• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.137-146
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• 2011

In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.863-868
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• 2020

Co Self-Powered Neutron Detector (SPND) is confronted with the problem of material consumption, which causes the response current can neither reflect the change of neutron flux in time nor be proportional to the neutron flux. In this paper, a deconvolution-based method is established to solve this problem. First of all, a step signal of neutron flux is taken as an example to analyze its performance. When the material consumption of Co SPND is 10%, after compensation, the response current can be in correspondence of neutron flux. Finally, the effects of this model in different Signal-to-Noise Ratio are analyzed, which fully confirms the truth of its excellent performance for compensating Co SPND's signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.819-837
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• 2014

Data centers, which implement cloud service, have been faced up with quick growth of energy consumption and low efficiency of energy. 60GHz wireless communication technology, as a new option to data centers, can provide feasible approach to alleviate the problems. Aiming at energy optimization in 60GHz wireless data centers (WDCs), we investigate virtualization technology to assign virtual resources to minimum number of servers, and turn off other servers or adjust them to the state of low power. By comprehensive analysis of wireless data centers, we model virtual network and physical network in WDCs firstly, and propose Virtual Resource Mapping Packing Algorithm (VRMPA) to solve energy management problems. According to VRMPA, we adopt packing algorithm and sort physical resource only once, which improves efficiency of virtual resource allocation. Simulation results show that, under the condition of guaranteeing network load, VPMPA algorithm can achieve better virtual request acceptance rate and higher utilization rate of energy consumption.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.9-13
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• 2014

The performance of large scale software applications has been automatically increasing for last few decades under the influence of Moore's law - the number of transistors on a microprocessor roughly doubled every eighteen months. However, on-chip transistors limitations and heating issues led to the emergence of multicore processors. The energy efficient ARM based System-on-Chip (SoC) processors are being considered for future high performance computing systems. In this paper, we present a case study of two widely used parallel programming models i.e. MPI and MapReduce on distributed memory cluster of ARM SoC development boards. The case study application, Black-Scholes option pricing equation, was parallelized and evaluated in terms of power consumption and throughput. The results show that the Hadoop implementation has low instantaneous power consumption that of MPI, but MPI outperforms Hadoop implementation by a factor of 1.46 in terms of total power consumption to execution time ratio.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.769-776
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• 2023

In this paper, we designed an MLSA(Match-line Sense Amplifier) for low-power CAM(Content Addressable Memory). By using the MLSA and precharge controller, we reduced power consumption during CAM operation by employing a selective match-line charging technique to mitigate power consumption caused by mismatch. Additionally, we further reduced power consumption due to leakage current by terminating precharge early when a mismatch occurs during the search operation. The designed circuit exhibited superior performance compared to the existing circuits, with a reduction of 6.92% and 23.30% in power consumption and propagation delay time, respectively. Moreover, it demonstrated a significant decrease of 29.92% and 52.31% in product-delay-product (PDP) and energy-delay-product (EDP). The proposed circuit was validated using SPECTRE simulation with TSMC 65nm CMOS process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1113-1132
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• 2011

In wireless sensor networks (WSNs), most energy saving asynchronous MAC protocols are custom tailored for unicast communications only. However, broadcast protocols are very commonly used in WSNs for a variety of functionalities, such as gathering network topology information, event monitoring and query processing. In this paper, we propose a novel low-power asynchronous broadcast MAC protocol called Alarm Broadcast (A-CAST). A-CAST employs the strobe preamble that specifies the residual waiting time for the following data transmission. Each receiver goes back to sleep upon hearing the strobe preamble for the residual time duration, to conserve energy and to wake up just before data transmission starts. We compute the energy consumption of A-CAST via rigorous mathematical analysis. The analytic results show that A-CAST outperforms B-CAST, a simple broadcast extension of the well-known B-MAC. We also implement A-CAST on sensor motes and evaluated its performance through real experiments. Our experimental results show that A-CAST reduces the energy consumption by up to 222% compared to the previously proposed protocols.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3066-3079
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• 2016

Recent years have witnessed a dramatic increase in topology research of wireless sensor networks (WSNs) where both energy consumption and survivability need careful consideration. To balance energy consumption and ensure survivability against both random failures and deliberate attacks, we resort to complex network theory and propose an energy-aware preferential attachment (EPA) model to generate a robust topology for WSNs. In the proposed model, by taking the transmission range and energy consumption of the sensor nodes into account, we combine the characters of Erdős -Rényi (ER) model and Barabasi-Albert (BA) model in this new model and introduce tunable coefficients for balancing connectivity, energy consumption, and survivability. The correctness of our theoretic analysis is verified by simulation results. We find that the topology of WSNs built by EPA model is asymptotically power-law and can have different characters in connectivity, energy consumption, and survivability by using different coefficients. This model can significantly improve energy efficiency as well as enhance network survivability by changing coefficients according to the requirement of the real environment where WSNs deployed and therefore lead to a crucial improvement of network performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.4
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• pp.42-48
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• 2014

Sewage treatment facilities can purify sewage enough to be send to river or sea water, that discharged from human life and industrial activities. In the sewage treatment process, we can get large amount of by-product energy resources and materials such as heat of sewage, digester gas and purified water etc., it can be utilized by applying various technologies thereby we can reduce energy consumption in the process. In this paper, it was analyzed using the data collected from the operational case study for the energy savings effect that can be obtained when using the digester gas, one of the by-product materials of sewage treatment process, for electric power generation. Cost of 623million won is an annual reduction of 4,032MWh corresponding 9% of the annual electricity consumption of the sewage treatment plant, such an alternative power generation using digester gas was proposed in this paper has been verified the feasibility of the proposed reduction of energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2003-2021
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• 2020

Today's computer systems are widely integrated with CPU and GPU to achieve considerable performance, but energy consumption of such system directly affects operational cost, maintainability and environmental problem, which has been aroused wide concern by researchers, computer architects, and developers. To cope with energy problem, we propose a task-scheduling framework to reduce energy under performance constraint by rationally allocating the tasks across the CPU and GPU. The framework first collects the estimated energy consumption of programs and performance information. Next, we use above information to formalize the scheduling problem as the 0-1 knapsack problem. Then, we elaborate our experiment on typical platform to verify proposed scheduling framework. The experimental results show that our proposed algorithm saves 14.97% energy compared with that of the time-oriented policy and yields 37.23% performance improvement than that of energy-oriented scheme on average.

• Solar Energy
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• v.19 no.3
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• pp.63-73
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• 1999

Ice storage systems are used to shift the peak load in day time into night time in summer. This paper describes a system simulation of partial ice storage system composed of an encapsulated ice storage tank, a screw compressor chiller, a heat exchanger, and a brine pump. For the system simulation, a one-dimensional model of ice storage tank is developed and validated by comparison with the performance data from measurements of an ice storage tank installed at a building. The control strategies considered in this study are chiller priority and storage priority being used commercially. The system is simulated with design cooling load of 600 RT peak load in design day and with off-design day cooling load, and the electric energy costs of the two control strategies for the same system size are compared. As a result of calculation, the energy consumption in a week for storage priority is higher than that for chiller priority control. However due to lower cost of night electric charge rate, energy cost for storage priority control is lower than chiller priority.