• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.201-207
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• 2012

Currently, NAND Flash memory has been widely used in consumer storage devices due to its non-volatility, stability, economical feasibility, low power usage, durability, and high density. However, a high capacity of NAND flash memory causes the high power consumption and the low performance. In the convention memory research, a hierarchical filter mechanism can archive an effective performance improvement in terms of the power consumption. In order to attain the best filter structure for NAND flash memory, we selected a direct-mapped filter, a victim filter, a fully associative filter and a 4-way set associative filter for comparison in the performance analysis. According to the results of the simulation, the fully associative filter buffer with a 128byte fetching size can obtain the bet performance compared to another filter structures, and it can reduce the energy*delay product(EDP) by about 93% compared to the conventional NAND Flash memory.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.513-520
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• 2016

Korea's energy consumption has been constantly increasing. Final energy consumption was increased by an annual average of 2.9% compared to 2010. The consumption of all energy sources except for its oil was increased during the same time. While electric demand has increased coal consumption increased rapidly. Therefore, calorfic value and carbon emission factor development can improve the quality of Korea's greenhouse gas inventory. Calorific value is the amount of heat generated while burning coal. Caloric value is one of the most important factors in the development of carbon emission factors. Calorific value is used as the basis for the analysis of the various energy statistics. This study has calculated the other bituminous coal and coking coal's calorfic value by the data received from domestic coal-fired power plants and steel manufacturer. Calorofic value's trend analysis period is the year of 2010~2014. Through analyzing the carbon content it was calculated the carbon emission factor. The bituminous coal and coking coal's uncertainty analysis was performed using a Monte Carlo simulation.

• The KIPS Transactions:PartC
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• v.14C no.2
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• pp.185-190
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• 2007

The efficient node energy utilization is one of important performance factors in wireless sensor networks because sensor nodes operate with limited battery power. To extend the lifetime of the wireless sensor networks, maintaining balanced power consumption between sensor nodes is more important than reducing each energy consumption of the sensor node in the network. In this paper, we proposed a cluster formation algorithm to extend the lifetime of the networks and to maintain a balanced energy consumption of nodes. To obtain it, we add a tiny slot in a round frame, which enables to exchange the residual energy messages between the base station (BS). cluster heads, and nodes. The performance of the proposed protocol has been examined and evaluated with the NS 2 simulator. As a result of simulation, we have confirmed that our proposed algorithm show the better performance in terms of lifetime than LEACH. Consequently, our proposed protocol can effectively extend the network lifetime without other critical overhead and performance degradation.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.715-724
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• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.214-220
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• 2011

This paper studies about the assessment of thermal performance between wet ondol system and electric ondol system. Electrical ondol systems shows faster warm-up time, higher floor surface temperature distribution and lower power consumption than wet ondol system. However, if we provide heat regularly wet ondol system which has more heat capacity shows greater thermal storage than electric ondol system. Therefore, we could conclude that wet ondol system which keeps temperature regularly by the thermal storage show better energy-efficiency in case of using the central heating and district heating system. However, Electrical ondol system shows better efficiency in case of using the space during short time or individual heating systems which needs to heat quickly. The Experiment says that electric ondol system has more benefits on timing to reach the set temperature and energy-efficiency than wet ondol system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5614-5633
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• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.724-735
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• 2003

In recent high-performance superscalar processors, the result value of an instruction is predicted to improve instruction-level parallelism by breaking data dependencies. Using those predicted values, instructions are speculatively executed and substantial performance can be gained. It, however, requires additional power consumption due to the frequent access and update of the value prediction table. In this paper, first, the trade-off between the performance improvement and the increased power consumption for value prediction is measured and analyzed. And, in order to reduce additional power consumption without performance loss, the technique of controlling speculative execution with confidence counter and predicting useful instructions is developed. Also, in order to prove the validity, a tool is developed that can simulate processor behavior at cycle-level and measure total energy consumption and power consumption per cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1823-1840
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• 2023

In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.203-210
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• 2003

A simulation study was carried to analyze the vehicle fuel consumption on component basis. Experiments was also carried out to identify the simulation results, under FTP-75 Hot Phase driving conditions. and arbitrary driving conditions. A good quantitative agreement was obtained. Based on the simulation, fuel energy was used in pumping loss(3.7%), electric power generation(0.7%), engine friction(12.7%), engine inertia(0.7%), torque converter loss(4.6%), drivetrain friction(0.6%), road-load(9.2%), and vehicle inertia(13.4%) under FTP-75 Hot Phase driving conditions. Using simulation program, the effects of capacity factor and idle speed on fuel consumption were estimated. A increment of capacity factor of torque converter resulted in fuel consumption improvement under FTP-75 Hot Phase driving conditions. Effect of a decrement of idle speed on fuel consumption was negligible under the identical driving conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3018-3036
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• 2013

In this paper, we investigate power allocation scheme and outage performance for a physical-layer network coding (PNC) relay based secondary user (SU) communication in cognitive multi-antenna relay networks (CMRNs), in which two secondary transceivers exchange their information via a multi-antenna relay using PNC protocol. We propose an optimal energy-efficient power allocation (OE-PA) scheme to minimize total energy consumption per bit under the sum rate constraint and interference power threshold (IPT) constraints. A closed-form solution for optimal allocation of transmit power among the SU nodes, as well as the outage probability of the cognitive relay system, are then derived analytically and confirmed by numerical results. Numerical simulations demonstrate the PNC protocol has superiority in energy efficiency performance over conventional direct transmission protocol and Four-Time-Slot (4TS) Decode-and-Forward (DF) relay protocol, and the proposed system has the optimal outage performance when the relay is located at the center of two secondary transceivers.