• Journal of Korea Trade
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• v.26 no.8
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• pp.21-36
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• 2022

Purpose - Carbon emission standards are based on the "production-based carbon emissions" generated by the production of goods in the relevant country which were the existing measurement methods. However, can such carbon emissions measurement standards be established international? For example, some of the goods produced in developing countries are produced for the demand of developed countries. The method of measuring carbon emission based on the final demand of a certain country is called "consumption-based carbon emissions." This study compares productionand consumption-based CO₂ emissions according to economic growth in ninety-three countries categorized by income level. Design/methodology - Our empirical model considers the difference between production- and consumption-based CO₂ emissions according to economic growth. Also, our model investigated whether the EKC hypothesis in most of the previous studies that had been based on production-based emissions was also established in the consumption-based emission model. Considering the continuous characteristics of CO₂, we utilized the generalized method of moments (GMM), specifically a system GMM econometric technique because CO₂ in the previous period can affect CO₂ in the present period. Findings - Our main findings can be summarized as follows: The results show that for the consumption-based CO₂ emissions model, CO₂ continuously increases as economic growth increases in the upper-middle income countries. The inverted U-shaped result was found in the case of the production-based model. However, in the lower-income countries, an inverted-U shape in which CO₂ emissions decrease at some point as the economy grows in the production-based model does not appear. On the other hand, in the consumption-based model, an inverted U-shaped result was obtained when estimating with system-GMM. Additionally, the proportion of manufacturing, energy imports, and energy consumption had an effect on both the production- and the consumption-based model regardless of the group's CO₂ emissions. On the basis of such assessments, policymakers need to consider not only production- but also consumption-based options. Originality/value - Previous studies have mainly focused on production-based CO₂ emissions, with most of them revolving around economic growth or the effect of various social and economic factors on CO₂ emissions. However, this study considers the relationship with economic growth using consumption-based emissions as a dependent variable by classifying ninety-three countries by income level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1027-1035
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• 2014

The most important design factor for portable devices is power consumption. In this paper, in the early design stage of a mobile device which measures temperature and humidity a power consumption model will be proposed and then the overall power consumption will be estimated based on this model. We will verify previously the correctness of such estimated power consumption before implementation of the real device. That is our proposed design methodology based on power consumption model. An improved design method for efficiently reducing the current consumption in the idle mode is also presented. By implementing a real prototype of the mobile device for measuring temperature and humidity, the correctness of our proposed design methodology based on power consumption modeling will be verified.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.69-75
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• 2020

Industrial IoT has much interested in wireless mesh networks (WMNs) due to cost effectiveness and coverage. According to the advance in caching technology, WMNs have been researched to overcome the throughput degradation of multihop environment. However, there is few researches of cache power consumption models for WMNs. In particular, a wired line based cache power consumption model in content-centric networks is not still proper to WMNs. In this paper, we split the amount of cache power from the idle power consumption of CPU, and then the cache hit ratio proportional power consumption model (CHR-model) is proposed. The proposed CHR-model provides more accurate power consumption in WMNs, compared with the conventional cache power efficiency based consumption model (CPE-model). The proposed CHR-model can provide a reference model to improve energy-efficient cache operation for Industrial IoT.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.4
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• pp.287-293
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• 2003

This study examined the temperature-dependent regression model of energy consumption based on various measuring period. The methodology employed was to construct temperature-dependent linear regression model of daily energy consumption from one day to three months data-sets and to compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. Heating energy consumption from a building in Daejon was examined experimentally. From the results, predicted value based on one day experimental data can have error over 100%. But predicted value based on one week experimental data showed error over 30%. And predicted value based on over three months experimental data provides accurate prediction within 6% but it will be required very expensive.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.139-146
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• 2012

In the server cluster environment, one of the ways saving energy is to control server's power according to traffic conditions. This is to determine the ON/OFF state of servers according to energy usage of data center and each server. To do this, we need a way to estimate each server's energy. In this paper, we use a software-based power consumption estimation model because it is more efficient than the hardware model using power meter in terms of energy and cost. The traditional software-based power consumption estimation model has a drawback in that it doesn't know well the computing status of servers because it uses only the idle status field of CPU. Therefore it doesn't estimate consumption power effectively. In this paper, we present a CPU field based power consumption estimation model to estimate more accurate than the two traditional models (CPU/Disk/Memory utilization based power consumption estimation model and CPU idle utilization based power consumption estimation model) by using the various status fields of CPU to get the CPU status of servers and the overall status of system. We performed experiments using 2 PCs and compared the power consumption estimated by the power consumption model (software) with that measured by the power meter (hardware). The experimental results show that the traditional model has about 8-15% average error rate but our proposed model has about 2% average error rate.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.90-96
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• 2004

The objective of this study was to develop a model for safe work load based on a physiological model of metabolic energy of manual material handling tasks. Fifteen male subjects voluntarily participated in this study. Lifting activities with four different weights, 0, 8, 16, 24kg, and four different working frequencies (2, 5, 8, 11 lifts/min) for a lifting range from floor to the knuckle height of 76cm were considered. Oxygen consumption rates and heart rates were measured during the performance of sixteen different lifting activities. Simplified predictive equations for estimating the oxygen consumption rate and the heart rate were developed. The oxygen consumption rate and the heart rate could be expressed as a function of task variables; frequency and the weight of the load, and a personal variable, body weight, and their interactions. The coefficients of determination ($r^2$) of the model were 0.9777 and 0.9784, respectively, for the oxygen consumption rate and the heart rate. The model of oxygen consumption rate was modified to estimate the work load for the given oxygen consumption rate. The overall absolute percent errors of the validation of this equation for work load with the original data set was 39.03%. The overall absolute percent errors were much larger than this for the two models based on the US population. The models for the oxygen consumption rate and for the work load developed in this study work better than the two models based on the US population. However, without considering the biomechanical approach, the developed model for the work load and the two US models are not recommended to estimate the work loads for low frequent lifting activities.

• ETRI Journal
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• v.32 no.2
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• pp.302-311
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• 2010

In this study, we analyzed consumers' choices of various broadcasting and telecommunication convergence services and time consumption for chosen services by using survey data. A multivariate probit model was used to model consumers' choices of various broadcasting and telecommunication convergence services, and an ordered probit model was used to model consumers' time consumption for chosen services. Factors affecting consumers' choices and time-consumption behavior were identified, and simulation results of market competition and substitution were obtained. Based on these results, it was found that for the time being, consumers are highly locked into existing broadcasting services and are likely to become more price-sensitive to the new broadcasting and telecommunication convergence services. Also, the ways in which individual characteristics affect choices and time consumption were found to be very diverse service by service.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.98-105
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• 2021

Using the frequency-based decomposition, I decompose the consumption growth to explain well-known patterns of stock returns in the Korean market. To be more specific, the consumption growth is decomposed by its half-life of shocks. The component over four years of half-life is called the business-cycle consumption component, and the components with half-lives under four years are short-run components. I compute the long-run and short-run components of stock excess returns as well and use component-by-component sensitivities to price stock portfolios. As a result, the business-cycle consumption risk with half-life of over four years is useful in explaining the cross-section of size-book-to-market portfolios and size-momentum portfolios in the Korean stock market. The short-run components have their own pricing abilities with mixed direction, so that the restricted one short-term factor model is rejected. The explanatory power with short- and long-run components is comparable to that of the Fama-French three-factor model. The components with one- to four-year half-lives are also helpful in explaining the returns. The results about the long-run components emphasize the importance of long-run component in consumption growth to explain the asset returns.

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.335-356
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• 2011

In this paper, we attempted to suggest a way to evaluate appropriateness and efficiency for the energy consumption structure. For this, based on Markowitz (1952)' mean-variance portfolio model, we constructed an optimal fossil fuel mix. In constructing the optimal mix, we first defined returns on fossil fuels (oil, coal and natural gas) as TOE (Ton of Oil Equivalent) per $1. Then, by using the dynamic latent common factor model, we decomposed the growth rates of the returns on each fossil fuel into two parts : the common part and the idiosyncratic part. Finally, based on the results from the dynamic latent common factor model, we constructed the optimal fossil fuel mix implied by the mean-variance portfolio model. Our results indicate that for the fossil fuel mix to be on the efficient frontier, it is crucial to reduce oil consumption as low as possible. Moreover, our results imply that it is more efficient to increase natural gas consumption rather than coal consumption in reducing oil consumption. These results are in line with the strategies for the future energy consumption structure pursued by Korea and indicate that reduction in oil use can improve overall efficiency in energy consumption.

• 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.