• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.22-31
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• 2012

A Smartphone is an intelligent device combined mobile phone and pc's support functions, and can perform multiple functions to satisfy the demands of users. It has excellent processing power and communication modules(DMB, Wi-Fi, Bluetooth, NFC etc) to carry out the demands of users. But continuous using of battery power on processor and equipped modules causes acceleration of battery consumption. This means that effective power management in devices like smartphone is important. Therefore, the management of power consumption on system execution and communication module is a serious issue in this field of study. In this paper, we would like to propose a communication module selection algorithm based on energy consumption parameter of each communication module and data transfer time. Our scheme automatically select appropriate communication system to reduce high energy consumption on bluetooth sleep mode so that this scheme is more efficient and effective thus improving user convenience in longer usage time. Experimental results showed the 20% energy saving.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.103-104
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• 2015

Solar energy has proven to be a potential clean energy source to help offset the large consumption of fossil. Nowadays, many research projects aim to enhance photovoltaic (PV) system performance and functionality. This research focuses on integrating self-monitor capability into dc-dc converters that control PV panels to detect a fault in series-connected PV cells, called hot spotting. A detection method using ac parameter characterization is proposed and its operation is examined through simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1225-1234
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• 2013

According to the importance of greenhouse gas emissions, it grows day by day, the goverment is promoting to prepare the specific policy implementation to enhance building energy-saving design standars as the development agenda. In this study, the statistical analysis was performed by Descriptive statistics, Regression analysis, and Hypothesis testing to collect to generate and storage energy usage data in real time to settle parameter setting to affect energy consumption under energy-guzzling apartment not single building. This study is expected to be utilized as the basis for the optimum energy-saving design of the future of the building or facility energy costs rise and the demand for energy-efficient and stable management.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.184-197
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• 2015

This paper builds on a recent method, chain routing with even energy consumption (CREEC), for designing a wireless sensor network with chain topology and for scheduling the communication to ensure even average energy consumption in the network. In here a new suboptimal design is proposed and compared with the CREEC design. The chain topology in CREEC is reconfigured after each group of n converge-casts with the goal of making the energy consumption along the new paths between the nodes in the chain as even as possible. The new method described in this paper designs a single near-optimal Hamiltonian circuit, used to obtain multiple chains having only the terminal nodes different at different converge-casts. The advantage of the new scheme is that for the whole life of the network most of the communication takes place between same pairs of nodes, therefore keeping topology reconfigurations at a minimum. The optimal scheduling of the communication between the network and base station in order to maximize network lifetime, given the chosen minimum length circuit, becomes a simple linear programming problem which needs to be solved only once, at the initialization stage. The maximum lifetime obtained when using any combination of chains is shown to be upper bounded by the solution of a suitable linear programming problem. The upper bounds show that the proposed method provides near-optimal solutions for several wireless sensor network parameter sets.

• Smart Structures and Systems
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• v.33 no.6
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• pp.465-482
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• 2024

In this paper, a robust wireless sensor network configuration design method is proposed to develop the optimal configuration under the consideration of sensor failure and energy consumption. A malfunctioned sensor in a wireless sensor network may lead to data transmission failure of the entire sensing cluster, inducing severe deterioration in system identification performance. The proposed method determines a wireless sensor network configuration that is robust against sensor failure. By utilizing Bayesian inference, we introduce a robust indicator to evaluate the impact on estimation accuracy of sensor configurations with various malfunctioned sensors. Moreover, a network formation strategy is proposed to optimize the energy efficiency of the wireless sensor network configuration. Therefore, the resultant robust wireless sensor network configuration can operate with the minimum energy consumption while the measurement information of the sensor network with malfunctioned sensors can be guaranteed. The proposed method is illustrated by designing the robust wireless sensor network configurations of a truss model and a bridge model.

• Current Optics and Photonics
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• v.8 no.4
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• pp.399-405
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• 2024

In this paper, an optical modulator based on monolayer graphene and triple-layer black phosphorus (BP) heterojunction in the optical communication band range is designed. The influences of geometric parameters, chemical potential, BP orientation and dispersion on the fundamental mode of this modulator were determined in detail by the finite-difference time-domain (FDTD) method. Using appropriate geometric parameter settings, the extinction ratio of this proposed modulator is 0.166 dB, while the modulator with a working length of 3 ㎛ can realize a 0.498 dB modulation depth. The 3-dB bandwidth of this modulator could achieve up to 2.65 GHz with 27.23 fJ/bit energy consumption. The extinction ratio and bandwidth of the proposed modulator increased by 66% and 120.83%, respectively, compared to the monolayer graphene-based ridge-type waveguide modulator. Energy consumption was reduced by 97.28%, compared to a double-layer graphene-based modulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2504-2526
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• 2016

Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.854-857
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• 2008

Wireless sensor consists of an internal power source which has limited life time. Several MAC protocols have exploited scheduled sleep/listen cycles to conserve energy in sensor networks. Duty cycle is a user-adjustable parameter in low duty cycle MAC protocols, which determines the length of the sleep period in a frame. The sire of duty cycle has direct effect on the Performance of MAC Protocols. In this Paper, we simulated TEEM (A Traffic Aware, Energy Efficient MAC) and S-MAC in NS-2 with different duty cycle values and analyze how duty-cycle effects on the performance and energy consumption of both the protocols.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.161-167
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• 2009

The liquid solar air conditioning system is introduced as an alternative solution to control air condition and to save electrical energy consumption. The heat and mass transfer performances of dehumidifier/regenerator in liquid solar air conditioning system are influenced by air and desiccant condition. The application of this system, the thermal energy from the sun and inlet air are unable to control, but operation parameter of other components such as pump, fan and sensible cooling unit are able to control. The equilibrium point of heat and mass transfer are the liquid desiccant and inlet air conditions, where, the heat and mass are not transferred between the liquid desiccant and vapor air. By knowing equilibrium point of heat and mass transfer, the suitable optimal desiccant conditions for certain air condition are funded. This present experiment study is investigated the equilibrium point heat and mass transfer in various air and desiccant temperature. The benefit of equilibrium point heat and mass transfer will be helpful in choose and design proper component to optimize electrical energy consumption.

• Land and Housing Review
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• v.10 no.3
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.