• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.7-13
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• 2017

In this paper, we propose a novel dynamic subchannel grouping (DSG) algorithm to maximize the system capacity considering intended proper outage probability for the downlink of enterprise small-cell networks (ESNs). In the proposed DSG scheme, a local gateway (LGW) which is installed in a building dynamically divides the frequency bandwidth into different numbers of subchannel groups (SGs) based on the numbers of small-cell access points (SAPs) and small-cell user equipments (SUEs) per floor. Then, the LGW assigns the SGs to SAPs and the SAPs allocate them to their serving SUEs. Through simulation results, we show that the proposed DSG scheme is appropriate for the ESNs compared to the conventional small-cell networks in which all SAPs use the number of fixed SGs in terms of the system capacity and outage probability.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.63-73
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• 1997

For the practical applications of the EIT technology, it is essential to reconstruct sttic images iwth a higher spatial resolution in a reasonalble amount of processing time. Using the conventional EIT static image reconstruction algorithms, however, the processing time increases exponential with poor convergence characteristics as we try to get a higher spatial resolution. In order to overcome this problem, we developed a recursive mesh grouping method based on the Fuzzy-GA like algorithm. Computational simulation using the well-known improve dewton-raphson method with the proposed recursive mesh grouping algorithm shows a promising result that we can significantly reduce the processing time in the reconstruction of EIT static images of a higher spatial resolution.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.71-77
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• 2016

There has been unknown polynomial time algorithm for cellular formation problem (CFP) that is one of the NP-hard problem. Therefore metaheuristic method has been applied this problem to obtain approximated solution. This paper shows the existence of polynomial-time heuristic algorithm in CFP. The proposed algorithm performs coarse-grained and fine-grained cell formation process. In coarse-grained cell formation process, the cell can be formed in accordance with machine frequently used that is the number of other products use same machine with special product. As a result, the machine can be assigned to most used cell. In fine-grained process, the product and machine are moved into other cell that has a improved grouping efficiency. For 35 experimental data, this heuristic algorithm performs better grouping efficiency for 12 data than best known of meta-heuristic methods.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.441-451
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• 2022

In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.27-35
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• 2005

As the number of Mobile IP users is expected to grow, the signaling overhead associated with mobility management in the wireless Internet is bound to grow. And since the wireless link has far less bandwidth resources and limited scalability compared to the wired network link, the signaling overhead associated with mobility management has a severe effect on the wireless link. In this paper, we propose IP-Grouping algorithm that can greatly reduce the signaling cost in the wireless link as Access Routers(ARs) with a large rate of handoff are grouped into a Group Zone. Based on the numerical analysis and simulation, we show that the wireless signaling cost in the IP-Grouping is much lower than that of the Hierarchical Mobile IPv6 under various condition.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.171-178
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• 2013

Desktop grid computing is the computing paradigm that can execute large-scale computing jobs using the desktop resources with heterogeneity and volatility. However, such the computing environment can not guarantee the stability and reliability of task execution because the desktop resources with different performance can freely participate and leave in task execution. Therefore, in this paper, we design resource grouping scheme using k-means clustering algorithm with an aim to provide desktop grid computing with the stability and reliability of task execution. Moreover, we conduct resource grouping using the execution log data of actual desktop grid systems and present application methods of desktop resource groups to fault-tolerance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.702-711
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• 2011

This paper proposes a HAG(Hidden-Node-Aware Grouping) algorithm for IEEE 802.15.4 networks to enhance the performance by eliminating collisions resulted from the hidden node problem without adopting the RTS/CTS packet exchanges. To solve the hidden node problem, the HAG algorithm organizes nodes into disjoint transmission groups by dynamically allocating hidden nodes into separate groups which take turns in a round robin way for their transmission. For dynamic group adjustment, it periodically evaluates the presence of hidden nodes based on subordinate nodes' receipt reports. To accurately measure its behavior, this paper also builds an analytical model to estimate its throughput fluctuation over various network topologies. The mathematical model along with simulation results confirmed that the HAG technique gracefully degraded the throughput of IEEE 802.15.4 networks whereas the standard IEEE 802.15.4 networks suffer severe throughput fallout as hidden nodes become populated.

• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.51-64
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• 2005

In this paper, we introduce a system for evaluating similarity of C program source code using method which compares syntax-trees each others. This method supposes two characteristic features as against other systems. It is not sensitive for program style such as indentation, white space, and comments, and changing order of control structure like sentences, code block, procedures, and so on. Another is that it can detect a syntax-error cause of using paring technique, We introduce algorithms for similarity evaluation method and grouping method that reduces the number of comparison, In the examination section, we show a test result of program similarity evaluation and its reduced iteration by grouping algorithm.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.275-284
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• 2014

Decision Tree is one of analysis techniques which conducts grouping and prediction into several sub-groups from interested groups. Researcher can easily understand this progress and explain than other techniques. Because Decision Tree is easy technique to see results. This paper uses CART algorithm which is one of data mining technique. It used 273 variables and 70094 data(2010-2011) of working environment survey conducted by Korea Occupational Safety and Health Agency(KOSHA). And then refines this data, uses final 12 variables and 35447 data. To find satisfaction factor in working environment, this page has grouped employee to 3 types (under 30 age, 30 ~ 49age, over 50 age) and analyzed factor. Using CART algorithm, finds the best grouping variables in 155 data. It appeared that 'comfortable in organization' and 'proper reward' is the best grouping factor.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.