• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.12
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• pp.1090-1097
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• 2000

Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

• Knowledge Management Research
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• v.9 no.4
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• pp.51-63
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• 2008

Effective energy consumption now becomes one of the area of knowledge management which potentially gives global impact. It is considerable for the energy management to optimize the usage of energy, rather than decreasing energy consumption at any cases. To resolve these challenges, an intelligent and personalized system which helps the individuals control their own behaviors in an optimal and timely manner is needed. So far, however, since the legacy energy management systems are nation-wide or organizational, individual-level energy management is nearly impossible. Moreover, most estimating methods of energy consumption are based on forecasting techniques which tend to risky or analysis models which may not be provided in a timely manner. Hence, the purpose of this paper is to propose a novel individual-level energy management system which aims to realize timely and personalized energy management based on context-aware computing approach. To do so, an index model for energy consumption is proposed with a corresponding service framework.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1618-1637
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• 2014

Clustering wireless sensor network is an efficient way to reduce the energy consumption of individual nodes in a cluster. In clustering, multihop routing techniques increase the load of the Cluster head near the sink. This unbalanced load on the Cluster head increases its energy consumption, thereby Cluster heads die faster and create an energy hole problem. In this paper, we propose an Energy Balancing Cluster Head (EBCH) in wireless sensor network. At First, we balance the intra cluster load among the cluster heads, which results in nonuniform distribution of nodes over an unequal cluster size. The load received by the Cluster head in the cluster distributes their traffic towards direct and multihop transmission based on the load distribution ratio. Also, we balance the energy consumption among the cluster heads to design an optimum load distribution ratio. Simulation result shows that this approach guarantees to increase the network lifetime, thereby balancing cluster head energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3683-3703
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• 2018

Wireless sensor networks (WSNs) consist of set of sensor nodes. These sensor nodes are deployed in unattended area which are able to sense, process and transmit data to the base station (BS). One of the primary issues of WSN is energy efficiency. In many existing clustering approaches, initial centroids of cluster heads (CHs) are chosen randomly and they form unbalanced clusters, results more energy consumption. In this paper, an energy efficient clustering protocol to prevent unbalanced clusters based on firefly and midpoint algorithms called EEC-FM has been proposed, where midpoint algorithm is used for initial centroid of CHs selection and firefly is used for cluster formation. Using residual energy and Euclidean distance as the parameters for appropriate cluster formation of the proposed approach produces balanced clusters to eventually balance the load of CHs and improve the network lifetime. Simulation result shows that the proposed method outperforms LEACH-B, BPK-means, Park's approach, Mk-means, and EECPK-means with respect to balancing of clusters, energy efficiency and network lifetime parameters. Simulation result also demonstrate that the proposed approach, EEC-FM protocol is 45% better than LEACH-B, 17.8% better than BPK-means protocol, 12.5% better than Park's approach, 9.1% better than Mk-means, and 5.8% better than EECPK-means protocol with respect to the parameter half energy consumption (HEC).

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1081-1085
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• 2009

We have already developed EMI reducing techniques using lossless compression by vertically differential EMI suppression method (VDE[1]). It applies lossless modulo reduction and data bit mapping optimization for low voltage differential signaling (LVDS) transmission lines, that reduces the probability of transient bit and EMI by 12 dB [6][7]. We also improved and optimized the VDE for low power LCD interface. With this modified VDE algorithm[8], the developed FPGA was measured the reduction of the power consumption of LCD circuit by more than 15 % compared to the conventional methods in the case of 14-in LCD with SXGA resolution. The VDE algorithm is based on the total image systematic approach. In the VDE method, the present image signals are subtracted for the 1H delayed image signals and transferred to a column driver through a PCB. As the vertical correlations for image signals are very high, we expected that most of the vertically subtracted image signals remain 0 level and transient cycles become very long. As a result, the power consumption and EMI are extremely reduced for the transferred image signals on a PCB. In this paper, we discussed our proposed method by emphasizing the fact that systematic approach are important based on not only display point of view but also total system point of view.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6152-6168
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• 2017

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.

• ETRI Journal
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• v.41 no.4
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• pp.452-464
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• 2019

The use of wireless body area networks (WBANs) in healthcare applications has made it convenient to monitor both health personnel and patient status continuously in real time through wearable wireless sensor nodes. However, the heterogeneous and complex network structure of WBANs has some disadvantages in terms of control and management. The software-defined network (SDN) approach is a promising technology that defines a new design and management approach for network communications. In order to create more flexible and dynamic network structures in WBANs, this study uses the SDN approach. For this, a WBAN architecture based on the SDN approach with a new energy-aware routing algorithm for healthcare architecture is proposed. To develop a more flexible architecture, a controller that manages all HUBs is designed. The proposed architecture is modeled using the Riverbed Modeler software for performance analysis. The simulation results show that the SDN-based structure meets the service quality requirements and shows superior performance in terms of energy consumption, throughput, successful transmission rate, and delay parameters according to the traditional routing approach.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.1-31
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• 2010

One of the prominent challenges of e-government identified in developing countries is low level of ICT literacy and skills of e-government users. For those countries at the nascent stage of e-government development, it is crucial to identify and provide e-skills needed from the demand side. However, prior research has mostly focused on the supply side of e-skills, ignoring the consumption side of e-skills. In addition, no user centric approach for e-skills identification and development for e-service consumption, with respect to the stages of e-government development, have been proposed and validated. The purpose of this article is thus to: 1) Identify skills required for e-services utilization by all participants-citizens, public, and private sector employees-involved in G2C, G2B, and G2E e-government relationships respectively; assuming they are consumers of e-government and to 2) Propose and validate an user-centric approach for e-skills identification and development based on stages of e-government utilizing the Delphi method. As a result of the study, a comprehensive list of e-skills (N = 81) was generated. We found that e-skills required for e-service consumption are not merely technical; they include a wide variety of related skills that can be applied to enhancing e-skills. Therefore, the findings can serve as a standard curriculum for training and educating both citizens and government employees in developing countries. Moreover, the findings of this research may also facilitate international organizations in indentifying and measuring citizens' readiness for e-government in terms of e-skills.