• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.157-164
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• 2023

This paper suggests O(n²) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(T_e) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate _minr_w(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate _minr_fi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.196-198
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• 2003

Virtually every digital signal processors(DSPs) support on-chip multi- memory banks that allow the processor to access multiple words of data from memory in a single instruction cycle. Also, all existing fixed-point DSPs have irregular architecture of heterogeneous register which contains multiple register files that are distributed and dedicated to different sets of instructions. Although there have been several studies conducted to efficiently assign data to multi-memory banks, most of them assumed processors with relatively simple, homogeneous general-purpose resisters. Therefore, several vendor-provided compilers fer DSPs were unable to efficiently assign data to multiple data memory banks. thereby often failing to generate highly optimized code fer their machines. This paper presents an algorithm that helps the compiler to efficiently assign data to multi- memory banks. Our algorithm differs from previous work in that it assigns variables to memory banks in separate, decoupled code generation phases, instead of a single, tightly-coupled phase. The experimental results have revealed that our decoupled algorithm greatly simplifies our code generation process; thus our compiler runs extremely fast, yet generates target code that is comparable In quality to the code generated by a coupled approach

• 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 Internet Computing and Services
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• v.19 no.5
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• pp.89-96
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• 2018

In online communities, a large number of participants can exchange their opinion using replies without time and space restrictions. While the online space provides quick and free communication, it also easily triggers unnecessary quarrels and conflicts. The network established on the discussion participants is an important cue to analyze the confrontation and predict serious disputes. In this paper, we present a quantitative measure for polarity observed on the discussion network built from reply exchanges in online communities. The proposed method uses the comment exchange information to establish the user interaction network graph, computes its maximum spanning tree, and then performs vertex coloring to assign two colors to each node in order to divide the discussion participants into two subsets. Using the proportion of the comment exchanges across the partitioned user subsets, we compute the polarity measure, and quantify how discussion participants are bipolarized. Using experimental results, we demonstrate the effectiveness of our method for detecting polarization and show participants of a specific discussion subject tend to be divided into two camps when they debate.