• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.75-81
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• 1999

This paper presents in the rrethod power demand estimated of consuming facility algorithm using orthogonal polynomial regression rmdel. Estimation rmdel presented can use mathematical rrethod consists. of extrapolation and correlation rrethod, Computation tirre and capacity of presented rmdel was rmre economic than multiple regression rrodel because low-order equation can use in the high-order equation without sorre correction, and vice-versa. Therefore this rmthed can be very usefulness rmthed in the power demand estimation Fourth-order rrodel was very good armng this rrodel that was coJTJp)Sed the estimation rmdel of second, third and fourth-order. Power demand estimated result of consuming facility using correlation rrethod was good in the percentage error of about 2[%1 Also It was to verify efficiency and awroPJiation the estimated rmdel that estimation percentage error was about 1[%] in the oower demand estimated result of 1997.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1569-1580
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• 2016

For the 2.4 GHz active RFID to be successful in the market, one of the requirements is the increased battery life. However, currently we do not have any accurate power consumption estimation method. In this study we develop a simulation model, which can be used to estimate power consumption of tag accurately. Six different simulation models are proposed depending on collision algorithm and query command method. To improve estimation accuracy, we classify tag operating modes as the wake-up receive, UHF receive, sleep timer, tag response, and sleep modes. Power consumption and operating time are identified according to the tag operating mode. Query command for simplifying collection and ack command procedure and newly developed collision control algorithm are used in the simulation. Other performance measures such as throughput, recognition time for multi-tags, tag recognition rate including power consumption are compared with those from the current standard ISO/IEC 18000-7.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.11
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• pp.411-418
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• 2016

Context-aware application has a lot of power consumption because it creates context by using a number of smartphone's sensors. Furthermore, only few kinds of researches have been conducted that provide information for the evaluation result of power consumption in the aspect of applications. In addition, evaluation of power consumption do not consider user's usage pattern or provide only total amount of power consumption, and inform developers power consumption of sensors undistinguishable. It makes developers hard to develop a power consumption-considered application. If developers could get information for power consumption of context-aware application in detail, a development of power-considered context-aware applications would be possible. Consequently, this paper proposes a BMT(Bench Mark Test) model which is able to inform developers useful evaluation criteria and result about power consumption of smartphone's components and sensors with usage pattern considered.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06d
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• pp.440-444
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• 2007

센서 네트워크를 구성하는 각 노드는 AA형 건전지를 사용하여 2년 6개월 이상 동작하는 것을 목표로 하며, 따라서 저전력을 고려하여 설계되어야 한다. 본 논문에서는 저전력 센서 네트워크를 위한 분산 컴퓨팅 모델을 제안한다. 제안된 모델은 우선 센서 노드에서 처리를 위한 에너지 소비와 통신을 위한 에너지 소비의 크기를 분석한다. 그리고 처리 에너지 비용을 지불하여 통신 에너지 감소라는 이득을 얻을 수 있음을 보인다. 한편, 이 기법은 특정 센서 노드의 에너지를 집중적으로 소비할 수 있음을 보이고, 이를 해결할 수 있는 에너지 균형 분산 컴퓨팅 모델을 제안한다. 시뮬레이션 기반 실험 결과 제안된 모델이 전체적인 에너지 소비를 낮추었을 뿐 아니라 센서 노드들 간에 에너지 균형도 이루고 있음을 알 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1422-1427
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• 2006

In order to estimate the power consumed by an embedded microprocessor during an execution of software, we measure and utilize the current consumed by the processor during the execution of each instruction. In this paper, we measure and analyse the current consumed by the microprocessor adc16s310 during the execution of arithmetic and logic instructions, and propose a power estimation model which estimates the current for all instruction executions precisely by using a small numbers of current measurements. The proposed model can estimate the current with an average 0.34% error by using only 5.84% of total current measurements for arithmetic and logic instructions of the processor.

• Smart Media Journal
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• v.12 no.11
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• pp.18-26
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• 2023

The building energy management system (BEMS), a system designed to efficiently manage energy production and consumption, aims to address the variable nature of power consumption within buildings due to their physical characteristics, necessitating stable power supply. In this context, accurate prediction of building energy consumption becomes crucial for ensuring reliable power delivery. Recent research has explored various approaches, including time series analysis, statistical analysis, and artificial intelligence, to predict power consumption. This paper analyzes the strengths and weaknesses of the Prophet model, choosing to utilize its advantages such as growth, seasonality, and holiday patterns, while also addressing its limitations related to data complexity and external variables like climatic data. To overcome these challenges, the paper proposes an algorithm that combines the Prophet model's strengths with the gated recurrent unit (GRU) to forecast short-term (2 days) and medium-term (7 days, 15 days, 30 days) building energy consumption. Experimental results demonstrate the superior performance of the proposed approach compared to conventional GRU and Prophet models.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.17-25
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• 2023

As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.282-284
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• 2012

임베디드 분야에서 전력 에너지 소비 문제는 시스템을 설계하는데 있어서 매우 중요한 이슈가 되고 있다. 특히 휴대성이 강조되는 모바일 장치의 제한된 전력을 효율적으로 이용하기 위해서 하드웨어적인 관리 못지않게 소프트웨어적인 관리 기술의 필요성이 강조되고 있으며 전력 소비 관리를 위한 최적화된 컴파일러 기법이 연구되고 있다. 이 논문에서는 모바일 장치에서 구동되는 어플리케이션의 전력 에너지 소비를 줄이기 위한 전역 코드 스케줄링 기법을 제시한다. 이를 위해, 재목적 소프트웨어 개발 도구인 EXPRESSION의 컴파일러인 EXPRESS의 코드 최적화 기법을 이용하여 전력 에너지 효율적인 전역 코드 스케줄링 모델을 설계하고 성능평가 방법을 제시한다.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.10-14
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• 2013

In this paper, when applying current-mode circuit design technique showing constant power dissipation none the less operation frequency, to the low power design of dynamic voltage frequency scaling, we introduce the low power current-mode circuit design technique applying MOSFET in sub-threshold region, in order to solve the problem that has large power dissipation especially on the condition of low operating frequency. BSIM 3, was used as a MOSFET model in circuit simulation. From the simulation result, the power dissipation of the current memory circuit with sub-threshold MOSFET showed $18.98{\mu}W$, which means the consumption reduction effect of 98%, compared with $900{\mu}W$ in that with strong inversion. It is confirmed that the proposed circuit design technique will be available in DVFS using a current-mode circuit design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.