• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.213-221
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• 2012

In this paper, a dynamic power management system is proposed to reduce energy consumption for multiple clients in cloud computing environments. The proposed system monitors both keyboard and mouse input from the user, available memory, and CPU usage in the virtual machine. If the system detects no keyboard and mouse input for a certain amount of time and both available memory and CPU usage reach predefined threshold value, the manager in the virtual machine orders the client to shutdown the client machine, which results in significant power save. The developed system is applied to the real university computer lab and the performance of the system is evaluated.

• Journal of the Korean Magnetics Society
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• v.20 no.6
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• pp.234-238
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• 2010

Solenoid diaphragm fuel pump, which to replace mechanical fuel pump system by utilizing cam-shaft driving force, is in the spotlight for being a high efficient green car component. However, there is a drawback in power consumption as a solenoid diaphragm fuel pump only relies on solenoid for its flux needed in reciprocating motion. Therefore, this research proposes permanent magnet type VCM (Voice Coil Motor) fuel pump system to minimized power consumption. Furthermore, the study compares and analyzes power consumption and dynamic performance between the current and the former solenoid diaphragm pump by conducting finite element analysis with the commercial electromagnetic solver, MAXWELL.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.222-229
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• 2020

Recent multi-core processors for smart devices use per-core dynamic voltage and frequency scaling (DVFS) that enables independent voltage and frequency control of cores. However, because the conventional task scheduler was originally designed for per-core DVFS disabled processors, it cannot effectively utilize the per-core DVFS and simply allocates tasks evenly across all cores to core utilization with the same CPU frequency. Hence, we propose a novel task scheduler to effectively utilize percore DVFS, which enables each core to have the appropriate frequency, thereby improving performance and decreasing energy consumption. The proposed scheduler classifies applications into two types, based on performance-sensitivity and allows a performance-sensitive application to have a dedicated core, which maximizes core utilization. The experimental evaluations with a real off-the-shelf smart device showed that the proposed task scheduler reduced 13.6% of CPU energy (up to 28.3%) and 3.4% of execution time (up to 24.5%) on average, as compared to the conventional task scheduler.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.1-8
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• 2016

We proposed a load unbalancing scheduling method for energy-efficient multi-core embedded systems considering DVFS (Dynamic Voltage/Frequency Scaling) power consumption and task characteristics. It is a new kind of scheduler which combines load balancing and load unbalancing technique. The purpose of the method is to effectively utilize energy without much effect in performance. In this paper, we conduct experiments on energy consumption and performance using the previous load balancing and unbalancing techniques and our proposed technique. The proposed technique reduced energy consumption more than 13.7% when compared to other algorithms. As a result, the proposed technique shows low energy consumption without much decline in the performance and is adequate for energy-efficient multi-core embedded systems.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.483-491
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• 2014

Contemporary computer systems exploits DVFS (Dynamic Voltage/Frequency Scaling) technology for balancing performance and power consumption. The efficiency of DVFS depends on how much performance we get for larger power consumption due to elevated CPU frequency. Especially for memory-bounded applications, higher CPU frequency often does not result in higher performance. In this paper, we present an upper bound of CPU frequency scaling based on memory accesses. It is observed that the performance gain due to higher CPU frequency is limited by memory accesses (last level cache misses) per instructions by experiments. Using the results, we present the CPU frequency upper bound with little performance gain. Experimental results show that for a memory-bounded application, applying the frequency upper bound enhances the energy efficiency of the application by above 30%.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.4
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• pp.43-53
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• 2002

In this paper, a new dynamic D-flip-flop which does not suffer from charge sharing and glitch problems is proposed. And a dual-modulus divide-by-128/129 prescaler has been designed with the proposed D-flip-flops using a 0.6$0.6{\mu}m$ CMOS technology. Eleven-transistor architecture enables it to operate at the higher frequency range and the transistor merging technique contributes to the reduction of power consumption. At 5V supply voltage, the simulated maximum operating frequency and the current consumption of the divide-by-128/129 prescaler are 1.97GHz and 7.453mA, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.854-857
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• 2015

As the number of devices integrated on system-on-chip(SoC) increases exponentially, energy reduction technology is essential. Dynamic Voltage and Frequency Scaling (DVFS) is a very effective technique for reducing power consumption. Since it requires complex voltage regulators and PLL circuits, DVFS tends to have significant overheads. In this paper, we propose a new voltage selection algorithm to minimize transition overhead for multiprocessor SoC (MPSoC). Simulation results show that proposed algorithm appears less energy consumption with transition overhead even though maintains performance.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.451-453
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• 2007

This paper describes the design of an asynchronous implementation of a sensor network processor. The main purpose of this work is the reduction of power consumption in sensor network node processors and the research presented here tries to explore the suitability of asynchronous circuits for this purpose. The Handshake Solutions toolkit is used to implement an asynchronous version of a sensor processor. The design is made compact, trading area and leakage power savings with dynamic power costs, targeting the typical sparse operating characteristics of sensor node processors. It is then compared with a synchronous version of the same processor. Both versions are then compared with existing commercial processors in terms of power consumption.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1584-1587
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• 2005

Although the picture quality of today's displays is very good already, a continuous improvement is desirable as the new larger display sizes increase the visibility of artifacts. A contributing factor for picture quality enhancement through smart video processing and algorithm design is the information gathered from video statistics. Interesting parameters gathered from video statistics are e.g. the image- and display load, the usage of the color gamut, the estimated power consumption and the occurrence of static image parts. Examples of applications that can benefit from video statistics are power calculations, color gamut mapping algorithms, dynamic backlight control for LCD panels and LED backlights for LCD panels.