• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.42-48
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• 1999

Consider the situation that informations necessary to solve a certain problem are distributed among processors on a network. It is called a distributed algorithm that in this situation each processor exchanges the message with adjacent processors to solve the problems. This paper proposes a distributed algorithm to solve the problem that constructs the weighted shortest path tree in an asynchronous network system. In general, a distributed algorithm is estimated by the number of messages(message complexity of the distributed algorithm proposed in this paper are O(n53) and O(nln) respectively. where n is the number of processors on the network.

• The Journal of the Acoustical Society of Korea
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• v.12 no.2
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• pp.5-13
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• 1993

The purpose of this paper is to suggest and analyze the parallel algorithm for merging two heaps, on SIMD-SM-R parallel computer. In order to create the parallel algorithm for merging two heaps, we have classified two subproblems. For the first method, to select node p as a LEVEL-FIND function, Wyllie(19) suggests the method with time complexity O(log n) while this thesis has O(log(n/k)). For the second method, to merge two subheap, our algorithm has O(log(n/k)*log(n)) using max(2**(i-1), 「(m+1)/4」)'s processors while Dekel and Sahni(4)'s method and Hong's method(18) have O(log m). Also our parallel algorithm's EPU is close to 1 and so has an optimal speed-up ratio.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.925-928
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• 2003

As the maximum power operating point(MPOP) of photovoltaic(PV) power generation systems changes with changing atmospheric conditions such as solar radiation and temperature, an important consideration in the design of efficient PV system is to track the MPOP correctly. Many maximum power point tracking(MPPT) techniques have been considered in the past, however, techniques using microprocessors with appropriate MPPT algorithms are favored because of their flexibility and compatibility with different PV arrays. Although the efficiency of these MPPT algorithms is usually high, it drops noticeably in case of rapidly changing atmospheric conditions. This paper proposed a new MPPT algorithm based on perturb & observe(P&O) algorithm with experiment. The results shows that the new P&O algorithm has successfully tracked the MPOP, even in case of rapidly changing atmospheric conditions, and has higher efficiency than ordinary algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.57-70
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• 2004

Given a tree network on which each node has its own demand and also stands for a candidate location of a potential facility. such as plant or warehouse, the f-median problem on the network (PMPOT) is to select less than or equal to P number of facility locations so that the whole demand on a node is satisfied from only one facility and the total demand occurred on the network can be satisfied from those facilities with the minimum total cost, where the total cost Is the sum of transportation costs and the fixed costs of establishing facilities. Tamir(1996) developed an O(p n$^2$) algorithm for PMPOT which is known to be the best algorithm In terms of the time complexity, where n is the number of nodes in the network, but he didn't make any comments or explanation about implementation details for finding the optimal solution. In contrast to Tamir's work, Kariv and Hakimi(1979) developed O(p$^2$n$^2$) algorithm for PMPOT and presented O(n$^2$) algorithm for finding the optimal solution in detail. In this paper, we not only develop another O(p n$^2$) dynamic programming algorithm for PMPOT that is competitive to Tamir's algorithm in terms of the time complexity, but also present O(n) algorithm that is more efficient than kariv and Hakimi's algorithm in finding the optimal solution. finally, we implement our algorithm on a set of randomly generated problems and report the computational results.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.111-117
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• 2015

The exam scheduling problem has been classified as nondeterministic polynomial time-complete (NP-complete) problem because of the polynomial time algorithm to obtain the exact solution has been unknown yet. Gu${\acute{e}}$ret et al. tries to obtain the solution using linear programming with $O(m^4)$ time complexity for this problem. On the other hand, this paper suggests chromatic number algorithm with O(m) time complexity. The proposed algorithm converts the original data to incompatibility matrix for modules and graph firstly. Then, this algorithm packs the minimum degree vertex (module) and not adjacent vertex to this vertex into the bin $B_i$ with color $C_i$ in order to exam within minimum time period and meet the incompatibility constraints. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(m) time complexity for exam scheduling problem, and gets the same solution with linear programming.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.63-68
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• 2021

In this study, data was augmentation through the SinGAN algorithm using small image data, and defects in rubber O-rings were detected using the random forest algorithm. Unlike the commonly used data augmentation image rotation method to solve the data imbalance problem, the data imbalance problem was solved by using the SinGAN algorithm. A study was conducted to distinguish between normal products and defective products of rubber o-ring by using the random forest algorithm. A total of 20,000 image date were divided into transit and testing datasets, and an accuracy result was obtained to distinguish 97.43% defects as a result of the test.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.141-151
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• 2012

This paper suggests more simple algorithm than Hungarian algorithm for assignment problem. Hungarian algorithm selects minimum cost of row and column, and subtracts minimum cost from each cost. Then, performs until the number of minimum lines with 0 equals the number of rows. But, the proposed algorithm selects the minimum cost for each rows only. From the start point with over 2 to the target point with null selects in column, fixes the maximum opportunity cost that the difference of the cost of starting point and target point, and moves the cost less than opportunity cost th more than previous cost. For the 25 balance and 7 unbalance assignment problems, This algorithm gets the optimal solution same as Hungarian algorithm. This algorithm improves the time complexity $O(n^3)$ of Hungarian algorithm to $O(n^2)$, and do not performs the transformation process from unbalance to balance assignment in Hungarian algorithm. Therefore, this algorithm can be alter Hungarian algorithm in assignment problem.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.325-330
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• 2004

The Big O notation of a sorting algorithm analysis is an asymptotic algorithm analysis which gives information of a rough mathematical function with an infinite increase of a sample size, without any specification of a probabilistic model. Hence. in an application with a limited finite number of data, it is necessary to test efficiencies of sorting algorithms. I estimated probabilistic models which analyze the number of exchanges varying input sizes to sort. The estimated models to explain the relationship of sorting efficiency on the sample size (N of the sample size and S of the number of exchange of elements) are S=0.9305 $N^{1.339}$ for Quick sort algorithm with O(nlogn) time complexity, and S=0.2232 $N^{2.0130}$ for Insertion sort algorithm with O( $n^2$) time complexity. Furthermore, there are strongly supports that more than 99% of the above relationship could be explained by the estimated models (p＜0.001). These findings suggest it is necessary to analyze sorting algorithm efficiency in applications with a finite number of data or a newly developed sorting algorithm.

• The Journal of Engineering Research
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• v.1 no.1
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• pp.49-57
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• 1997

In this paper, the follow-up works of Habermann's deadlock avoidance algorithm is investigated from the view of correction, efficiency and concurrency. Habermann's deadlock avoidance algorithm is briefly surveyed and in-depth discussion of follow-up algorithms modified and improved is presented. Then, further improvement of Kameda's algorithm will be discussed. His algorithm for testing deadlock-freedom in computer system converts the Habermann's model into a labeled bipartite graph so that the deadlock detection problem can be equivalent to finding complete matching for Mormon marriage problem. His algorithm has a running time of O($mn^1.5$) because Dinic's algorithm is used. The speed of above algorithm can be enhanced by employing a faster algorithm for finding a maximal matching. The wave method by Kazanov is used for.

• Journal of IKEEE
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• v.24 no.2
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• pp.507-513
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• 2020

The median filter that is used in various fields requiring image processing converts to a median value of pixels belonging to a radius r for all pixels in the image of n×m size. For 8-bit depth images, an O(nm) time algorithm exists but for over 16-bit depth images, there is an O(nmlog²r) time algorithm of Gil and Werman. In this paper, we propose an efficient median filter algorithm that works for more than 16-bit depth images. The time complexity of our algorithm is the same as that of Gil and Werman, but theoretical analysis and experimental results show that ours is efficient than above two times.