• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.107-114
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• 2018

Recently, various wearable personal devices such as a smart watch have been developed and these personal devices are being miniaturized. The user desires to receive new services from personal devices as well as services that have been received from personal computers, anytime and anywhere. However, miniaturization of devices involves constraints on resources such as limited input and output and insufficient power. In order to solve these resource constraints, this paper proposes a resource collaboration system which provides a service by composing sharable resources in the resource sharing environment like IoT. the paper also propose a method to infer and recommend user-customized resources among various sharable resources. For this purpose, the paper defines an ontology for resource inference. This paper also classifies users behavior types based on a user model and then uses them for resource recommendation. The paper implements the proposed method as a prototype system on a personal device with limited resources developed for resource collaboration and shows the effectiveness of the proposed method by evaluating user satisfaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.484-503
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• 2016

Mobile cloud computing has recently become a new paradigm for the utilization of a variety of shared mobile resources via wireless network environments. However, due to the inherent characteristics of mobile devices, a limited battery life, and a network access requirement, it is necessary for mobile servers to provide a dynamic approach for managing mobile resources efficiently in mobile cloud computing environments. Since on-demand job requests occur frequently and the number of mobile devices is drastically increased in mobile cloud computing environments, a different mobile resource management method is required to maximize the computational power. In this paper, we therefore propose a cooperative, mobile resource sharing method that considers both the inherent properties and the number of mobile devices in mobile cloud environments. The proposed method is composed of four main components: mobile resource monitor, job handler, resource handler, and results consolidator. In contrast with conventional mobile cloud computing, each mobile device under the proposed method can be either a service consumer or a service provider in the cloud. Even though each device is resource-poor when a job is processed independently, the computational power is dramatically increased under the proposed method, as the devices cooperate simultaneously for a job. Therefore, the mobile computing power throughput is dynamically increased, while the computation time for a given job is reduced. We conduct case-based experiments to validate the proposed method, whereby the feasibility of the method for the purpose of cooperative computation is shown.

• KEPCO Journal on Electric Power and Energy
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• 제2권4호
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• pp.569-575
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• 2016

In this paper, we propose a method to develop a static equivalent model of an inverter-based distributed energy resource (DER), where the model is used for a steady-state fault analysis of a power grid. First, we introduce the characteristics of an inverter-based DER as well as its general configuration. Then, we derive the equivalent model of the DER on the basis of the characteristics. Last, the performance of the proposed method is proven by the results of computer simulations.

• 환경영향평가
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• 제7권2호
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• pp.145-152
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• 1998

The first Environmental Impact Assessment(EIA) in Korea was carried out for Electric Power resource development. This study includes of the method and procedure of pre-Environmental investigation and EIA for Electric Power resource development. Through the analysis of these we make some conclusions for the improvemental and effective method of impact prediction, the environmentally sound and sustainable development of the earth(ESSD) and the collection of public opinions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1638-1653
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• 2014

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1083-1087
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• 1997

Every effort is now being exerted in industrialized and developing countries to reduce emission of greenhouse gases from electric power sector. In this paper, we provide supply-side resource mix strategies in the long-term generation expansion planning under the expected greenhouse gas regulations. Under the environmental regulations, we explore the least-cost generation expansion plan of Korea and determine the composition of future resource mixes. Our analysis is performed on the basis of the revised WASP package which can evaluate emission of carbon dioxide from each power plant. The evaluation process of carbon dioxide emissions, which can consider the efficiency and operating conditions of each generator simultaneously, has been incorporated into the probabilistic production cost simulation module of WASP.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.1-4
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• 2022

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(2)
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• pp.121-124
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• 2001

This paper proposed resource allocation algorithm for the minimum switching activity of functional unit in high level synthesis process as like DSP which is circuit to give many functional unit. The resource allocation method after scheduling use the power function calculating average hamming distance and switching activity of the between two input. First of all, the switching activity is calculated by the input value after calculating the average hamming distance between operation. In this paper, the proposed method though high If level simulation find switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To use the switching activity find the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step. As the existing method, the execution time can be fast according to use the number of operator and max control step. And it is the reduction effect from 6% to 8%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.987-992
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• 2016

This study introduces an example environment where wireless devices are mobile, devices use dynamic voltage scaling, devices and tasks are heterogeneous, tasks have deadline, and the computation and communication power is dynamically changed for energy saving. For this type of environment, the efficient system-level energy management and resource management for task completion can be an essential part of the operation and design of such systems. Therefore, the resources are assigned to tasks and the tasks may be scheduled to maximize a goal which is to minimize energy usage while trying to complete as many tasks as possible by their deadlines. This paper also introduces mobility of nodes and variable transmission power for communication which complicates the resource management/task scheduling problem further.