• Journal of Smart Tourism
• /
• v.3 no.2
• /
• pp.23-36
• /
• 2023

Due to the phenomenon of aging, a new consumer segment known as the "new-silver generation" is emerging. Unlike the previous silver generation, this generation possesses significant economic power and consuming willingness, attracting attention from consumer goods companies. However, both the new-silver generation and the elderly face challenges in adopting contactless or self-service technologies such as self-order kiosks, resulting in negative reactions. Therefore, this study aims to investigate the attitude and response of the newsilver generation towards kiosks, as well as the factors influencing their resistance to such technology. By applying theoretical perspectives from the innovation resistance model, technostress theory, and the value-based model, this study identifies influencing factors for innovation resistance among the new-silver generation when using contactless technologies implemented in fast-food restaurants. The findings indicate that a lower awareness of new technologies and services corresponds to decreased adoption resistance, while a higher perceived value leads to more positive behaviors and attitudes among the new-silver generation utilizing kiosks at fast-food restaurants.

• Current Photovoltaic Research
• /
• v.11 no.4
• /
• pp.134-143
• /
• 2023

Efforts are being made to respond to global warming. Interest in and demand for the private sector-led RE100 campaign is also increasing. Self-built solar power generation, one of the implementation tools for RE100, is not expanding. However, it can be an economical means of implementation in the long run. In this study, we intend to analyze the impact on the optimal ratio of self-solar power generation using HOMER simulation. OPR defines the optimal solar power generation ratio and looks into what changes there are in the optimal solar power ratio when self-power consumption increases and external power purchase price changes. As a result, the optimal rate of self-solar power generation has a low impact even if self-power consumption increases. As the external power unit price increases, the optimal ratio increases, and at a power unit price of 100 KRW/kWh, OPR is 24%; at 200 KRW/kWh OPR is 31%; and at 300 KRW/kWh OPR is 34%. This shows that the electricity price replaced during the life cycle has a high impact on the economic feasibility of solar power generation. However, when the external power unit price reached a certain level, the increase in OPR decreased. This shows that it is difficult for domestic companies to achieve RE100 based on the economic feasibility of solar energy alone. Therefore, efforts are needed to supply renewable energy in the public sector.

• Journal of Platform Technology
• /
• v.6 no.3
• /
• pp.38-46
• /
• 2018

Smart Grid is an intelligent power grid for efficiently producing and consuming electricity through bi-directional communication between power producers and consumers. As renewable energy develops, the share of renewable energy in the smart grid is increasing. Renewable energy has a problem that it differs from existing power generation methods that can predict and control power generation because the power generation changes in real time. Applying a self-adaptative framework to the Smart Grid will enable efficient operation of the Smart Grid by adapting to the amount of renewable energy power generated in real time. In this paper, we assume that smart villages equipped with photovoltaic power generation facilities are installed, and apply the self-adaptative framework, AiTES, to show that smart grid can be efficiently operated through self adaptation framework.

• Journal of Korea Multimedia Society
• /
• v.6 no.7
• /
• pp.1312-1320
• /
• 2003

In this paper, we consider a multilayer neural network, with a single hidden layer. Error backpropagation learning method used widely in multilayer neural networks has a possibility of local minima due to the inadequate weights and the insufficient number of hidden nodes. So we propose a fuzzy supervised learning algorithm by using self-generation that self-generates hidden nodes by the compound fuzzy single layer perceptron and modified ART1. From the input layer to hidden layer, a modified ART1 is used to produce nodes. And winner take-all method is adopted to the connection weight adaptation, so that a stored pattern for some pattern gets updated. The proposed method has applied to the student identification card images. In simulation results, the proposed method reduces a possibility of local minima and improves learning speed and paralysis than the conventional error backpropagation learning algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.13 no.4
• /
• pp.71-84
• /
• 2003

Self-certified public keys need not be accompanied with a separate certificate to be authenticated by other users because the public keys are computed by both the authority and the user. At this point, verifiable self-certified public keys are proposed that can determine which is wrong signatures or public keys if public keys are used in signature scheme and then verification of signatures does not succeed. To verify these public keys, key generation center's public key trusted by users is required. If all users trust same key generation center, public keys can be verified simply. But among users in different domains, rusty relationship between two key generation centers must be accomplished. In this paper we propose inter-domain verifiable self-certified public keys that can be verified without certificate between users under key generation centers whose trusty relationship is accomplished. Also we present the execution of signature and key distribution between users under key generation centers use different public key parameters.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.05a
• /
• pp.57-60
• /
• 2008

KEPRI has studied planar type SOFC stacks using anode-supported single cells and kW class co-generation systems for residential power generation. A 1kW class SOFC system consisted of a hot box part, a cold BOP part and a water reservoir. A hot box part contains a SOFC stack made up of 48 single cells and ferritic stainless steel interconnectors, a fuel reformer, a catalytic combustor and heat exchangers. Thermal management and insulation system were especially designed for self-sustainable operation. A cold BOP part was composed of blowers, pumps, a water trap and system control units. When a 1kW class SOFC system was operated at $750^{\circ}C$ with hydrogen after pre-treatment process, the stack power was 1.2kW at 30 A and 1.6kW at 50A. Turning off an electric furnace, the SOFC system was operated using hydrogen and city gas without any external heat source. Under self-sustainable operation conditions, the stack power was about 1.3kW with hydrogen and 1.2kW with city gas respectively. The system also recuperated heat of about 1.1kW by making hot water.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.11a
• /
• pp.427-428
• /
• 2008

We have studied design and application about an self generation equipment for underground power transmission cable. The split CT(Current Transformer), which has the applicable underground power transmission cable, was manufactured through electromagnetic simulation of magnetic core. And manufactured the AC-DC converter that supplied stable DC power for PLC modem when current of power line has more than 150A. An self generation equipment using the CT and AC-DC converter get into operation the PLC modem consistently. As a result, the underground power transmission cable was showed the application possibility through the stable communication and network characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.2C
• /
• pp.31-40
• /
• 2005

we propose an enhanced self-generation supervised algorithm that by combining an ART algorithm and the delta-bar-delta method. Form the input layer to the hidden layer, ART-1 and ART-2 are used to produce nodes, respectively. A winner-take-all method is adopted to the connection weight adaption so that a stored pattern for some pattern is updated. we test the recognition of student identification, a certificate of residence, and an identifier from container that require nodes of hidden layers in neural network. In simulation results, the proposed self-generation supervised learning algorithm reduces the possibility of local minima and improves learning speed and paralysis than conventional neural networks.

• The Journal of the Korea Contents Association
• /
• v.22 no.9
• /
• pp.308-321
• /
• 2022

The purpose of this study is to understand how self-esteem, shopping motivations, and shopping tendencies affect the clothing purchase behavior of the so-called "MZ generation," a cohort that includes both millenials and Generation Z and exerts significant influence in various areas. The results of this study can be summarized as follows: First, it was found that extrinsic purchase motivations (purchased made due to the influence of other people), trend-seeking shopping tendencies, and pleasure-seeking shopping tendencies had a positive and significant effect on personal needs among the sub-factors of clothing purchase behavior of the MZ generation. Second, it was found that the MZ real purchase shopping motivations, trend-seeking shopping tendencies, pleasure-seeking shopping tendencies, and convenience-seeking shopping tendencies had a positive and significant effect on actual needs among the sub-factors of clothing purchase behavior among the MZ generation. Third, it was found that social self-esteem, extrinsic purchase motivations, and convenience-seeking shopping tendencies had a positive and significant effect on clothing marketing strategies among the sub-factors of clothing purchase behavior of the MZ generation. On the other hand, personal self-esteem was found to negatively affect the marketing strategies of clothing purchase behavior. In other words, the expectation that the MZ generation would buy clothes in accordance with their individual preferences and beliefs was not supported by the findings of this study. It would appear that the beliefs and behaviors of the digitally savvy MZ generation are changed by the fashion trend-related information they readily access when purchasing clothing. From the above research results, it can be concluded that there many variables that influence the clothing purchase behavior of the MZ generation and it is thus necessary to consider this cohort a new consumer segment and establish marketing strategies accordingly.

• Journal of Intelligence and Information Systems
• /
• v.9 no.3
• /
• pp.65-79
• /
• 2003

In general, the extraction and recognition of identifier is very hard work, because the scale or location of identifier is not fixed-form. And, because the provided image is contained by camera, it has some noises. In this paper, we propose methods for automatic detecting edge using canny edge mask. After detecting edges, we extract regions of identifier by detected edge information's. In regions of identifier, we extract each identifier using contour tracking algorithm. The self-generation supervised learning algorithm is proposed for recognizing them, which has the algorithm of combining the enhanced ART1 and the supervised teaming method. The proposed method has applied to the container images. The extraction rate of identifier obtained by using contour tracking algorithm showed better results than that from the histogram method. Furthermore, the recognition rate of the self-generation supervised teaming method based on enhanced ART1 was improved much more than that of the self-generation supervised learning method based conventional ART1.