• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.1-9
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• 2018

The multiple-choice multidimensional knapsack problem (MMKP) is a variant of the well known 0-1 knapsack problem, which is known as an NP-hard problem. This paper proposes a method for solving the MMKP using the integer programming-based local search (IPbLS). IPbLS is a kind of a local search and uses integer programming to generate a neighbor solution. The most important thing in IPbLS is the way to select items participating in the next integer programming step. In this paper, three ways to select items are introduced and compared on 37 well-known benchmark data instances. Experimental results shows that the method using linear programming is the best for the MMKP. It also shows that the proposed method can find the equal or better solutions than the best known solutions in 23 data instances, and the new better solutions in 13 instances.

• 산업경영시스템학회지
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• 제40권4호
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• pp.237-245
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• 2017

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

• 한국정보처리학회논문지
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• 제4권2호
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• pp.616-627
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• 1997

본 논문에서는 동영상 처리에서 사용되는 움직임 추정을 위한 삼단 검색 알고리 즘의 구조에서는 규칙적인 데이타 입력이 가능하게 되고 입력된 데이타는 그 데이타를 사용하는 모든 연산과정을 거치게 되어 데이타 입력 대역폭이 최소화 된다. 기존의 구조 들 보다 적은 자원으로 최대 계산 속도에 접근하는 성능을 가진다. 제안된 구조의 성능 분석과 다른 구조들과의 비교가 제시된다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1998년도 추계 학술대회논문집
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• pp.13-18
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• 1998

The practical use of the particle image velocimetry(PIV), a whole-field velocity measurement method, requires the use of fast, reliable, computer-based methods for tracking velocity vectors. The full search block matching, the most widely studied and applied technique both in area of PIV and Image Coding and Compression, is computationally costly. Many less expensive alternatives have been proposed mostly in the area of Image Coding and Compression. Among others, TSS, NTSS, HPM are introduced for the past PIV analysis, and found to be successful. But, these algorithms are based on small dynamic range, 7 pixels/frame in maximum displacement. To analyze the images with large displacement, Even and Odd field image separation and a simple version of multi-resolution hierarchical procedures are introduced in this paper. Comparison with other algorithms are summarized. A Results of application to the turbulent backward step flow shows the improvement of new algorithm.

• 산업경영시스템학회지
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• 제43권2호
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• pp.126-136
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• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1426-1435
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• 2003

Design goal is to find the one that has the highest probability of success and the smallest variation. A robustness index has been proposed to satisfy these conditions. The two-step optimization process of the target problem requires a scaling factor. The search process of a scaling factor is replaced with the making of the decoupled design between the mean and the standard deviation. The decoupled design matrix is formed from the sensitivity or the sum of squares. After establishing the design matrix, the robust design process has a new three-step one. The first is ″reduce variability,″ the second is ″make the candidate designs that satisfy constraints and move the mean on the target,″ and the final is ″select the best robust design using the proposed robustness index.″ The robust design process is verified by three examples and the results using the robustness index are compared with those of other indices.

• 전자공학회논문지B
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• 제30B권6호
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• pp.35-48
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• 1993

In this paper, a hierarchical motion vector estimation algorithm using pyramidal structure is proposed. Using a smaller measurement window at each level of a pyramid than that of the conventional scheme, the proposed algorithm, based on the TSS(three step search), reduces the computational complexity greatly with its performance comparable to that of the TSS. By increasing the number of cnadidate motion vectors which are to be used as the initial search points for motion vector estimation at the next level, the performance improves further. Then the computational complexity of the proposed hierarchical algorithm depends on the number of candidate motion vectors, with its PSNR (peak signal to noise ratio) ranging between those of the TSS and the full search method. The simulation results with two different block sizes and various test sequences are given and its hardware implementation is also sketched.

• 품질경영학회지
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• 제18권2호
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• pp.25-32
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• 1990

This paper presents an approximate algorithm for computing Fault-tree probabilities. The method is essentially composed of three steps. In the first step, a Fault-tree is converted into a network form. In the second step, We change the network into a parallelized diagram. In the third step, the approximate fault-tree probability is calculated from the parallelized diagram. In this paper, in order to verify the method two hypothetical Fault-tree is used by examples. The results show that the method is very useful, even though it is an approximate technique, since it needs not to search the minimal cut sets and has the simple computing rontines.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• Journal of applied mathematics & informatics
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• 제30권1_2호
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• pp.127-133
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• 2012

We establish the polynomial convergence of a new class of path-following methods for SDLCP whose search directions belong to the class of directions introduced by Monteiro [3]. We show that the polynomial iteration-complexity bounds of the well known algorithms for linear programming, namely the short-step path-following algorithm of Kojima et al. and Monteiro and Alder, carry over to the context of SDLCP.