• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2029-2046
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• 2016

Energy consumption is an important index in mobile ad hoc networks. Data packet transmission increases among nodes, particularly in big data communication. However, nodes may be unable to transmit data packets because of energy over-consumption. Consequently, information may be lost and network communication may block. While opportunistic network is a kind of mobile ad hoc networks, researchers do not focus on energy consumption in opportunistic network communication. This study proposed an effective sensor energy supply scheme that can be applied in opportunistic networks. This scheme considers nodes sensor requests and communication model. In this scheme, nodes do not only accomplish energy supply in communication, but also extend communication time in opportunistic networks. Compared with the Spray and Wait algorithm and the Binary Spray and Wait algorithm in simulations, the proposed scheme extends communication time, increases data packet transmission, and accomplishes energy supply among nodes.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• ETRI Journal
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• v.38 no.4
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• pp.735-745
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• 2016

The Paris agreement at the 21st Conference of the Parties (COP21) emphasizes the reduction of greenhouse gas emissions and increase in energy consumption in all areas. Thus, an important aspect is energy saving in buildings where the lighting is a major component of the electrical energy consumption. This paper proposes a building energy management system employing visible light communication (VLC) based on LED lighting. The proposed management system has key characteristics including personalization and localization by utilizing such VLC advantages as secure communication through light and location-information transmission. Considering the efficient implementation of an energy-consumption adjustment using LED luminaires, this paper adopts variable pulse position modulation (VPPM) as a VLC modulation scheme with simple controllability of the dimming level that is capable of providing a full dimming range. This paper analyzes the VPPM performances according to variable dimming for several schemes, and proposes a VPPM demodulation architecture based on dimming-factor acquisition, which can obtain an improved performance compared to a 2PPM-based scheme. In addition, the effect of a dimming-factor acquisition error is analyzed, and a frame format for minimizing this error effect is proposed.

• Journal of the Korean earth science society
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• v.39 no.5
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• pp.483-500
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• 2018

The purpose of this study was to explore what kinds of science communication are ongoing in formal and informal settings for learning about nuclear energy, which is very important issue domestically and internationally. The researchers collected and analyzed data from science textbooks at elementary and middle school levels, from exhibitions in Y informal hall that belongs to one nuclear power plant, and from 40 bestselling books about nuclear energy in order to explore the kind of science communication. The same process was used to explore Japanese case so that we could compare the results with Korean cases and draw implications for enhancing science communication about nuclear energy. The science communication of nuclear energy in Korea included implicit and indirect content espoused in science textbooks; two opposite views displayed in bestselling books, and positive aspects mainly displayed in exhibition of information hall in nuclear power plant. It is suggested that both direct and explicit science communication along with the neutral viewpoints including positive and negative ones be provided for the public to form a good understanding of nuclear energy.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.601-602
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• 2011

In wireless sensor networks, coverage problem is a fundamental issue that has attracted considerable attention in recent years. Most node scheduling patterns utilize the adjustable range of sensor to minimize the sensing energy consumption. However, a large source of consumption of communication energy of sensor is not strictly taken into account. In this paper, we introduce an energy-efficient pattern that is used to minimize the communication energy consumption of a sensor network. Calculations and extensive simulation are conducted to evaluate the efficiency of the new pattern comparing to existing ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2946-2962
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• 2017

An improved energy-efficient compressed network coding method is proposed for the data communication in the wireless sensor networks (WSNs). In the method, the compressed sensing and network coding are jointly used to improve the energy efficiency, and the two-hop neighbor information is employed to choose the next hop to further reduce the number of the transmissions. Moreover, a new packet format is designed to facilitate the intermediate node selection. To theoretically verify the efficiency of the proposed method, the expressions for the number of the transmissions and receptions are derived. Simulation results show that, the proposed method has higher energy efficiency compared with the available schemes, and it only requires a few packets to reconstruct measurements with reasonable quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5149-5167
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• 2017

Reducing energy consumption in a wireless video sensor network (WVSN) is a crucial problem because of the high video data volume and severe energy constraints of battery-powered WVSN nodes. In this paper, we present an adaptive dynamic resizing approach for a SRAM communication buffer in a WVSN node in order to reduce the energy consumption and thereby, to maximize the lifetime of the WVSN nodes. To reduce the power consumption of the communication part, which is typically the most energy-consuming component in the WVSN nodes, the radio needs to remain turned off during the data buffer-filling period as well as idle period. As the radio ON/OFF transition incurs extra energy consumption, we need to reduce the ON/OFF transition frequency, which requires a large-sized buffer. However, a large-sized SRAM buffer results in more energy consumption because SRAM power consumption is proportional to the memory size. We can dynamically adjust any active buffer memory size by utilizing a power-gating technique to reflect the optimal control on the buffer size. This paper aims at finding the optimal buffer size, based on the trade-off between the respective energy consumption ratios of the communication buffer and the radio part, respectively. We derive a formula showing the relationship between control variables, including active buffer size and total energy consumption, to mathematically determine the optimal buffer size for any given conditions to minimize total energy consumption. Simulation results show that the overall energy reduction, using our approach, is up to 40.48% (26.96% on average) compared to the conventional wireless communication scheme. In addition, the lifetime of the WVSN node has been extended by 22.17% on average, compared to the existing approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.585-588
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• 2019

Predictions of Energy Consumption for Industries gain an important place in energy management and control system, as there are dynamic and seasonal changes in the demand and supply of energy. This paper presents and discusses the predictive models for energy consumption of the steel industry. Data used includes lagging and leading current reactive power, lagging and leading current power factor, carbon dioxide (tCO2) emission and load type. In the test set, four statistical models are trained and evaluated: (a) Linear regression (LR), (b) Support Vector Machine with radial kernel (SVM RBF), (c) Gradient Boosting Machine (GBM), (d) random forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to measure the prediction efficiency of regression designs. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Journal of Ocean Engineering and Technology
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• v.32 no.2
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• pp.143-150
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• 2018

In this study, we designed and developed an underwater LED communication system composed of an LED and a photo sensor. In addition, we experimented with video data transmission in a water tank. Two communication modules were installed in the 3 m water tank, and the image data transmission test was successfully performed at a rate of 20 frames per second(FPS), image resolution of $480{\times}272$, and data communication speed of 4 Mbps.

• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.