• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.93-100
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• 2004

Test scheduling of SoC (System-on-a-chip) is very important because it is one of the prime methods to minimize the testing time under limited power consumption of SoC. In this paper, a heuristic algorithm, in which test resources are selected for groups and arranged based on the size of product of power dissipation and test time together with total power consumption in core-based SoC is proposed. We select test resource groups which has maximum power consumption but does not exceed the constrained power consumption and make the testing time slot of resources in the test resource group to be aligned at the initial position in test space to minimize the idling test time of test resources. The efficiency of proposed algorithm is confirmed by experiment using ITC02 benchmarks.

• Smart Media Journal
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• v.8 no.4
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• pp.72-79
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• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.115-129
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• 2022

Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

• Journal of Aquaculture
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• v.12 no.3
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• pp.247-254
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• 1999

Changes of oxygen consumption of Nile tilapia in relation to different body sizes(average body weight 4 g, 40 g, 120 g and 400 g) and water temperatures ($20^{\circ}C$, $25^{\circ}C$ and $30^{\circ}C$) were investigated by a continuous oxygen monitoring system. Mean oxygen consumption of 4 g, 40 g, 120 g and 400 g Nile tilapia at $20^{\circ}C$ were 318.8, 214.9, 84.1 and 69.4 mg $O_2$/kg fish/hr and that at $25^{\circ}C$ were 435.2, 345.9, 151.5 and 115.9 mg $O_2$/kg fish/hr, and that at $30^{\circ}C$ were 611.1, 538.4, 320.8, and 236.0 mg $O_2$/kg fish/hr, respectively. Oxygen consumption per unit body weight tended to decrease exponentially at all temperatures (P<0.05) as body weigth of the fish increased. Oxygen consumption of this fish at $25^{\circ}C$ was $1.61\pm0.18$ times higher than that at $20^{\circ}C$ and oxygen consumption at $30^{\circ}C$ was $1.53\pm0.27$ times higher than that at $25^{\circ}C$. Oxygen consumption per unit body weight linearly increased with the water temperature increased. Also, oxygen consumption of this fish during day time was higher than that during night time at 12L:12D day light condition. The differences between maximum and minimum daily oxygen consumption of this fish increased with the water temperature increased.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.1-26
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• 2008

This paper attempts to re-evaluate the size of housing wealth effect in Korea. Our focus is on the size of 'genuine' housing wealth effect, i.e., the response of consumption spending by home-owners to the changes in housing wealth. Two issues show up while we estimate the 'genuine' wealth effects using aggregate time series data: the issues around home ownership and proper measure of consumption. We first argue that it is more appropriate to use non-housing consumption, because housing consumption is in large part not of the choice of home owners but the imputed rents they do not actually choose to pay. We then proceed to address the issue of home ownership, by examining how much to revise the estimates of housing wealth effect obtained from aggregate non-housing consumption data. We construct two structural models and estimate the share of home-owners' consumption in those models' context. It is found that, if properly revised in light of the estimated consumption shares of home-owners, the magnitude of resulting housing wealth effects are larger than what simple time series regressions imply.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• The Korean Journal of Food And Nutrition
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• v.29 no.2
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• pp.275-282
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• 2016

Recently, increased caffeine intake has led to an increase in caffeine addiction and withdrawal symptoms. Coffee is surreptitiously consumed in as an additive to milk and caramel. There are few studies on how coffee affects the health of modern people. The purpose of this study is to determine the efficacy and side effects of coffee by awareness of coffee consumption patterns among college students, who are the principal consumers. A survey was conducted from May 11 to 17, 2015 and 302 questionnaires were analyzed. The respondents were 140 men (46.4%) and 162 women (53.6%). In terms of coffee additives, 151 (50.0%) respondents chose 'americano' and 111 (36.8%) 'variation'. The frequency of coffee intake and sleep time for college students was negatively correlated, with the correlation coefficient of -0.145 and significance probability of 0.019. The group that was 'positively' aware of the principal ingredients of coffee had a higher level of academic training than those with 'negative' awareness (p=0.000). Women recognized a larger number of side effects than men: 1.99 and 1.36, respectively, on average (p=0.001). 'Time for consumption' had statistically significant effects on the side effects of coffee consumption: consumption before/after lunch, before/after supper and before going to bed led to 0.4 times (p=0.048) and 0.3 times (p=0.023) more side effects, respectively, than consuming coffee after getting up and before/ after breakfast. Excessive caffeine intake through coffee led to limited sleep time and poorer learning concentration. The guidelines for proper coffee consumption should be created to help students consume coffee properly so that it will not affect sleep, learning concentration or adversely affect health.

• Journal of Families and Better Life
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• v.18 no.1
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• pp.167-184
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• 2000

This study has investigated the degree of similarities and/or differences of consumption expenditure styles among the households with different occupation. Two types of analysis were performed. One was comparative analysis which used to identify the changes of consumption expenditure styles among different occupation classes using time-series data of 1977-1996 Korean Urban Household Expenditure Survey and Rural Household Economy Survey. The other was multivariate analysis to investigate the effects of occupation on consumption expenditure styles with 1551 sample household data from 1996 Korean Urban Household Expenditure Survey. The results showed that the differences in consumption styles among different occupation classes including farmers are diminished during last two decades while there still exist some degree of differences in consumption styles. After controlling other socio-economic factors it is found that occupation is a determinant of consumption patterns of urban w ge earners especially consumption for clothing and health items.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12B
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• pp.1028-1036
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• 2006

Energy conservation is an important issue in wireless networks, especially for self-organized, low power, low data-rate impulse-radio ultra-wideband (IR-UWB) networks, where every node is a battery-driven device. To conserve energy, it is necessary to turn node into sleep state when no data exist. This paper addresses the energy consumption analysis of Direct-Sequence (DS) versus Time-Hopping (TH) multiple accesses and two kinds of sleeping protocols (slotted and unslotted) in PHY-MAC for Un networks. We introduce an analytical model for energy consumption or a node in both TH and DS multiple accesses and evaluate the energy consumption comparison between them and also the performance of the proposed sleeping protocols. Simulation results show that the energy consumption per packet of DS case is less than TH case and for slotted sleeping is less than that of unslotted one for bursty load case, but with respect to the load access delay unslotted one consumes less energy, that maximize node lifetime.

• The Korean Journal of Food & Health Convergence
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• v.7 no.6
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• pp.17-24
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• 2021

This study investigates the exercise-physiological changes in stages through the movement of the automatic stepper and to analyze the usefulness of the automatic stepper. For 18 male university students, out of 10 levels, 5 level and 10 level of automatic stepper exercise were performed. At each 10, 20, 30 minutes during exercise, 5 and 10 minutes after exercise stop the subjects were examined to analyze the changes in energy consumption after minutes, respiratory exchange rate, heart rate, oxygen consumption per body weight, METs, cumulative energy consumption, and lactic acid to verify the usefulness of the automatic stepper. The mean and standard deviation were calculated using the SPSS, and one-way ANOVA with repeated measure was performed to verify the difference in the mean between time periods. The LSD method was used for the post-hoc test, and the significance level was set to α = .05. There were no significant changes in both 5 and 10 level, but the cumulative energy consumption over time increased significantly. In addition, as a low-intensity exercise intensity is shown, a low increase in lactic acid indicated a safe exercise level. In future studies, in-depth studies of various variables through regular exercise programs are needed for those who need safe exercise.