• Korean Journal of Materials Research
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• v.15 no.9
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• pp.613-619
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• 2005

The ever increasing popularity and acceptance in the market place of portable systems, such as cell phones, PDA, notebook PC, etc., are fueling effects in further miniaturizing and lowering power consumption in these systems. The dynamic power consumption due to the CPU activities and the static power consumption due to leakage currents are two major sources of power consumption. Smaller devices and a lower de voltage lead to reducing the power requirement, while better insulation and isolation of devices lead to reducing leakage currents. All these can be harnessed in the SOI (silicon-on-insulator) technology. In this study, the key aspects of the SOI technology, mainly device electrical properties and device processing steps, are briefly reviewed. The interesting materials issues, such as SOI structure formation and SOI wafer fabrication methods, are then surveyed. In particular, the recent technological innovations in two major SOI wafer fabrication methods, namely wafer bonding and SIMOX, are explored and compared in depth. The results of the study are nixed in that, although the quality of the SOI structures has shown great improvements, the processing steps are still found to be too complex. Between the two methods, no clear winner has yet emerged in terms of the product quality and cost considerations.

• 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.

• Journal of The Geomorphological Association of Korea
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• v.23 no.3
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• pp.57-66
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• 2016

The objective of this study is to find out geomorphological characteristics of historical ruins where people produced and consumed large jar coffins excavated in the Yeongsan river basin using the map of old drainage network to restore distribution network. For this purpose, we chose the 21 consumption sites. The results are as follows. First of all, large jar coffins(relics, 47.6% of total) in the Yeongsan River basin were located in Sampo stream basin, almost all of them were located within the Yeongsan River main stream basin and Sampo stream basin. Also, distance from all consumption site to river was within about 2km. Therefore, it is thought that the all consumption sites are located at the place of the gift of nature that was very favorable to water transport of jar coffins. The results of this study may be used as basic data for research of cultural relics in the Yeongsan river basin.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.1019-1035
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• 2020

This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.

• Nutrition Research and Practice
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• v.4 no.3
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• pp.243-251
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• 2010

Although noodles occupy an important place in the dietary lives of Americans, up until the present time research and in-depth data on the noodle consumption patterns of the US population have been very limited. Therefore, this study aimed to analyze the food consumption and diet patterns of noodle consumers and non-consumers according to age, gender, income, and ethnicity. The 2001-2002 NHANES databases were used. The NHANES 2001-2002 data showed that noodle consumers reporting noodle consumption in their 24-h recall were 2,035 individuals (23.3% of total subjects). According to the results, the mean noodle consumption was 304.1 g/day/person, with 334.3 g for males and 268.0 g for females. By age, the intake of those in the age range of 9-18 years old ranked highest at 353.0 g, followed by the order of 19-50 year-olds with 333.5 g, 51-70 year-olds with by 280.4 g, older than 71years old with 252.3 g, and 1-8 year-olds with 221.5 g. By gender, males consumed more noodles than females. Also, according to income, the intake amount for the middle-income level (PIR 1~1.85) of consumers was highest at 312.5 g. Noodle intake also showed different patterns by ethnicity in which the "other" ethnic group consumed the most noodles with 366.1 g, followed by, in order, Hispanics with 318.7 g, Whites with 298.6 g, and Blacks with 289.5 g. After comparing food consumption by dividing the subjects into noodle consumers and non-consumers, the former was more likely to consume milk, fish, citrus fruits, tomatoes, and alcoholic beverages while the latter preferred meat, poultry, bread, and non-alcohol beverages.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.75-88
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• 2021

Purpose: This research aimed at exploring the functions of consumers' perceiving approach and avoidance roles and their feeling anger and disgust in the effect of the two types of self-discrepancy at social identity such as the ideal self-discrepancy and the ought self-discrepancy on within-self domain versus across-self domain consumption. Research design, data, and methodology - This study divided the self-discrepancy group into the ideal self-discrepancy and the ought self-discrepancy group as experimental groups for empirical study. Self-discrepancy type between-subjects design was used to develop two types of questionnaire according to the type of experimental groups. The platform, 'questionnaire stars' of 'WeChat' in China was used to collect 103 data from the ideal self-discrepancy group and 102 from the ought self-discrepancy group for empirical study. T-test and the structural equation model in Amos 21 were used to verify hypotheses developed through theoretical review. Results - First, ideal self-discrepancy positively affected the role-approaching goal and anger. Second, ought self-discrepancy positively affected the role-avoiding goal and disgust. Third, the role-approaching goal and anger positively influenced on the within- versus across- domain consumption. Fourth, the disgust negatively influenced on the within- versus across- domain consumption, however the role-avoiding goal did not influence on the consumption. Fifth, there was the mediation roles of anger (disgust) in the effects of ideal (ought) self-discrepancy on the consumption. Conclusions - When consumers feel anger at the ideal self- discrepancy induced by in-group, it is necessary for the marketers to promote their product brand used by the in-group. They should develop and advertise the messages priming the ideal self-discrepancy and the anger to increase the intent to purchase or use their product brand when the in-group members have used the brand by relating the brand to their social identity concerned with the ideal self-discrepancy. However, marketers should help consumers feel disgust by developing and advertising the messages expressing the ought self-discrepancy to lead the consumers to the place of purchasing or using their product brand when the members have used the brand based on keeping the consistence between the brand and other social identity not related to the ought self-discrepancy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• KIEAE Journal
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• v.15 no.3
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• pp.37-42
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• 2015

Purpose: Apartment is a typical residential type in Korea. In the past, apartment types were very monotonous. But today, the types of complex are changed because personal needs have been diversified and personalized. In order to meet those needs, construction companies are constructing various types of apartments. The more apartment types are diverse, the more the energy problems are taken place. So, the purpose of this study is to solve the problem of energy gap in the same complex through improving the thermal transmittance of wall. Method: Heating energy consumption of Building Energy Efficiency Rating System and heating energy usage of apartment show a similar trend on the graph. In order to identify the best position of heating energy consumption difference reduction, we change the building's U-value of front, back, side walls. Result: In the A complex, maximum and minimum heating energy consumption building's shapes are flat. the best efficiency is side U-value change and the worst is front change. In the E complex, maximum heating energy consumption building's shape is tower and minimum building shape is flat. Consequently, the front and back wall performance change was little effect to reduce energy gap, while the change of side wall's U-value show the great reduction between building's energy consumptions.

• Journal of the Korean Society of Costume
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• v.39
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• pp.271-281
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• 1998

The purposes of this study were to deter-mine the dimensions of the housewives' cloth-ing behavior for the environmental protection and the identify the effective variables. The results of this study was intended to provide fundamental material for the establishment of clothing behavior guidelines for the environmental protection. This study was conducted by reference analysis and empirical study. To develop theoreti-cal framework study. To develop theoreti-cal framework of dimensions of environmental protection behavior, references concerned were analyzed. The results of reference analy-sis showed that the dimensions of environmental protection bahavior were resource and energy saving, sold waste reduction, resource reuse or recycle, and green product purchase. The dimensions of housewives' clothing behavior for environmental protection were identified by use of self-administered questionnaires. The results of enpirical study showed that the dimensions of clothing behavior for the environmental protection wre clothing resource reuse or recycle, clothing management resource saving, clothing consumption resource saving, green product purchase, and clothing management resource saving was the highest and that of resource reuse or recycle was the lowest. Environmental consciousness, taking environmental education or not, residing place, clothing seperate-collectiong at residing place were effective variables on clothing behavior for environmental protection.

• Korean Institute of Interior Design Journal
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• v.14 no.6 s.53
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• pp.86-94
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• 2005

The recognition of emotionality becomes so important that it is called' emotional consumption society'. Emotional design, which is mostly concern about user's consensus & experiences and in the space, is appeared on commercial place. Emotional design is understanded from a Interactive point of view, human and interior-space. The purpose of this study is to examine the emotional design by analysis of multiple-commercial-functioned shopping places. Specially, the most recently remarkale Jerde partnership's shopping space in Japan. Jerde partnership' project theme is creative experience by making place and experience design. Though, they weren't claim to stand for emotional design, but presented an emotional element in the shopping mall works.