• Journal of the East Asian Society of Dietary Life
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• v.26 no.4
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• pp.285-296
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• 2016

This study was conducted to obtain a better understanding of American green tea consumers for increasing Korean green tea sales in the US market. In doing so, this study investigated green tea choice attributes of US consumers and segmented them based upon their perceptions about important attributes of green tea. A factor-cluster segmentation approach was used for this study. An exploratory factor analysis identified five green tea choice motives: 'Sensory', 'Diet', 'Price', 'Health', and 'Brand'. Based upon these five choice attributes, cluster analyses classified all respondents into four homogeneous subgroups: 'Highly motivated', 'Taste/Price oriented', 'Health oriented', and 'Brand oriented'. Cross-tab tests proved that green tea consumption and purchasing patterns were significantly different among the four clusters. In particular, two cluster groups representing 'Highly motivated' and 'Health oriented' groups were found to offer the most utility for further American green tea market segmentation research. Findings show that American green tea consumers include a wide range of age groups and they usually buy green tea at grocery markets. Managerial implications for all cluster groups based upon their unique characteristics are provided. Korean green tea companies can apply these findings in order to develop more effective and efficient marketing strategies to attract American consumers to buy more Korean green tea.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.2
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• pp.71-78
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• 2009

Up until recently, the energy and the economic analysis of a cogeneration system have been implemented by a manual calculation that is based on monthly thermal loads of buildings. In this study, a cogeneration system modeling validation with a detail building energy simulation, eQUEST, for a building energy and cost prediction has been implemented. By analyzing the hourly building electricity and thermal loads, it enables users to decide proper cogeneration system capacity and to estimate more accurate building energy consumption. eQUEST also verified the energy analysis when the heat pump system is integrated with the cogeneration system. The mechanical system configuration benefits from the high efficiency heat pump system while avoiding the building electricity demand increase. Economic analysis such as LCC (Life Cycle Cost) method is carried out to verify economical benefits of the system by applying actual utility rates of KEPCO(Korea Electricity Power COmpany) and KOGAS(KOrea GAS company).

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.5
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• pp.505-516
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• 2003

The purpose of this study was to develop the measurement of fashion sensibility and to verify the validity and utility. The survey has been done 91 photos selected in fashion magazines with 25 semantic differential hi-polar scale. The obtained data were analyzed by MDS, Discriminant analysis and Regression analysis. The major findings of this research were as follows. 1. According to the sensibility positioning, fashion image was classified by 4 group and agreed with constructing factors of fashion. 2. As result of the discrimination analysis, distinguishable fashion sensibility among design elements of clothing was related to refined, pleasant, feel like buying sensibility. 3. As result of the regression analysis, Preference was related to looking good, refined, and sweet, Buying needs related to likable, looking good and natural, Riches related to elegant, neat and refined, Pleasure related to looking good, elegant and bright. 4. The fashion design properties were different regarding Preference, Buying needs. Riches and Pleasure. Preference and Buying needs were related to H-line, similarity color combination, cotton and linen, Riches related to brilliance texture, ruffle and flounces, Pleasure related to fit and sexy design of clothing.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.12
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• pp.1440-1453
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• 2011

Proper consumer segmentation is receiving more attention from industry professionals as markets become more diverse and consumer-centered. Researchers have recognized the limitations of the traditional cluster analysis technique and this research study analyzes market segmentation using Mixture-model or latent-class segmentation. This study used a questionnaire to determine the characteristics of clothing shoppers using a new technique that proved its superiority over traditional techniques. Questions included items measuring fashion shopping behavior, store choice criteria, apparel consumption styles, price perception by product type, and demographic characteristics. Data were collected from 1074 males and females in their 20s and 30s through an online survey. SPSS 16.0 and Latent GOLD 4.0 were used to analyze the data. The ideal typology of clothing shoppers using the Mixture-model were: 'brand loyalty orientated group', 'group of conservative late 30s', 'group of pleasure-emotion early 20s', 'value oriented consumer product with high-income group', 'group of eco/symbol oriented consumer', and 'group of utility/goal oriented male consumer'. This study showed differences in fashion product purchasing behavior by conducting market segmentation for clothing shoppers using the Mixture-model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.11
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• pp.53-58
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• 2015

Systemic heating and cooling air conditioning systems are popular in various industrial fields and even home. Recently, the rate of supply of this kind of multi-heat pump has been increased under ESCO financing supporting system. Generally the heat pumping system has a structural simplicity and easy installation benefits. and has good running efficiency under normal designed condition. But under extreme climate condition (over $+30^{\circ}C$, under $-10^{\circ}C$), this system exposes abnormal power consumption. It causes high progressive electric power rates and resultant peak power capacity of power plant. In this paper, a novel system concept of buffering refrigerant accumulator and constant pressure control system to relieve peak power load is proposed and this system's utility is verified with an prototype experimental system.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.341-349
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• 2021

Many emerging mobile ad-hoc network application communications are group-oriented. Multicast supports group-oriented applications efficiently, particularly in a mobile environment that has a limited bandwidth and limited power. Energy effectiveness along with safety are 2 key problem in MANET design. Within this paper, MANET is presented with a stable, energy-efficient clustering technique. In this proposed work advanced clustering in the networks with ticket ID cluster manager (TID-CMGR) has formed in MANET. The proposed routing scheme makes secure networking the shortest route possible. In this article, we propose a Cluster manager approach based on TICKET-ID to address energy consumption issues and reduce CH workload. TID-CMGR includes two mechanism including ticket ID controller, ticketing pool, route planning and other components. The CA (cluster agent) shall control and supervise the functions of nodes and inform to TID-CMGR. The CH conducts and transfers packets to the network nodes. As the CH energy level is depleted, CA elects the corresponding node with elevated energy values, and all new and old operations are simultaneously stored by CA at this time. A simulation trial for 20 to 100 nodes was performed to show the proposed scheme performance. The suggested approach is used to do experimental work using the NS- simulator. TIDCMGR is compared with TID BRM and PSO to calculate the utility of the work proposed. The assessment shows that the proposed TICKET-ID scheme achieves 90 percent more than other current systems.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.517-526
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• 2018

Climate adaptation strategies for water utilities including 16 water treatment plants(WTPs) in Jeju were investigated. Drought, heat wave, and heavy rain were among the most significant climate factors affecting water utilities in Jeju. Heat wave increases water temperature, which in turn increases the concentration of algae, color, and odor materials. Some adaption strategies for the heat wave can be strengthening water monitoring and introducing advanced water treatments. Heavy rain increases raw water turbidity in surface water. The 7 WTPs that take raw water from streams or springs had a maximum turbidity of less than 50 NTU under heavy rain. However, due to concerns of turbidity spike in treated water, some WTPs discontinued intaking raw water when raw water turbidity increased more than 2 NTU. They instead received treated water from other WTPs which took groundwater for water supply. This happens because of the low skills of employees. Thus, there needs to be an increase in operator competency and upgrade of water facilities for the adaption of heavy rain. To improve adaption for the drought, there should be an increase in the capacity of intake facilities of surface water as well as a decrease in water loss. In addition, water consumption per person should be decreased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5800-5818
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• 2018

Interference may occur when several co-located wireless body area networks (WBANs) share the same channel simultaneously, which is compressed by resource scheduling generally. In this paper, a QoS-aware Adaptive Coloring (QAC) scheduling algorithm is proposed, which contains two components: interference sets determination and time slots assignment. The highlight of QAC is to determine the interference graph based on the relay scheme and adapted to the network QoS by multi-coloring approach. However, the frequent resource assignment brings in extra energy consumption and packet loss. Thus we come up with a launch condition for the QAC scheduling algorithm, that is if the interference duration is longer than a threshold predetermined, time slots rescheduling is activated. Furthermore, based on the relative distance and moving speed between WBANs, a prediction model for interference duration is proposed. The simulation results show that compared with the state-of-the-art approaches, the QAC scheduling algorithm has better performance in terms of network capacity, average delay and resource utility.

• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.9-19
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• 2022

Purpose: Previous studies have shown that consumers feel more happiness when they have experiential purchases than material purchases. This experiential advantage has aroused great concern of researchers in the field of social and consumer psychology. Focusing on this issue, the paper aims to tease out the relevant academic work and to further provide with some significant implications. Research design, data and methodology: The paper has divided the review into the following parts. Firstly, the connotation of experiential purchase and material purchase has been simply defined; Secondly, based on the logical framework of pre-factor variables, intermediary variables and regulating boundary conditions, this paper has collated the causal chain of the influence of purchases types on happiness; Finally, this paper has reviewed and summarized the shortcomings of existing studies, and have pointed out specific objectives of future research. Results: From the perspective of time utility and space form, this paper has expounded the substantive differences between the two types of purchase, which lays a foundation for the explanation of the follow-up mechanism. Moreover, the paper has mainly interpreted the intermediary mechanism from two aspects, namely, individual elements of consumers and social elements of consumption situations. Conclusions: This study expands the scope of previous happiness research and strengthens the negative events adaptation research.

• The Korean Journal of Food And Nutrition
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• v.37 no.4
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• pp.197-210
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• 2024

This study aims to develop a deep learning model to monitor rice serving amounts in institutional foodservice, enhancing personalized nutrition management. The goal is to identify the best convolutional neural network (CNN) for detecting rice quantities on serving trays, addressing balanced dietary intake challenges. Both a vanilla CNN and 12 pre-trained CNNs were tested, using features extracted from images of varying rice quantities on white trays. Configurations included optimizers, image generation, dropout, feature extraction, and fine-tuning, with top-1 validation accuracy as the evaluation metric. The vanilla CNN achieved 60% top-1 validation accuracy, while pre-trained CNNs significantly improved performance, reaching up to 90% accuracy. MobileNetV2, suitable for mobile devices, achieved a minimum 76% accuracy. These results suggest the model can effectively monitor rice servings, with potential for improvement through ongoing data collection and training. This development represents a significant advancement in personalized nutrition management, with high validation accuracy indicating its potential utility in dietary management. Continuous improvement based on expanding datasets promises enhanced precision and reliability, contributing to better health outcomes.