• Korean Journal of Human Ecology
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• v.14 no.2
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• pp.277-292
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• 2005

The objectives of this study are to examine the degree of propensity for symbolic consumption among adolescents and its factors, and to investigate the effects of demographic variables - sex, grade, father's education, mother's education, father's job, mother's job, monthly allowance, monthly household income - self-esteem, and socialization agents variables - parents, friends, mass media - on the propensity. In this study, the propensity for symbolic consumption is defined as the propensity to consume products through their affective, subjective, and symbolic value rather than through their practical and utility value. The data used in this study were collected from 509 adolescents who are in the 2nd grade of middle or high schools in Pusan. The research results can be summarized as follows: 1. The propensity for symbolic consumption were found to have significant differences according to sex, father's education, mother's education, mother's job, and monthly allowance. 2. It differs significantly according to adolescents' self-esteem. That is, the lower self-esteem adolescents have, the higher propensity for symbolic consumption they show. 3. It also differs significantly according to the degree of communication with parents, the degree of accepting friends' view, the degree of communication with friends, the degree of informative influence from friends, and the degree of taking in mass media.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.360-375
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• 2011

The fashion market focuses on consumers and maximizes consumers' satisfaction. The fashion market has been segmented to better satisfy the variety of consumer group. Although market segmentation has been studied, efficiency and effectiveness of market segmentation continuously bring problems. Also, problems of prediction about real consumer behavior, and efficiency and effectiveness of standards are pointed out. The purpose of this study is to determine the most important variables for dividing fashion product buyers. This study was designed as qualitative study and in-depth interview was conducted. The in-depth interview was conducted with five experts in fashion intelligence agency. In-depth interview was completed by an analytic induction and an investigator triangulation. Questions were about characteristics, demographic characteristics, important factors and fashion buying relationship, and interests of current clothing shoppers. The results of qualitative research demonstrated that clothing shoppers, with their valuable consumption and selective buying behaviors, seek differentiated products. They also long for high quality apparel for its price, because of their valuable consumption and price centered tendency. They illustrated active sides, such as enthusiastic information searching and emotional or experiential consumption, rather than attitudinal sides. The variables for dividing fashion product buyers included: "innovative seeking", "symbolic seeking", "personalized seeking", "quality-seeking", "selective seeking", "price-seeking", "utility-seeking", "hedonic seeking", "sensitive seeking", "brand-seeking", "digital seeking", "information-seeking", and "eco-seeking".

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1404-1423
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• 2015

In smart grid, electricity consumption data may be handed over to a third party for various purposes. While government regulations and industry compliance prevent utility companies from improper or illegal sharing of their customers' electricity consumption data, there are some scenarios where it can be very useful. For example, it allows the consumers' data to be shared among various energy resources so the energy resources are able to analyze the data and adjust their operation to the actual power demand. However, it is crucial to protect sensitive electricity consumption data during the sharing process. In this paper, we propose a fine-grained access control scheme (FAC) with efficient attribute revocation and policy updating in smart grid. Specifically, by introducing the concept of Third-party Auditor (TPA), the proposed FAC achieves efficient attribute revocation. Also, we design an efficient policy updating algorithm by outsourcing the computational task to a cloud server. Moreover, we give security analysis and conduct experiments to demonstrate that the FAC is both secure and efficient compared with existing ABE-based approaches.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.42-49
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• 2007

For electricity markets to function in a truly competitive and efficient manner, it is not enough to focus solely on improving the efficiencies of power supply. To recognize price-responsive load as a reliability resource, the customer must be provided with price signals and an instrument to respond to these signals, preferably automatically. This paper attempts to develop the Windows-based load management system in competitive electricity markets, allowing the user to monitor the current energy consumption or billing information, to analyze the historical data, and to implement the consumption strategy for cost savings with nine possible scenarios adopted. Finally, this modeling framework will serve as a template containing the basic concepts that any load management system should address.

• Journal of the Korean Society of Food Culture
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• v.34 no.6
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• pp.719-725
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• 2019

This study examined the relative importance and the effective utility of fermented milk by consumers. The questionnaire was developed by an in-depth interview and literature review and was surveyed on-line. Statistical analysis was carried out descriptive analysis, ANOVA, paired t-test, and conjoint analysis using the SPSS package. First, an analysis of the consumption status of fermented milk found that the consumption frequency was 1-2 times/week (36.2%), 3-4 times/week (26.5%). The product choice attributes of fermented milk were found to be the same with 'taste' (3.93) and 'manufacturing date/expired date' (3.92), rated the highest, followed in order by, 'sanitary quality' (3.82), 'origin of ingredient' (3.81). Comparative analysis of the importance and satisfaction level of the choice attributes of fermented milk showed that the choice attributes with lower satisfaction compared to importance were 'taste', 'nutrients', 'manufacturing data/expired date', 'sanitation quality', 'price', 'manufacturing method' and 'certification of quality' (p<0.001, p<0.01). 'Price' and 'certification of quality' were the choice attributes of fermented milk classified as 'Focus Here' because of its high importance and low satisfaction. The preferred combination of relative importance in choice attributes of the fermented milk was 'domestic resource', 'Eat with spoon', and 'none additives'. Therefore, it is believed that sales will increase if dairy companies can improve the 'price' and 'certification of quality'. In addition, the use of domestic ingredients in the development of new fermented milk products in the future could be an important marketing factor in consumer choice.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.367-377
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• 1997

In order to set public policy to overcome 'water crises' on both quantity and quality of water, we looked into the national-economic role of Korea water utility by two approaches. First, we examined the relationship between water consumption and economic growth during 1978-94, a period of rapid increase in water consumption caused by prompt industrialization and urbanization. The price and income elasticities of aggregate and sectoral demand for water were estimated. Second, we developed a static input-output(I-O) framework for analysing water issues in the short run. In addition, we discussed two topics in its application: i) sectoral failure(shortage) costs by supply-driven I-O model, ii) Leontief price model's sectoral pervasive effects of price due to rise in water rate. In conclusion, we found that investments to water sector and water shortage has a big influence on the standard of living and industrial production. Also we found that raising water rate to encourage conservation or to create investment funds decreases demand for water significantly but has a small influence on overall price levels.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• Architectural research
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• v.19 no.3
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• pp.71-77
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• 2017

Dynamic pricing refers to a system in which a tariff varies, according to a level of charging and applied time depending on time change. The power billing system used in the Korean Electric Power Corporation (KEPCO) is based on time of use (TOU) pricing, which is one of the dynamic pricing systems. This paper aimed to determine the operational results of a variable refrigerant flow system, to which a new control algorithm was applied, in order to respond to dynamic pricing, in summer and the utility of the new control. To do this, real measured data was acquired from a VRF system installed in a building for educational purposes, where dynamic pricing was applied for about 100 days during summer time. At the maximum load operation time period in TOU, the new control minimized operation within the indoor comfort range, an increase in refrigerant evaporation temperature in the indoor unit and the number of revolutions in a compressor in the outdoor unit was limited. As a result, power usage was decreased by 11%, and the operational cost by 14.6%. Furthermore, measurement results using the Predicted Mean Vote (PMV) model, that represented satisfaction of thermal environment, showed that 82.8% to 90.4% of the occupants of the building were satisfied during operation when the new control was applied.

• Korean System Dynamics Review
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• v.5 no.1
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• pp.49-71
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• 2004

Demand-side Management can be defined as'any utility activity aimed at modifying customers' use of energy to produce desired changes in the utility's load shape'. Customers benefit by being able to control energy costs and improve quality of life and become more productive. Utilities benefit from DSM's value as a resource that enhances asset utilization and reduces both fuel costs and environmental emissions. The scope of DSM includes load management through rate schedules and conservation by improving energy effciency and using electricity consumption effectively. This paper study the DSM resource evaluation and customer behavior analysis todesign the DSM Program plan in response to customer needs. We develop basic system dynamics model to analysis the customer behavior based on a survey research. The DSM Program participants in the Hi- efficiency Inverter, Electric motor and efficient lighting applicancies operating by Conservation program 2002 become the survey objects. DSM resource evaluation evaluate firstt the distribution potentialities of each machine and then forecast the degree of diffusion. We apply the system dynamic approach to simulate the dynamic DSM market situation at the domestic beginning. This model will give the energy Planner the opportunity to create different scenarios for DSM program planning. Also it will lead to increased understanding of the dynamic DSM market