• Journal of the Korean Society for information Management
• /
• v.40 no.3
• /
• pp.143-162
• /
• 2023

This study analyzed the Beopmaru, Supreme Court Library of Korea, circulation data to identify user lending patterns and proposed a plan to reflect the analysis results in future user services. In 2022, Beopmaru's collection of books was 212,608, with law books accounting for 73%. However, general books accounted for 83% of actual circulation. Looking at the usage coefficient by topic, the literature field was the most actively used at 5.85, and the law field was the least used at 0.23. In the case of interlibrary loan, both KERIS member institutions and the Korean Bar Association had the highest loan ratios in the legal field, civil law field, and judicial litigation procedure field, in that order. However, member institutions affiliated with KERIS, a legal academic community, were lending law books on a wider range of subject areas than the Korean Bar Association, a practical organization. To improve access to legal information, the Beopmaru public service was implemented, but in reality, the use of reading space was high, and the proportion of general books loaned was much higher. In order to improve this, it seems necessary to strengthen the promotion of Beopmaru loan services, provide personalized services, improve book lending regulations, strengthen online services, and establish a cooperative network.

• Journal of Korean Home Economics Education Association
• /
• v.35 no.2
• /
• pp.41-59
• /
• 2023

This study aimed at analyzing the educational needs of home economics teachers for food literacy cultivation education in secondary school home economics. A total of 192 home economics teachers were surveyed about their perceptions of importance and performance of food literacy education content categories and elements, and their priorities were identified. Among the 38 content elements presented, home economics teachers recognized that the current performance level was significantly lower than that of the importance over 34 content elements. Based on the Borich educational needs assessment and the Locus for Focus Model, we identified five content elements with 'very high' educational needs ('food security/food sovereignty', 'reducing food-related waste', 'food waste management and recycling', 'food-related waste recycling', and 'country of origin information'), and four content elements with 'high' educational needs ('genetically modified food', 'ethical food consumption', 'food additives', and 'eco-friendly agricultural products'). These results indicate that dietary education in secondary school home economics should emphasize both the production and disposal of food. The findings of this study suggest implications for the needs for a new dietary education in secondary school home economics that allows students to learn all stages of food system. These results can also be used as a basis for dietary education for cultivating food literacy in secondary school home economics education.

• The Korean Society of Law and Medicine
• /
• v.24 no.1
• /
• pp.43-65
• /
• 2023

The healthcare industry is a digital healthcare that combines technology based on the 4th Industrial Revolution, dealing with information on individual health and medical care, and is a fusion of health care services and medical science and technology. It is questionable whether digital healthcare according to the paradigm change can be discussed by the concept of medical practice under the existing Medical Act. There is no clear definition of the concept of medical practice in the Medical Service Act, but the concept is established through precedents. In addition, under the Medical Service Act, the subject of medical practice is limited to medical personnel. However, digital healthcare sometimes diagnoses and treats diseases using digital technology by medical personnel. On the other hand, what is possible by non-medical personnel is digital healthcare. This is because digital healthcare is understood as a concept that includes health care such as exercise, eating habits, and weight control. For this reason, if the concept of medical practice under the "Medical Act" on digital healthcare is included, it is subject to criminal punishment for "unlicensed medical practice" prescribed in Article 27 of the "Medical Act". In the health and medical industry, digital transformation and convergence with information and communication technology are rapidly progressing. As a result, there is a need to newly define it as 'digitalized medical practice' or 'information and communication technology (ICT)-based medical practice' separately from existing medical practices. The concept of medical practice has variability, not a fixed and invariable concept. However, in response to this demand, it is not an infinite expansion of the concept of medical practice, but a request to reset its scope. Therefore, the concept of medical practice should be legislated by reflecting the demand of consumers for the medical service system.

• Convergence Security Journal
• /
• v.22 no.2
• /
• pp.115-120
• /
• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• Korean Journal of Culture and Social Issue
• /
• v.22 no.1
• /
• pp.41-64
• /
• 2016

In two experiments, we compared envy with admiration in attentional and motivational benefits. In addition, we tested whether individual differences in working memory capacity (WMC) have consequences for emotion regulation. In Study 1, following WMC tasks, the participants were primed either with envy or with admiration through a recall task, in which they had to recall their own experiences about envy or admiration. The participants in the envy condition considered it more undeserved that another person had an advantage over them, than in the admiration condition. Additionally, in the envy condition, WMC was related to happiness, and anxiety was related to the motivation to study more. In contrast, there were no significant relationships between WMC, emotion and study hours in the admiration condition. Study 2 (N=43) found greater memory for the envy scenario in the envy condition than in the admiration and in the control condition. Additionally, there were significant relationships between WMC, anxiety and recall accuracy in the envy condition. However, these relations were not found in the admiration and in the control condition. Findings implicate that envy may play an important role in memory systems and that WMC is related to emotion regulation abilities.

• Journal of Industrial Convergence
• /
• v.21 no.9
• /
• pp.41-48
• /
• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.31-49
• /
• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.

• Journal of The Korean Association For Science Education
• /
• v.27 no.3
• /
• pp.272-284
• /
• 2007

The purpose of this study was to describe the scales of attitudes toward science and the validation of instruments for students and their parents. These instruments include three scales: cognition about value of science, affection toward science & science learning, and conative participation in scientific activities. A sample of middle school students (N=198) and their parents (N=153) was selected. Data analysis indicated that the instruments developed in this study had proper validity and reliability measures (${\alpha}=0.93$ for student questionnaire, ${\alpha}=0.88$ for parent questionnaire). The results reveal that both students and parents were well aware of the academic/vocational and social value of science, but they had low awareness of the individual value. In spite of that, students have positive feelings regarding enjoyment toward science and science learning, their self-concept and self-efficacy were low. And parents' responses were observed to support their kids in general field but not in science. Especially, female students had low participation in scientific activities and also their parents had low support for scientific activities (p<.0.1). Finally, there were positive correlations between students' attitudes toward science and their parents' affection toward science & science learning and conative participation in science activities.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.2
• /
• pp.34-40
• /
• 2024

Secret sharing is a cryptographic technique that involves dividing a secret or a piece of sensitive information into multiple shares or parts, which can significantly increase the confidentiality of a secret. There has been a lot of research on secret sharing for different contexts or situations. Tassa's conjunctive secret sharing method employs polynomial derivatives to facilitate hierarchical secret sharing. However, the use of derivatives introduces several limitations in hierarchical secret sharing. Firstly, only a single group of participants can be created at each level due to the shares being generated from a sole derivative. Secondly, the method can only reconstruct a secret through conjunction, thereby restricting the specification of arbitrary secret reconstruction conditions. Thirdly, Birkhoff interpolation is required, adding complexity compared to the more accessible Lagrange interpolation used in polynomial-based secret sharing. This paper introduces the multi-compartment secret sharing method as a generalization of the conjunctive hierarchical secret sharing. Our proposed method first encrypts a secret using external groups' shares and then generates internal shares for each group by embedding the encrypted secret value in a polynomial. While the polynomial can be reconstructed with the internal shares, the polynomial just provides the encrypted secret, requiring external shares for decryption. This approach enables the creation of multiple participant groups at a single level. It supports the implementation of arbitrary secret reconstruction conditions, as well as conjunction. Furthermore, the use of polynomials allows the application of Lagrange interpolation.

• Journal of Industrial Convergence
• /
• v.22 no.3
• /
• pp.1-12
• /
• 2024

The purpose of this study is to categorize the adaptation of re-employed injured workers to the workplace and to explore the determinants that affect their adaptation to the workplace. In order to categorize the group of re-employed injured workers to adapt to the workplace, a latent profile analysis was conducted on 522 injured workers. As a result of the analysis, the workplace adaptation group was classified into three types: environmental dominant adaptation type (group 1), work-oriented adaptation type (group 2), and 'environmental adaptation type (group 3). In addition, as a result of conducting a mixed regression analysis to analyze the factors influencing their adaptation to the workplace after industrial accident, it was found that the work-oriented adaptation and environmental adaptation adaptation type were lower than the environmental dominant adaptation type. In addition, it was confirmed that educational background and self-esteem are factors that have an important influence on the adaptation of injured workers to the workplace. Based on the results of this study, it was suggested that the system needs to be supplemented in two aspects: customized support for individuals in the pre-reemployment stage and the employment environment after re-employment in order to increase the adaptation of injured workers to work. Specifically, there are consideration of the development and spread of rehabilitation programs and the expansion of the scope of subsidies that were paid only to the original business owners. Through this study, it is expected that more targeted policy measures can be prepared for re-employed injured workers.