• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.21 no.1
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• pp.1-10
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• 2015

Enzyme kinetics-based respiration model can be effectively used for estimating respiration rate in $O_2$ consumption and $CO_2$ production of fresh produce as a function of $O_2$ and $CO_2$ concentrations. Arrhenius equation can be applied to describe the temperature dependence of the respiration rate. Parameters of enzyme kinetics-based respiration model and activation energy of Arrhenius equation were compiled from analysis of literature data and closed system experiment. They enable to estimate the respiration rate for any modified atmosphere conditions at temperature of interest and thus can be used for design of modified atmosphere packaging of fresh produce.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.81-94
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• 2022

This study sets the research goal of reducing energy consumption which 'H' University Industry-University Cooperation Foundation and resident companies are concerned with, as well as conducting policy research and data analysis. We tried to present a solution to the problem using the technique. The algorithm showing the greatest reliability in the power of the model for the analysis algorithm of this paper was selected, and the power consumption trend curves per minute and hour were confirmed through predictive analysis while applying the algorithm, as well as confirming the singularity of excessive energy consumption. Through an additional sub-sensor analysis, the singularity of energy consumption of the unit was identified more precisely in the facility rather than in the building unit. Through this, this paper presents a system building model for real-time monitoring of campus power usage, and expands the data center and model for implementation. Furthermore, by presenting the possibility of expanding the field through research on the integration of mobile applications and IoT hardware, this study will provide school authorities and resident companies with specific solutions necessary to continuously solve data-based field problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.514-537
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• 2020

Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

• Journal of Distribution Science
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• v.18 no.1
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• pp.71-83
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• 2020

Purpose: Because the energy consumption, economic growth and logistics development are still the heated topics which have attracted many scholars' interests. Therefore, this paper attempts to analyze the effect of logistics development on the economic growth, explore the effect of the economic growth on energy consumption and to discuss the effect of the logistics development on energy intensity. Research design, data and methodology: Using the panel data over the period 2000-2017 of 156 countries and employing the country & year fixed effect model, system generalized method moments and random effect model, the empirical analyses of this propositions are performed. Results: The empirical findings present that the logistics development is positively related to the economic growth. The energy consumption in the t-1 period and economic growth are positively related to the current energy consumption. The logistics development is negatively related to the energy intensity. Meanwhile, the empirical findings also indicate that there is a great difference about these effects among the four sub-samples (low income 18 countries, low middle income 49 countries, upper middle income 44 countries, high income 49 countries). Conclusions: Based on the evidences in this paper provided, we can find that these variables can affect each other.

• Journal of the Korean Society of School Health
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• v.29 no.3
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• pp.218-225
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• 2016

Purpose: The purpose of this study was to investigate the factors affecting energy drinks consumption among adolescents in South Korea. Methods: The study is a secondary analysis. Using statistics from the 11th (2015) Korea Youth Risk Behavior Web-based Survey, any variations among the subjects were presented as percentages and analyzed by $x^2$ test and logistic regression analysis. The study sample comprised 68,043 middle and high school students in South Korea. Results: In Model 1 including general characteristics, the significant factors of energy drinks consumption were gender, weekly allowance, cohabitation with family. and economic status. In the final model where health-related characteristics were added, the significant factors were gender, school type, weekly allowance, cohabitation with family, stress level, sadness, drinking, smoking and walking days. Conclusion: The result suggests that intensified education on energy drinks consumption is needed not only at schools, but in the whole community. Also, adolescents' awareness of potential health effects of energy drinks, in particular when mixed in alcoholic beverages, should be increased through health education.

• Journal of Agricultural Extension & Community Development
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• v.16 no.4
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• pp.1021-1048
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• 2009

Based on Rural living indicator -2005 survey data, in RDA this study attempted to investigate Rural Residents' real life satisfaction or identity model by the types of leisure consumption depending on each generation and explored the relationship between leisure consumption and the enhancement of self-identity/ interpersonal relationship, and that between leisure consumption satisfaction and real life satisfaction. Based on systematic random sampling with constructed questionnaires, 1,870 data were collected and analyzed. Overall, the results of this study showed that there are statistically significant differences between generation in leisure consumption. In detail, the findings of this study are as follows. The types of Rural Residents' leisure consumption can be divided into three styles including Semi-leisure type, Passive leisure type and Total leisure type consumption. The preferred types of leisure consumption of Rural Residents' were Semi-leisure type, Passive leisure type and Total leisure type in order. Except for times-pending leisure culture consumption, Semi-leisure type and Passive leisure type influenced on the enhancement of self-identity and interpersonal relationship, then the enhancement of self-identity and interpersonal relationship influenced on leisure consumption-satisfaction, and finally leisure consumption satisfaction influenced on real life satisfaction.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.51-60
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• 2017

India is the top recipient of workers' remittance flows; recent data indicate that the Remittances/GDP ratio has increased from 2.7% in 2000 to 3.36% in 2015. We apply a consumption behavior model, based on the "permanent income hypothesis", to estimate the consumption augmentation and the stability impact for the period of 1989-2014. The independent variables are: (i) real per capita income (exclusive of remittances) is the measure of "permanent income", (ii) remittances is the measure of "transitory income", and (iii) real interest rate as the indicator of consumers' ability for intertemporal consumption. The economic ramifications are important since current global risk factors could decrease flows in the future. The results indicate the significance of all three variables; there are: (i) evidence of significant consumption augmentation, (ii) consumption responds higher to remittances than to real income, the remittance elasticity is 0.571 and the income elasticity is 0.31, and (iii) evidence of pro-cyclical effect. The VAR model indicates some linkages and causality in the series that result in small response to the shocks. Policies to increase or stabilize remittance flows and to leverage remittances for economic development are important.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.871-880
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• 2009

Along with the complexity and size growth of embedded software, it is critical to meet the nonfunctional requirements such as power consumption as well as functional requirements such as correctness. This paper, apart from the existing studies of source code-based power analysis, proposes an approach of model-based power analysis using UML 2.0. Specially, we focus on the development of energy library to analyze the power consumption of embedded software. Our energy library supports model-based power analysis, and also supports the easy adaption for the change of embedded application.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.3
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• pp.149-165
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• 2022

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.