• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.123-131
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• 2019

In this paper, related studies were investigated by dividing them into cost-benefit analysis, security continuity services, and SW-centric calculations. The case analysis was conducted on A institutions in the United States, Japan and South Korea. Based on this, an improvement model was prepared through comparison with the current system. The SCS(Security Continuity Service) performance evaluation system-based information protection service cost calculation model is proposed. This method applies a service level agreement(SLA) and NIST Cybersecurity framework that are highly effective through cost-effectiveness analysis and calculates consideration based on characteristics, performance criteria, and weights by information protection service. This model can be used as a tool to objectively calculate the cost of information protection services at public institutions. It is also expected that this system can be established by strengthening the current recommended statutory level to the enforceability level, improving the evaluation system of state agencies and public institutions, introducing a verification system of information protection services by national certification bodies, and expanding its scope to all systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.71-82
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• 2021

In this study, a novel method for monitoring road pavements using the Mobile Mapping System (MMS) and a deep learning crack detection system was presented. Furthermore, an optimal maintenance method through economic analysis was presented targeting the pavement section of Sejong City. As a result of monitoring the pavement conditions, it was confirmed that the pavement ratings were good in the order of national highways, municipal roads, and roads of provinces. In addition, economic analysis using the pavement deterioration model showed that micro-surfacing, one of the preventive maintenance methods, is the most economical in terms of maintenance costs and user benefits. The results of this study are expected to be used as fundamental reference for local governments' infrastructure management plans.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.193-200
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• 2022

In this paper, we examined the causes of privacy concerns and related factors in social log-in services. On the basis of the 'principal-agent theory,' we established factors such as perceived information asymmetry and fear of seller opportunism affecting information privacy concern of social log-in services users. In addition, we analyzed the relationship between the information privacy concern and intention to use on the basis of the 'privacy calculus theory'. The results of the study showed that (1) fear of seller opportunism had the significant effect on information privacy concerns, (2) information privacy concerns had the significant effect on perceived risk, (3) in accordance with the privacy calculus theory, perceived risk had the negative effect on intention to use, while perceived benefit had the positive effect on intention to use. The findings of the study are expected to help to improve the social log-in service firms' understanding for customers' information privacy protection behaviors.

• Journal of Platform Technology
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• v.9 no.4
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• pp.32-41
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• 2021

The EU enacted a law strongly regulating the GDPR to protect the privacy of its citizens on 25 May 2018. Compliance with GDPR is an essential prerequisite for companies to enter the European market in the global economic era. In this paper, Step-by-step measures have been defined to conclude DPA agreements for the appropriate level of protection against EU personal data transfer. To explore the benefits and expected effects of determining appropriateness at the government level. As a result, enterprises benefit from simplifying processes, reducing time, and reducing costs when entering the EU. Government-level support in response to personal data breach and communication with the EU Commission will have a positive impact, However, even after the adequacy decision, the entity continues to need activities to secure personal data through compliance with GDPR principles and obligations. Major operations of companies that comply with GDPR are also maintained as important tasks that must be observed in most cases except for the Data Protection Agreement.

• Asian Journal for Public Opinion Research
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• v.9 no.2
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• pp.142-160
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• 2021

The Internet and digital devices have become an important part of life among the youth (age 17-24) of today. During the COVID-19 pandemic in Indonesia, Internet use in youth increased by 19.3%, with an average usage of 11.6 hours per day. Youths gain a lot of opportunities from the Internet, but, it also exposes them to various risks. Therefore, there is a need for measures to make the Internet a safe place for youth, in a balanced way that addresses opportunities alongside risks, through digital literacy. It is expected that through digital literacy, youths can take advantage of online opportunities, without being subjected to any dangers. This study aims to examine the relationship between the digital literacy, online opportunities, and online risks of young people, while at the same time examining the influence of digital literacy on those online risks and opportunities. This study employed the quantitative study approach (explanatory study). Cross-sectional surveys and structured questionnaires were used for data collection. The results showed that youth's (age 17-24) monthly expenses, age, and education levels were important factors for digital literacy and online opportunity; also, the digital literacy variable plays an important role and affects online risk and opportunity positively. Digital literacy has a greater influence on online opportunities than it has on online risks. As youths spend more time online, they become more digitally literate, which can enable them to benefit more from new technology. Unfortunately, those with greater digital literacy cannot find a way to avoid risks while seeking opportunities.

• Nutrition Research and Practice
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• v.16 no.6
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.801-811
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• 2022

In this study, we constructed a database of dyeing concentrations of all reactive dyes used for dyeing linen according to the thickness of the linen fabric and attempted to improve the reproducibility of the dyeing process for the commercialization of linen fabric materials. Linen fabric is a natural cellulose material that is comfortable and suitable for eco-friendly trends. It is a typical summer material with excellent breathability and thermal conductivity, quick moisture absorption and dissipation, and a cool touch. Dyeability and fastness were evaluated depending on the thickness of the linen fabric using a monochlorotriazine (MCT) reactive dye and bifunctional yellow, red, and blue dyes. All three colors of the MCT reactive dye and bifunctional dyes exhibited a darker shade as the fiber thickness of the marker increased. Fastness to washing was excellent at grades 4-5 or higher, regardless of the color of the dye and the number of linen fabrics. Although some color-fastness differences were noted, with the color change occurring most frequently with blue color, the fastness variations with dye type were mostly similar. The results of this study are expected to facilitate the selection of reactive dyes according to the thickness of the linen fabric based on the basic data from the laboratory, which will aid in the mass production of linen fabric and benefit the fashion industry.

• Korean Journal of Materials Research
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• v.33 no.5
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.65-84
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• 2014

The purpose of this study is to review the theories and cases of performance sharing in the franchise industry to present a method for more effective franchise performance-sharing. To that end, this study reviewed the theory on resource dependence and the theory on inequality to describe the performance-sharing between the franchisor and the franchisee and their relationship. It also looked at the cases of a week-in cooler system at 'Beer Market', the allocation of fees for alcoholic beverage sales to franchisees, the scholarship program of 'Onigiri and Ikyudon' and 'Bonsamo' which is a franchisees' committee for Bonjuk to introduce examples of performance-sharing. Through a theoretical review and case review, this study presents five types of methods for performance-sharing. First, 'the sharing of core competence by the franchise company; second, 'the establishment of a royalty culture'; third, 'scientific analysis of markets and establishment of a revenue forecast system'; fourth, 'reinforced financial support from the franchisor'; and lastly, 'the positive application of franchisees' committees'. Such methods are expected to provide a groundwork for mutual benefit and co-prosperity between franchisor and franchisee.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.393-399
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• 2023

Upper limb amputees wear an upper limb prosthesis for both aesthetic purposes and functional necessity, and in particular, in the case of amputee with both hands, it is essential to wear a myoelectric prosthetic hand capable of gripping action. The prosthetic hand operated by the EMG signal of the remaining muscles is a public insurance benefit item of the Industrial Accident Compensation Insurance, and test method standards are needed to be developed for the safety of the user and the effectiveness of the product performance. In this study, we developed systems for measuring the gripping force of myoelectric hand prosthesis by a load cell and for durability test of the prosthesis over repeated use with a proximity sensor, and propose a test method standard. Since the international test method standard has not yet been established, it is expected that Korea will be able to play a leading role in this standardization field in the future.