• Journal of the Korean Society of Clothing and Textiles
• /
• v.39 no.4
• /
• pp.625-639
• /
• 2015

The number of Chinese tourists visiting Korea has rapidly increased over the last decade. It is important to understand Chinese consumption patterns and shopping behavior because they have become major customers in the Korean fashion market. This study focuses on how Chinese tourists feel while shopping in Korea and how emotions influence their attitude towards purchased products. We examine how planned purchase and unplanned purchase impact shopping emotions and product usage satisfaction. A survey was conducted on 550 women between 20 and 60 years of age who have visited Seoul more than once with an online panel from an international survey firm. Data are analyzed using structural equation modeling by AMOS 20.0. Respondents were asked to recall most impressive fashion product that they bought in Korea during their recent visit and to answer if it was a planned or unplanned purchase. This study also measures emotions during product purchases and usage satisfaction. The respondents are categorized into heavy and light buyers according to purchasing power to determine the moderating effects of purchase amount. The results indicate that planned purchases tend to deliver positive emotions that enhance product usage satisfaction. In the case of unplanned purchases, without the mediating role of positive shopping emotions, it has a negative impact on product attitude and shows the importance of positive emotions during shopping. The influence of unplanned purchases on shopping emotions or product attitude in light buyers is not significant for the moderating effect of purchasing power. Only planned purchases trigger product usage satisfaction when it is mediated by positive emotions.

• Proceedings of the KIEE Conference
• /
• 2002.07a
• /
• pp.432-434
• /
• 2002

Recently, electricity demand of remote islands in Korea has been rapidly increased. It's mainly due to increase of income level resulted from economic development. Electricity demand patterns and characteristics in remote islands are different from those of mainland in point of time of peak load, demographic and industrial characteristics of islands, and so on. The optimal power supply in remote islands has a important relationship with accurate analysis of island's load characteristics, the adoption of relevant load forecasting technique, and optimal power facilities reflecting local's electricity demand characteristics. This paper shows the recent load pattern and characteristics, load forecasting using probability distribution, and the perpetration of relevant power facilities in remote islands.

• International Journal of Internet, Broadcasting and Communication
• /
• v.9 no.2
• /
• pp.1-10
• /
• 2017

The high costs of electric vehicle supply equipment (EVSE) and installation are currently a stumbling block to the proliferation of electric vehicles (EVs). The cost-effective solutions are needed to support the expansion of charging infrastructure. In this paper, we develope EV charging system based on the big data analysis of the power consumption patterns. The developed EV charging system is consisted of the smart EV outlet, gateways, powergates, the big data management system, and mobile applications. The smart EV outlet is designed to low costs of equipment and installation by replacing the existing 220V outlet. We can connect the smart EV outlet to household appliances. Z-wave technology is used in the smart EV outlet to provide the EV power usage to users using Apps. The smart EV outlet provides 220V EV charging and therefore, we can restore vehicle driving range during overnight and work hours.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.97-115
• /
• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.127-132
• /
• 2021

Korea is both a resource-poor country and a energy-consuming country. In addition, the use and dependence on electricity is very high, and more than 20% of total energy use is consumed in buildings. As research on deep learning and machine learning is active, research is underway to apply various algorithms to energy efficiency fields, and the introduction of building energy management systems (BEMS) for efficient energy management is increasing. In this paper, we constructed a database based on energy usage by device per household directly collected using smart plugs. We also implement algorithms that effectively analyze and predict the data collected using RNN and LSTM models. In the future, this data can be applied to analysis of power consumption patterns beyond prediction of energy consumption. This can help improve energy efficiency and is expected to help manage effective power usage through prediction of future data.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1083-1093
• /
• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

• Journal of Biosystems Engineering
• /
• v.8 no.2
• /
• pp.1-10
• /
• 1983

The resulting characteristics of vibrations show different patterns for the various oscillating mechanisms. These vibrations causes troublesome operation problems for the operators and sometimes for the machines. Furthermore, in some cases the practical usage of this oscillating mechanism is constrained by its mechanical conditions. In this study, a balanced oscillating tillage tool with triple blades having different acting area was designed. The horizontal and vertical oscillating accelerations and draft power requirement due to the various travel speeds, lift angles, amplitudes and oscillating frequencies were investigated in a laboratory soil bin with a soil having invariable properties. The results obtained are summarized as follows: 1. Overall, the horizontal acceleration decreased as the oscillating frequency and amplitude decreased. But the increase in travel speed caused the decrease horizontal acceleration. The blade with the lift angle of $30^{\circ}$ exhibited the lowest value of horizontal acceleration among the blades tested. 2. For the vertical acceleration, the fluctuating trend of oscillating acceleration was similar to the trend of the horizontal acceleration. 3. The draft power requirement decreased as the amplitude and oscillating frequency increased. But the increase in travel speed caused the increase in draft power requirement. The blade with the lift angle of $10^{\circ}$ showed the lowest value of draft power requirement among the blades tested.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.8
• /
• pp.1792-1798
• /
• 2010

Home Gateway is always on for continuous services of home networks. Ubiquitous home networks are extended. so power consumption of home gateways increases by geometric progression. Our algorithm is for home gateway to sleep, listen or wakeup according to network traffic adaptively, as well as to keep always-on service. To do this, it traces the accumulated average of previous sleep periods. In addition to this basic algorithm, we make the profiles for user's living pattern per the day to reflect network usages in detail and adaptively. As the simulation results by comparing with overall accumulated average and per-day accumulated average, in case of the overall accumulated average, the difference the estimation and real value is distributed from 0.43% to 4%. In contrast of this, in case of the per-day accumulated average is distributed from 0.06% to 2%. From this results, we know the profiling of per-day usage pattern can help reduce the difference of the real sleep period and the estimated sleep period.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.5
• /
• pp.543-549
• /
• 2012

Hybrid electric propulsion systems are expected as future primary combat platforms because the systems can supply enough electric power, easily locate components inside vehicles, and maneuver without undesired noise. However, increasing electric/electronic/software usage causes abnormal failure patterns which have not been noticeable in conventional automotive. Recently, the functional safety standard for road vehicles were enacted and vehicle manufacturers request their components which satisfy standardized quality. This research analyzes functional safety standards(IEC 61508 and ISO 26262) and compares the standards for road vehicles with military standards of system safety. Strategies to apply functional safety in the combat hybrid electric vehicle are scrutinized.

• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.226-230
• /
• 2007

This paper proposes a local scheduling method based on user pattern for Volunteer computing project, Korea@Home. It enables Korea@Home participants to run the agent without disturbance. It is devised to prevent user's application from delay while running the agent and decreases the frequency of switching resource between the user and the agent. We analyze the user's patterns of donating computing resource with Korea@Home which is a representative volunteer computing project in Korea. It has contributed the computing power to several applications including climate prediction and virtual screening. It promotes the volunteers to participate continuously without disturbance and increases the potential computing power with non-disturbance scheduling based on user usage pattern for Volunteer Computing.