• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.388-393
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• 2007

In designing transform coders bit allocation is one of the important issues. In this paper we propose two optimal algorithms for integer bit allocation in transform coding. Based on high-resolution formulas for bit allocation, the most and least greedy algorithms are developed to optimally adjust non-integer bit rates of coefficient quantizers to integer values. In particular, a duality property is observed between the two greedy algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.8
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• pp.321-330
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• 2015

In journal manuscript submission and review systems, authors can submit their manuscript at any time and editorial members are struggling to find proper reviewers for the submitted manuscripts and assign them to such reviewers. In order to solve this problem, we propose a greedy algorithm and a genetic algorithm to recommend proper reviewers for the submitted manuscripts. The proposed algorithms evaluate reviewers' speciality for the submitted manuscripts by using the submitted manuscripts' keywords and the reviewers expertises. In addition to that, they take the fairness among the reviewers' speciality and the review frequency for consideration. To verify the proposed algorithms, we apply them to the JIPS manuscript submission and review system that the Korea Information Processing Society has operated, and present the results in this paper. By performing the performance evaluation of the proposed algorithms, we finally show that the genetic algorithm outperforms the greedy algorithm in terms of the recommended reviewers' fitness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.921-928
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• 2017

Unlike wired networks, broadcasting in wireless networks can transmit data to several nodes at a time in a single transmission. The omnidirectional broadcasting of node in wireless networks simultaneously reaches all neighboring nodes. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem that minimizes the total transmission power when broadcasting in wireless networks. The proposed algorithm uses a neighborhood list which is a set of nodes that can transmit messages within the maximum transmission range of each node, and among the transmitting nodes that have received the data, the node having the largest number of the neighboring nodes firstly transmits the data to neighboring node. The performance of the proposed algorithm was evaluated by computer simulation, and was compared with existing algorithms in terms of total transmission power and broadcasting frequency for broadcasting to all nodes. Experiment results show that the proposed algorithm outperforms the conventional algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.69-80
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• 2016

Some studies were conducted for the purpose of minimizing total clearance time for rapid evacuation from the indoor spaces when disaster occurs. Most studies took a long time to calculate the optimal evacuation route that derived minimum evacuation time. For this reason, this study proposes an evacuation route assignment algorithm that can shorten the total clearance time in a short operational time. When lots of exits are in the building, this algorithm can shorten the total clearance time by assigning the appropriate pedestrian traffic volume to each exit and balances each exit-load. The graph theory and greedy algorithm were utilized to assign pedestrian traffic volume to each exit in this study. To verify this algorithm, study used a cellular automata-based evacuation simulator and experimented various occupants distribution in a building structure. As a result, the total clearance time is reduced by using this algorithm, compared to the case of evacuating occupants to the exit within shortest distance. And it was confirmed that the operation takes a short time In a large building structure.

• Annual Conference of KIPS
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• 2015.10a
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• pp.41-44
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• 2015

하플로타입 페이징이란 상동 염색체의 DNA 염기 서열로부터 hetero SNP만을 읽어 들여 프래그먼트들을 만들고 이 프래그먼트들을 조합하여 하플로타입을 결정하는 것을 말한다. 하플로타입 페이징 과정에서 프래그먼트들의 조합은 무수히 많이 존재하며 때문에 하플로타입을 결정하기 위한 효율적인 알고리즘이 필요하다. 본 논문에서는 하플로타입 페이징 알고리즘들의 정확도 비교를 위해 제공되고 있는 데이터들을 가지고 탐욕적 알고리즘을 사용하여 하플로타입 페이징을 했을 경우 얼마나 정답과 유사한 하플로타입을 얻을 수 있는지를 분석하였다. 실험 결과 모든 데이터에 대하여 약 80%의 꽤 높은 정답률을 보였다. 더 나아가, 정답률이 저조한 구간에 대한 원인 분석을 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.185-191
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• 2019

During the modern battlefields of multi-batches flight formation attack situation, it is an essential task for a commander to make a proper fire distribution of air defense missile launch platforms for threat targets with effectively and quickly. Pan et al. try to solve this problem using genetic algorithm, but they are fails. This paper gets the initial feasible solution using high threat target first destroying strategy only use 75% available fire of each missile launch platform. Then, the assigned missile is moving to another target in the case of decreasing total threat. As a result of experiment, while the proposed algorithm is polynomial-time complexity greedy algorithm but this can be improve the solution than genetic algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.367-374
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• 2022

A sampling set selection algorithm is proposed to reconstruct original graph signals from the sampled signals generated on the nodes in the sampling set. Instead of directly minimizing the reconstruction error, we focus on minimizing the upper bound on the reconstruction error to reduce the algorithm complexity. The metric is manipulated by using QR factorization to produce the upper triangular matrix and the analytic result is presented to enable a greedy selection of the next nodes at iterations by using the diagonal entries of the upper triangular matrix, leading to an efficient sampling process with reduced complexity. We run experiments for various graphs to demonstrate a competitive reconstruction performance of the proposed algorithm while offering the execution time about 3.5 times faster than one of the previous selection methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.153-160
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• 2022

A greedy algorithm is proposed to select a subset of nodes of a graph for bandlimited graph signals in which each signal value is generated with its weight. Since graph signals are weighted, we seek to minimize the weighted reconstruction error which is formulated by using the QR factorization and derive an analytic result to find iteratively the node minimizing the weighted reconstruction error, leading to a simplified iterative selection process. Experiments show that the proposed method achieves a significant performance gain for graph signals with weights on various graphs as compared with the previous novel selection techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.641-644
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• 2016

Unlike wired networks, broadcasting in wireless networks can transmit data at once to several nodes with a single transmission. For omnidirectional broadcast to a node in wireless networks, all adjacent nodes receive the data at the same time. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem of minimizing the total transmit power on broadcasting in wireless networks. We apply two matrices to the proposed algorithm: one is a distance matrix that represents the distance between each node, the other is an adjacency matrix having the number of adjacency nodes. Among the nodes that receive the data, a node that has the greatest number of the adjacent node transmits data to neighbor preferential. We compare the performance of the proposed algorithm with random method through computer simulation in terms of transmitting power of nodes. Experiment results show that the proposed algorithm outperforms better than the random method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1682-1687
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• 2020

We study the problem of sampling a subset of nodes of graphs for bandlimited graph signals such that the signal values on the sampled nodes provide the most information in order to reconstruct the original graph signal. Instead of directly minimizing the reconstruction error, we focus on minimizing the upper bound of the reconstruction error to reduce the complexity of the selection process. We further simplify the upper bound by applying useful approximations to propose a low-weight greedy selection process that is iteratively conducted to find a suboptimal sampling set. Through the extensive experiments for various graphs, we inspect the performance of the proposed algorithm by comparing with different sampling set selection methods and show that the proposed technique runs fast while preserving a competitive reconstruction performance, yielding a practical solution to real-time applications.