algorithm with other algorithms in CPU and GPU environment. Experimental results show that the proposed CPU and GPU collaboration algorithm maintains a balance between the execution time of the CPU and GPU compared to the previous algorithms, and the execution time is improved remarkable as the number of elements increases.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.198-200
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• 2006

This paper presents a development of an educational simulator of particle swarm optimization (PSO) and application for solving the test functions and economic dispatch (ED) problems with nonsmooth cost functions. A particle swarm optimization is one of the most powerful methods for solving global optimization problems. It is a population-based search algorithm and searches in parallel using a group of particles similar to other AI-based heuristic optimization techniques. In developed simulator, lecturers and students can select the functions for simulation and set the parameters that have an influence on PSO performance. To improve searching capability for ED problems, a crossover operation is proposed to the position update of each individual (CR-PSO). To verify the feasibility of CR-PSO method, numerical studies have been performed for two different sample systems. The proposed CR-PSO method outperforms other algorithms in solving ED problems.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.66-76
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• 2009

The motion estimation in video encoding system occupies the biggest part. So, we require the motion estimator with efficient structure for real-time operation. And for motion estimator's implementation, it is desired to design hardware module of an exclusive use that perform the encoding process at high speed. This paper proposes motion estimation detection block(MED), 41 SADs(Sum of Absolute Difference) calculation block, minimum SAD calculation and motion vector generation block based on parallel processing. The parallel processing can reduce effectively the amount of the operation. The minimum SAD calculation and MED block uses the pre-computation technique for reducing switching activity of the input signal. It results in high-speed operation. The MED and 41 SADs calculation blocks are composed of adder tree which causes the problem of critical path. So, the structure of adder tree has changed the most commonly used ripple carry adder(RCA) with carry skip adder(CSA). It enables adder tree to operate at high speed. In addition, as we enabled to easily control key variables such as control signal of search range from the outside, the efficiency of hardware structure increased. Simulation and FPGA verification results show that the delay of MED block generating the critical path at the motion estimator is reduced about 19.89% than the conventional strukcture.

• Journal of IKEEE
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• v.21 no.1
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• pp.100-103
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• 2017

Motion estimation occupies the largest computation in the video compression. Multiple processing elements are often exploited in parallel to meet processing speed. More processing elements increase processing speed, but they also increase hardware area. therefore, it is important to optimize the number of processing element. HEVC (high efficiency video coding) usually exploits multi-stage motion estimation algorithms for low computation and high performance. Since the number and position of search points are different in each stage, the utilization of the processing elements is not always 100% and the utilization is quite different with the number of processing elements. In this paper, the optimizing method is proposed on the number of processing elements. It finds out the optimal number of the processing elements for the given multi-stage motion estimation algorithm by calculating utilization and execution cycle of the processing elements.

• The Journal of Korean Association of Computer Education
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• v.21 no.6
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• pp.39-47
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• 2018

This paper dealt with investigating the number of minimal spanning ladders originated from ladder game and their properties as well as the related computational thinking aspects. The author modified the filtering techniques to enhance Mathematica project where a new type of graph was generated based on the algorithm using a generator of firstly found minimal spanning graph by repeatedly applying independent ladder operator to a subsequence of ladder sequence. The newly produced YC graphs had recursive and hierarchical graph structures and showed the properties of edge-symmetric. As the computational complexity increased the author divided the whole search space into the each floor of the newly generated minimal spanning graphs for the (5, 10) YC graph and the higher (6, 15) YC graph. It turned out that the computational thinking capabilities such as data visualization, abstraction, and parallel computing with Mathematica contributed to enumerating the new YC graphs in order to investigate their structures and properties.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.624-627
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• 2004

본 연구는 동일한 병렬기계에서의 총 납기지연의 합을 최소화하는 일정계획 문제에 대해 다룬다. 이 문제는 Lenstra et al. (1977)에 의해 NP-hard로 알려져 있으며, 작업의 수와 기계의 수가 큰 현실적 문제에 대해 적절한 시간 내에 최적해를 찾는다는 것은 사실상 불가능하다. 따라서 본 연구에서는 이 문제를 해결하기 위하여 혼합형 유전 알고리즘(hybrid genetic algorithm)을 제안한다. 혼합형 유전 알고리즘에서는 임의로 발생시킨 모집단에 대해 먼저 유전 알고리즘(genetic algorithm)이 세대를 진행하며 해를 개선한다. 유전 알고리즘이 일정기간동안 더 이상 해를 개선하지 못하면, 부분탐색 알고리즘(local-search algorithm))이 유전 알고리즘의 모집단의 개체들에 대해 해의 개선을 시도한다. 즉, 부분 탐색 알고리즘은 모집단 속의 각각의 개체를 초기해로 하여 모집단 내의 개체 수만큼의 부분 최적해(local optimum)들을 구한다. 이렇게 구한 부분 최적해들로 새로운 모집단을 구성하면 다시 유전 알고리즘이 진행된다. 이 과정을 종료조건에 이를 때까지 번갈아가며 반복 수행한다. 본 연구에서 제안한 유전 알고리즘에서는 Bean(1994)이 제안한 Random key 방법으로 개체를 표현하였으며 Park(2000)이 제안한 3가지 교차 연산자들을 채용하였다. 부분탐색 알고리즘을 위해서는 쌍대교환(pair-wise interchange) 방법을 통해 이웃해를 생성하였다. 선행실험을 통하여 제안한 혼합형 유전알고리즘에서 사용하는 다양한 모수(parameter)값들을 최적화하였으며 알고리즘의 성능을 비교하기 위하여 기존의 알고리즘과도 비교실험을 수행하였다.복적인 지표가 채택되는 경우를 포함하고 있다. 셋째는 추상적이며 측정이 어려운 지표를 채택하고 있는 경우이다. 여기에는 지표에 대한 정확한 정의가 이루어져 있지 않아 피 평가자가 불필요하거나 과다한 평가 자료를 준비해야 하거나 평가자로 하여금 평가 시 혼돈을 유발할 가능성이 있거나, 또는 상위개념의 평가항목과 하위개념의 평가항목이 혼재되어 구분이 모호한 경우를 포함하고 있다. 바탕으로 '생태적 합리성'이라는 체계적인 지식교육을 거쳐서, '환경정의' 의식의 제고로 이어가고, 굵직한 '환경갈등'의 상황에서 뚜렷한 정치적 태도와 실천을 할 수 있는 '생태적 인간상'의 육성으로 나아갈 수 있어야 한다는 것이 필자의 생각이다. 이를 위해서는 어찌되었건 체험학습 영역에서는 환경현안에 대한 사회적 실천을 '교육 소재'로 삼을 수 있어야 하며, 교과학습 영역에서는 한국사회의 환경현안에 대한 정치경제적 접근을 외면하지 말고 교과서 저작의 소재로 삼을 수 있어야 하며, 이는 '환경관리주의'와 '녹색소비'에 머물러 있는 '환경 지식교육'과 실천을 한단계 진전시키는 작업으로 이어질 것이다. 이후 10년의 환경교육은 바로 '생태적 합리성'과 '환경정의'라는 두 '화두'에 터하여 세워져야 한다.배액에서 약해를 보였으나, 25% 야자지방산의 경우 50 ${\sim}$ 100배액 어디에서도 액해를 보이지 않았다. 별도로 적용한 시험에서, 토마토의 경우에도 25% 야자지방산 비누 50 ${\sim}$ 100배액 모두 약해를 발생하지 않았으나, 오이에서는 25% 야자지방산 비누 100배액에도 약해를 나타내었다. 12. 이상의 결과, 천연지방산을 이용하여 유기농업에 허용되는 각종의 살충비누를 제조할 수 있었으

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.183-192
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• 2022

With the growth of the packaging industry, demand on the packaging printing comes in various forms. Customers' orders are diversifying and the standards for quality are increasing. Offset printing is mainly used in the packaging printing since it is easy to print in large quantities. However, productivity of the offset printing decreases when printing various order. This is because it takes time to change colors for each printing unit. Therefore, scheduling that minimizes the color replacement time and shortens the overall makespan is required. By the existing manual method based on workers' experience or intuition, scheduling results may vary for workers and this uncertainty increase the production cost. In this study, we propose an automated scheduling method of parallel offset printing process for packaging printing. We decompose the original problem into assigning and sequencing orders, and ink arrangement for printing problems. Vehicle routing problem and assignment problem are applied to each part. Mixed integer programming is used to model the problem mathematically. But it needs a lot of computational time to solve as the size of the problem grows. So guided local search algorithm is used to solve the problem. Through actual data experiments, we reviewed our method's applicability and role in the field.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.1-7
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• 2002

The fast extraction of the silhouettes of a model is very useful for many applications in computer graphics and animation. In this paper, we present an efficient algorithm to compute a sequence of perspective silhouettes for a polyhedral model from a moving viewpoint. The viewpoint is assumed to move along a trajectory q(t), which is a space curve of a time parameter t. Then, we can compute the time-intervals for each edge of the model to be contained in the silhouette by two major computations: (i) intersecting q(t) with two planes and (ii) a number of dot products. If q(t) is a curve of degree n, then there are at most of n + 1 time-intervals for an edge to be in a silhouette. For each time point $t_i$ we can extract silhouette edges by searching the intervals containing $t_i$ among the computed intervals. For the efficient search, we propose two kinds of data structures for storing the intervals: an interval tree and an array. Our algorithm can be easily extended to compute the parallel silhouettes with minor modifications.