• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2350-2364
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• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• International Commerce and Information Review
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• v.7 no.4
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• pp.77-94
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• 2005

The successful knowledge and information based companies facilitate to restructure the industry and strengthen the national competitiveness in the future. The advent of information age provides us new challenge because the information breakthrough can play a pivotal role in terms of knowledge transfer in the human resource management. This research focuses on best practices of human management and contrasting the human resource strategy of Japanese and American firms respectively, Based on this, we suggest the strategic alternatives of the described HR problems as well as the way of effective human resource management for Korean venture firms. We have reviewed the previous international and domestic literatures in details to understand HR liabilities of newness of venture firms in terms of the population ecology. The objective of this research is to solve the HR problems that Korean firms faced with.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.862-869
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• 2013

In order to support a cell-independent traffic asymmetry, the conventional TDD system cannot avoid crossed time slot (CTS) interference. Moreover, the TDD/FDD hierarchical overlay cellular systems is taken into account as a generally accepted cell model in a heterogeneous radio environment. In this paper, we propose an interference resolving radio resource allocation technique in a TDD-OFDMA cellular system that overlays a FDD-CDMA cell. In our proposed scheme, we exploit under-used FDD-CDMA uplink resource by TDD mobile abiding by a region based time slot(TS) allocation which in turn mitigates CTS interference considerably. It is demonstrated that combined with under-used resource utilization scheme based on mobile's location, the proposed technique can reduce CTS interference considerably and support the asymmetric traffic in TDD system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.331-337
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• 2004

Target motion analysis with a sonar system in general uses a regular sampling time and thus obtains regular target information regardless of the target maneuver status. This often results in overconsumption of the limited sonar resources. We propose two methods of the IMM(interacting Multiple Model) PDAF algorithm for sonar resource management to improve target motion analysis performance and to save sonar resources in this paper. In the first method, two different process noise covariance which are used as mode sets are combined based on probability. In the second method, resource time which are processed from two mode sets is calculated based on probability and then considered as update time at next step. Performance of the proposed algorithms are compared with the other algorithms by a series of Monte Carlo simulation.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.558-563
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• 2005

This paper presents a GA-based optimal algorithm for a resource leveling model that levels the resources of a set of non-critical activities experiencing conflicts simultaneously up to an assumed level of resource rates specified by the planner using a pair-wise comparison of the activities being considered. A parameter called the future float is adopted and applied as an indicator for assigning leveling priorities to the sets of activities experiencing conflicts. A construction project network example was worked out to demonstrate the performance of the proposed method. The histogram obtained using the algorithm proposed was shown to be the same as, or very close to that produced by the existing resource leveling method based on the least total float rule, which shifts non-critical activities individually.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1100-1110
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• 2003

Design and implementation of remote procedure cail (RPC) resource service system based on the XML considering the request delegation between the servers are described for the resource application and efficient processing of distributed environment. For this purpose, the request information about several server, which would be used by client, is encoded into XML document based on XML-DOM and transferred to server. Server classifies the client requests using objects which can deal with the XMLL-DOM. For the request delegation between the servers, server saves the request result of client in XMLL-DOM structure without replying it immediately, and makes the client request delegated to another server in XML-DOM's request information. In addition, the resource repository are managed for resource transparency of distributed environment. As a result, resource application and processing efficiency are improved by reduction of response time caused by integration of RPC and XML-RPC services and request delegation between the servers. Extension of asynchronous and average blocking time of client were reduced and information of resource which can be used by client was offered.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.29-35
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• 2015

The heterogeneous LTE (Long Term Evolution)-Advanced networks comprising a macrocell and femtocells can provide an efficient solution not only to extend macrocell coverage but also to deal with packet traffics increasing explosively within macrocells. An efficient resource management scheme is necessary to maintain the QoS (Quality of Service) of mobile multimedia services because the LTE-Advanced system should support not only voice but also mobile applications such as data, image and video. This paper proposes a resource management scheme to guarantee QoS continuity of multimedia services and to maximize the resource utilization in OFDMA (Orthogonal Frequency Division Multiple Access) based LTE-Advanced systems. This scheme divides the resources into several service blocks and allocates those resources based on the competition between macrocell and femtocell. Simulation results show that it provides better performances than the conventional one in respect of handover failure rate and blocking rate.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.278-289
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• 2013

Up-to-date market dynamics and intense competition have forced a production system to be more widely distributed and decentralized than ever, and the production system itself can be regarded as a collaborative network of autonomous production resources in which the responsibility of decision making is also decentralized into individual autonomous entities. The conventional resource management models, however, are not suitable for the distributed and decentralized environment because of their centralized nature. In this paper, an agent-based resource management model is proposed. The proposed model applies employment relation-driven fractal organization (FrOrg) into organizational model for distributed production resources and presents a resource management framework based on employment contracts. The fractal organization is a structured association in which a self-similar pattern recursively appears, and employment relations between production resources are recursively constructed throughout the entire production system.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.