• Journal of Korean Society of Rural Planning
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• v.16 no.2
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• pp.1-10
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• 2010

This study aimed to systematically adjust rural area development projects that have been carried out by a variety of government departments for activation of rural areas and overcome inefficient problems caused by the policies and projects promoted separately. As its alternative, this study aimed to explore efficient improvement scheme of rural villages associated with various projects. Major agriculture/rural policies and projects that have been promoted were classified by the target space of the policies and projects as Environment space, living space, and production space. Each space was categorized into five sub-items without duplication. By assessment results of rural area improvement level and preference by Analytic Hierarchy Process(AHP) method, maintenance of rural areas was classified into four types. And outer space structure was analyzed by using Space Syntax Method(SSM). Based on the analysis result above, facilities for improvement of rural villages were placed around representative facilities. Facility allocation was based on selection and concentration in terms of facility maintenance and on type attributes in terms of spatial aspects. And finally, alternatives schemes for setting up the basic direction of improvement of rural villages are local area characteristics and environmentally conscious business plan.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.454-462
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• 2016

portable white space device(WSD) obeying the Korean regulations of TV white space(TVWS) can cause harmful interference to a digital TV receiver residing at the same pixel around the edge of the digital TV service coverage for the case with a changed propagation environment. In order to solve this problem, we propose a method to allocate the resource of a hybrid WSD based on TVWS geo-location DB with spectrum sensing. Using the received power of digital TV signal through the spectrum sensing, a hybrid WSD can calculate the maximum permitted EIRP based on location probability. Based on the accurate allocation method proposed in this paper, it is possible to satisfy the Korean TVWS regulations and to eliminate the harmful interference to TV receivers nearby the hybrid WSD.

• Journal of the Korean Institute of Educational Facilities
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• v.16 no.4
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• pp.79-88
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• 2009

To enhance the administrational efficiency and for university facility and space management to be public, this research suggests a competent and an objective evaluation system and index. The study will assist national and university finances to contribute towards advanced education. Furthermore, figure out the space management condition of national university by utilizing the evaluation system, and through that suggesting efficient special management method. According to the result of this study, evaluation system for university facility can be widely divided into seven categories; system preparation, members conference, propriety of space allocation, propriety of management system, space use ratio, time control of space use, imposition index of surplus use. Based on these subdivisions, the space management category contains 19 evaluation items and the marking system allows perfect score of 100 points. In result of examining space management condition using the evaluation system, space management was well enforced in research focused university group where as in education centered university group, it shows relatively low enforcement. It also illustrated that efforts of evaluation items were required in categories of imposition index of surplus use and special use ratio in order for efficient space management.

• Journal of the Korean Geographical Society
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• v.46 no.3
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• pp.366-381
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• 2011

A competitive location problem in discrete space is computationally difficult to solve in general because of its combinatorial feature. In this paper, we address an alternative method for solving competitive location problems in discrete space, particularly employing deterministic allocation. The key point of the suggested method is to reducing the number of predefined potential facility sites associated with the size of problem by utilizing geometric concepts. The suggested method was applied to the existing broadband marketplace with increasing competition as an application. Specifically, we compared computational results and spatial configurations of two different sized problems: the problem with the original potential sites over the study area and the problem with the reduced potential sites extracted by a GIS-based geometric algorithm. The results show that the competitive location model with the reduced potential sites can be solved more efficiently, while both problems presented the same optimal locations maximizing customer capture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.564-582
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• 2015

This paper proposes a novel swarm intelligence optimization method which integrates bacterial foraging optimization (BFO) with quantum computing, called quantum bacterial foraging optimization (QBFO) algorithm. In QBFO, a multi-qubit which can represent a linear superposition of states in search space probabilistically is used to represent a bacterium, so that the quantum bacteria representation has a better characteristic of population diversity. A quantum rotation gate is designed to simulate the chemotactic step for the sake of driving the bacteria toward better solutions. Several tests are conducted based on benchmark functions including multi-peak function to evaluate optimization performance of the proposed algorithm. Numerical results show that the proposed QBFO has more powerful properties in terms of convergence rate, stability and the ability of searching for the global optimal solution than the original BFO and quantum genetic algorithm. Furthermore, we examine the employment of our proposed QBFO for cognitive radio spectrum allocation. The results indicate that the proposed QBFO based spectrum allocation scheme achieves high efficiency of spectrum usage and improves the transmission performance of secondary users, as compared to color sensitive graph coloring algorithm and quantum genetic algorithm.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.693-703
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• 2005

Given the local traders with pattern-based multi-predictors of stock prices, we study a method of dynamic asset allocation to maximize the trading performance. To optimize the proportion of asset allocated to each recommendation of the predictors, we design an asset allocation strategy called meta policy in the reinforcement teaming framework. We utilize both the information of each predictor's recommendations and the ratio of the stock fund over the total asset to efficiently describe the state space. The experimental results on Korean stock market show that the trading system with the proposed meta policy outperforms other systems with fixed asset allocation methods. This means that reinforcement learning can bring synergy effects to the decision making problem through exploiting supervised-learned predictors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4835-4855
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• 2015

TV white space (TVWS) is showing promise to become the first widespread practical application of cognitive technology. In fact, regulators worldwide are beginning to allow access to the TV band for secondary users, on the provision that they access the geolocation database. Device-to-device (D2D) can improve the spectrum efficiency, but large-scale D2D communications that underlie TVWS may generate undesirable interference to TV receivers and cause severe mutual interference. In this paper, we use an established geolocation database to investigate the power allocation problem, in order to maximize the total sum throughput of D2D links in TVWS while guaranteeing the quality-of-service (QoS) requirement for both D2D links and TV receivers. Firstly, we formulate an optimization problem based on the system model, which is nonconvex and intractable. Secondly, we use an effective approach to convert the original problem into a series of convex problems and we solve these problems using interior point methods that have polynomial computational complexity. Additionally, we propose an iterative algorithm based on the barrier method to locate the optimal solution. Simulation results show that the proposed algorithm has strong performance with high approximation accuracy for both small and large dimensional problems, and it is superior to both the active set algorithm and genetic algorithm.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.596-608
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• 2004

A lot of work has been done to reduce disk access time in I/O intensive systems, which store and handle massive amount of data, by distributing data across multiple disks and accessing them in parallel. Most of the previous work has focused on an efficient mapping from a grid cell to a disk number on the assumption that data space is regular grid-like partitioned. Although we can achieve good performance for low-dimensional data by grid-like partitioning, its performance becomes degenerate as grows the dimension of data even with a good disk allocation scheme. This comes from the fact that they partition entire data space equally regardless of distribution ratio of data objects. Most of the data in high-dimensional space exist around the surface of space. For that reason, we propose a new declustering algorithm based on the partitioning scheme which partition data space from the surface. With an unbalanced partitioning scheme, several experimental results show that we can remarkably reduce the number of data blocks touched by a query as grows the dimension of data and a query size. In this paper, we propose disk allocation schemes based on the layout of the resultant data blocks after partitioning. To show the performance of the proposed algorithm, we have performed several experiments with different dimensional data and for a wide range of number of disks. Our proposed disk allocation method gives a performance within 10 additive disk accesses compared with strictly optimal allocation scheme. We compared our algorithm with Kronecker sequence based declustering algorithm, which is reported to be the best among the grid partition and mapping function based declustering algorithms. We can improve declustering performance up to 14 times as grows dimension of data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.551-556
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• 2018

A lot of hardwares are allocated on the satellite to perform the attitude control. Sun sensor is very important hardware to acquire the initial attitude after separation from launcher and to maintain the safety attitude from the satellite anomaly operation. So the allocation of the sun sensor to acquire the field of view and the attitude control design using it, are critical work in the beginning of development. Number of Sun sensor for GEO-KOMPSAT2 is reduced with respect to COMS due to star tracker usage. The additional sun sensor using COMS heritage is considered. In this paper, it is described the analysis and the results on the method for the safety improvement which is to enlarge the field of view and to consider the harness connection of P/R-side of the sun sensor.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.19-29
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• 2017

When a fixed-sized memory allocation method is used for sparse volume data, a considerable memory space is in general wasted, which becomes more serious for a large volume of high resolution. In this paper, in order to reduce such unnecessary memory consumption, we propose a volume representation method to store mostly voxels that represent valid information rather than all voxels in a fixed volume space. Then our method is compared with the conventional static memory allocation method, an octree-based representation, and a voxel hashing method in terms of memory usage and computation speed. In particular, we compare the proposed method and the voxel hashing method with respect to implementation of the GPU-based Marching Cubes algorithm.