• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.485-492
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• 2021

The wind turbines with a rated capacity of 50kW or less are generally considered as small class. Small wind turbines are an attractive alternative for off-grid power system and electric home appliances, both as stand-alone application and in combination with other energy technologies such as energy storage system, photovoltaic, small hydro or diesel engines. The research objective is to develop the 50kW scale wind turbine blades in ways that resemble as closely as possible with the construction and methods of utility scale turbine blade manufacturing. The mold process based on wooden form is employed to create a hollow, multi-piece, lightweight design using carbon fiber and fiberglass with an epoxy based resin. A hand layup prototyping method is developed using high density foam molds that allows short cycle time between design iterations of aerodynamic platforms. A production process of five blades is manufactured and key components of the blade are tested by IEC 61400-23 to verify the appropriateness of the design. Also, wind system with developed blades is tested by IEC 61400-12 to verify the performance characteristics. The results of blade and turbine system test showed the available design conditions for commercial operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.283-289
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• 2021

Many people with disabilities have shown interest in artificial intelligence speakers that serves as the main hub of the smart home. Therefore, the purpose of this study was to identify the intention of people with disabilities to use such speakers. The focus is on those with physical disabilities, a segment that accounts for the largest number of disability types. Based on the theoretical model of technology acceptance, the effect of perceived ease of use and perceived usefulness of artificial intelligence speakers by people with disabilities was analyzed using Structural Equation Modeling (SEM). Research has confirmed that the technology acceptance model is suitable for identifying the intention to use artificial intelligence speakers by people with disabilities, and specifically that the perceived ease of use has a significant impact on usefulness. Furthermore, the perceived ease of use for people with disabilities did not have a statistically significant effect on their intent to use whereas the perceived usefulness was shown to have a significant effect on the same. This study is meaningful as a foundation for developing customized artificial intelligence speaker services and improving the use of artificial intelligence speakers by people with disabilities.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.405-413
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• 2022

Since the COVID-19 outbreak, the active utilization of new health care service utilizing the ICT technology and data science such as telemedicine, smart hospital, AI dignosis has been increasingly found. In this study we examined the business model of Amazon healthcare which leads disruptive innovation in U.S. health care industry with the introduction of hybrid model of telemedicin, in-person care and customer-centric online drug delivery, home-use diagnostic kit, characterized by the integrated model combining medical care, drug delivery and the use of diagnostic kit. We showed using the multiproduct competition model that the synergy effect between the Amazon's original business areas and the healthcare business area causes the active market penetration and the increase in the customer value from utilization of the Amazon care. Using Hotelling's spatial competition model, we also showed that the competition in the health care market can be greater when consumer's choice of health care providers are available in telemedicine platform. In the long, run the issue of competition being weakened due to the exit of less competent healthcare providers may arise, to which the policymakers in the charge of fair competition in health care industry should pay attention.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.227-239
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• 2022

Purpose: In our study, in order to find lactic acid bacteria (LAB) with multi-drug resistance to antibiotics, we isolated 140 strains from 15 types of kimchi commercially available in Korea and 20 types of Kimchi made at home from January to December in 2016, and investigated their H₂O₂ generating ability and multi-drug resistance to antibiotics. Methods: In order to observe the H₂O₂ generation ability of LAB, we performed the experiment with methods such as Rabe, Hillier, and Kang. To test the antibacterial susceptibility of LAB, we used the disc agar diffusion method using MRS agar (Difco, USA) according to the CLSI and WHO test methods. There are 18 types of antibiotic discs used. Results: Out of the total numbers of 140 strains, 6 strains of Ent. Faecium, 25 strains of L. plantarum, 1 strain of L. rhamnosus, 3 strains of L. sakei, 1 strain of L. acidophilus, 1 strains St. thermophilus, and 7 of unidentified strains generated H₂O₂. The antibiotic susceptibility of Ent. Faecium indicated SXT, OX, NA, and E; and the antibiotic susceptibility of L. plantarum indicated NA; and the antibiotic susceptibility of St. thermophilus indicated NA, CC, RA, CTT, CM, and P ; and the antibiotic susceptibility of L. rhamnosus indicated SXT, VA, NA and CTT; and the antibiotic susceptibility of 6 strains of L. sakei indicated SXT, OX, NOR, NA, CTT and CIP, all indicating antibiotic resistance. In the case of multi-drug resistance to antibiotics for 53 strains of L. antarum, 8-drug resistance was the most common with 25 strains, followed by 7-drug-resistant strains with 18 strains, 9-drug-resistant strains with 4 strains, 6-drug-resistant strains with 3 strains, 5-drug-resistant strains with 2 strains, and 17-drug-resistant strains with 1 strain. In the case of multi-drug resistance to antibiotics for Ent. Faecium 27 strains, 9-drug resistance was most commonly identified as 9 strains, 8-drug resistance was identified as 6 strains, 7- and 11 drug resistances were identified as 4 strains each, and 4- and 6-drug resistances were identified as 1 strain each. Conclusion: Ent. Faecium, L. plantarum, L. rhamnosus, L. sakei, and St. thermophilus, shown to have anantibacterial activity in previous studies on LAB and shown to have and H₂O₂ generating ability, antibiotic resistance and multi-drug resistance in this study, are expected to be able to play an excellent role for long-term inpatients to use as an alternative to antibiotics and to cope with emerging antibiotic resistance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.897-907
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• 2023

The purpose of this study is to find out the development direction of adult learners' blended learning class as a study on the class satisfaction of adult college students according to the blended learning class participation type. To this end, a survey was conducted targeting adult learners at two schools that are carrying out the LiFE project (lifelong education system support project). The analyzed research results are as follows. First, in the case of adult learners, the proportion of participating in liberal arts + major classes as a blended learning subject was 77.8%, and home was the highest with 69.8% as a place to participate in online classes. Second, satisfaction with the blended learning teacher/instructor teaching method was generally satisfied with 95.2% of average or higher. Third, 96.8% of the students answered 'yes' or higher regarding the level of satisfaction with the blended learning method. The above research results show that blended learning is one of the important teaching and learning methods in providing adult-tailored education to adult learners who combine work and study. It can be seen that the blended learning teaching method is an effective teaching method that enables interactive communication between the instructor and the learner rather than the one-way teaching-oriented content delivery class of the traditional classroom.

• Journal of Distribution Research
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• v.17 no.4
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• pp.1-27
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• 2012

Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in