Mimi Bong;Hyeyoun Kim;Ji-Youn Shin;Soohyun Lee;Hwasook Lee
Korean Journal of Culture and Social Issue
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v.14
no.1_spc
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pp.319-348
/
2008
Self-efficacy, achievement goals, task value, and attribution are some of the representative motivation constructs that explain adolescents' cognition, affect, and behavioral patterns in achievement settings. These constructs have won researchers' recognition by demonstrating explanatory and predictive utility that transcends various social and cultural milieus learners are exposed to. Korean adolescents' motivation is generally in line with this universal trend and can be described adequately with these constructs. Nonetheless, there also exist a host of indigenous factors that shape these motivation constructs to be uniquely Korean. The purpose of the present article was to explore some of the socio-cultural factors that appear to wield particularly determining effects on Korean adolescents' academic motivation. Review of the relevant literature identified interdependent self-construal, traditional morals of filial piety, familism, educational fervor, academic elitism, and the college entrance system as important cultural, social, and policy-related such factors. Also discussed in this article were the roles of these factors in creating more immediate psychological learning environments for Korean adolescents, such as parent-child relationships, teacher-student relationships, and classroom goal structures.
Maritime transportation is one of the oldest means of transportation utilized by mankind, and it has significantly contributed to the advancement of civilization by efficiently transporting bulk cargo at a low cost. The study aim to identify the factors influencing the selection of shipping companies in the bulk shipping market and provide insights for improving the competitiveness of shipping-related companies. To achieve this goal, the Analytic Hierarchy Process (AHP) was employed. For the empirical analysis, previous research, interviews, and a pilot test were conducted to identify five top-level factors such as companies, vessels, operations, services, and transaction factors. Each top-level factor has four sub-factors. The results of the analysis, based on 80 valid questionnaires, are as follows: Firstly, in the selection of shipping companies, the priority of factors influencing the choice of shipping companies was as follows: vessel factors were the most important, followed by company, operations, relationship, and service factors. Secondly, when investigating the priority of sub-factors, the availability/appropriateness of vessels was the most crucial factor, followed by company characteristics, financial soundness, and the company's reputation in order. The implications of these findings suggest that shipowners should focus on securing more suitable vessels and enhancing their reputation in response to shippers' demand. Shippers, on the other hand, should consider maintaining a healthy financial structure as a crucial task in securing competitive shipping service providers.
Journal of the Institute of Convergence Signal Processing
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v.24
no.3
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pp.166-171
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2023
Efficient energy management is a very important factor in sensor networks with limited resources, and cluster techniques have been studied a lot in this respect. However, a problem may occur in which energy use of the cluster header is concentrated, and when the cluster header is not evenly distributed over the entire area but concentrated in a specific area, the transmission distance of the cluster members may be large or very uneven. The transmission distance can be directly related to the problem of energy consumption. Since the energy of a specific node is quickly exhausted, the lifetime of the sensor network is shortened, and the efficiency of the entire sensor network is reduced. Thus, balanced energy consumption of sensor nodes is a very important research task. In this study, factors for balanced energy consumption by cluster headers and sensor nodes are analyzed, and a balancing distribution clustering method in which cluster headers are balanced distributed throughout the sensor network is proposed. The proposed cluster method uses multi-hop routing to reduce energy consumption of sensor nodes due to long-distance transmission. Existing multi-hop cluster studies sets up a multi-hop cluster path through a two-step process of cluster setup and routing path setup, whereas the proposed method establishes a hierarchical cluster routing path in the process of selecting cluster headers to minimize the overhead of control messages.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.17
no.4
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pp.127-142
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2022
According to social change, entrepreneurship education at university is drawing attention as a means to cultivate convergent creative competency required by the times. Currently, the number of entrepreneurship education at university is increasing every year, and quantitative expansion is taking place, but quality advancement of education remains a task. In this context, this study conducted an action research with the aim of revitalizing entrepreneurship education and upgrading quality, and developing a entrepreneurship education program suitable for general elective courses operated by universities. In the process of the study, first, through literature analysis related to entrepreneurship education at university, educational contents and teaching methods of entrepreneurship education were confirmed. Based on this, the IPA analysis was used to analyze the educational needs of students for entrepreneurship education contents and design a program that reflects this. The designed program was applied and operated to the entrepreneurship education of A University, and improvements were derived and improved by analyzing the opinions of learners in the action research process. The entrepreneurship education program developed through this study was composed as follows. The necessity of entrepreneurship education at the beginning of the lecture is sufficiently presented, and the knowledge necessary for start-up, including idea discovery and business model design, is delivered through theoretical lectures by teacher-centered method. In the second half of the lecture, students with similar interests are gathered into teams and learner-centered practical activities are operated. The contents of the activities include information on idea discovery, business model design, business plan and pitching. Practical activities for each team are conducted during class hours, and the professor advice on difficulties for each team.
AI is accepted not only in the private sector but also in the defense sector as a cutting-edge technology that must be introduced for the development of national defense. In particular, artificial intelligence has been selected as a key task in defense science and technology innovation, and the importance of data is increasing. As the national defense department shifts from a closed data policy to data sharing and activation, efforts are being made to secure high-quality data necessary for the development of national defense. In particular, we are promoting a review of the business budget system to secure data so that related procedures can be improved to reflect the unique characteristics of AI and big data, and research and development can begin with sufficient large quantities and high-quality data. However, there is a need to establish standardization and quality standards for structured data and unstructured data at the national defense level, but the defense department is still proposing standardization and quality standards for structured data, so this needs to be supplemented. In this paper, we propose an unstructured data set standard format for defense unstructured data sets, which are most needed in defense artificial intelligence, and based on this, we propose a standardization method for defense unstructured data sets.
Woongil Park;Eunbi Cho;Jeong-Hyeon Chang;Joo-chang Kim
Journal of Internet Computing and Services
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v.25
no.1
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pp.91-98
/
2024
With the advancement of ICT (Information and Communication Technology), searching for judgments through the internet has become increasingly convenient. However, predicting sentencing based on judgments remains a challenging task for individuals. This is because sentencing involves a complex process of applying aggravating and mitigating factors within the framework of legal provisions, and it often depends on the subjective judgment of the judge. Therefore, this research aimed to develop a model for predicting sentencing using artificial intelligence by focusing on structuring the data from judgments, making it suitable for AI applications. Through theoretical and statistical analysis of previous studies, we identified variables with high explanatory power for predicting sentencing. Additionally, by analyzing 50 legal judgments related to serious crimes that are publicly available, we presented a framework for extracting essential information from judgments. This framework encompasses basic case information, sentencing details, reasons for sentencing, the reasons for the determination of the sentence, as well as information about offenders, victims, and accomplices evident within the specific content of the judgments. This research is expected to contribute to the development of artificial intelligence technologies in the field of law in the future.
Ji Young Lee;Ji Eun Park;Mi Sun Chung;Se Won Oh;Won-Jin Moon;Aging and Neurodegeneration Imaging (ANDI) Study Group, Korean Society of Neuroradiology (KSNR)
Journal of the Korean Society of Radiology
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v.82
no.5
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pp.1124-1139
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2021
The objective assessment of atrophy and the measurement of brain volume is important in the early diagnosis of dementia and neurodegenerative diseases. Recently, several MR-based volumetry software have been developed. For their clinical application, several issues arise, including the standardization of image acquisition and their validation of software. Additionally, it is important to highlight the diagnostic performance of the volumetry software based on expert opinions. We instituted a task force within the Korean Society of Neuroradiology to develop guidelines for the clinical use of MR-based brain volumetry software. In this review, we introduce the commercially available software and compare their diagnostic performances. We suggest the need for a standard protocol for image acquisition, the validation of the software, and evaluations of the limitations of the software related to clinical practice. We present recommendations for the clinical applications of commercially available software for volumetry based on the expert opinions of the Korean Society of Neuroradiology.
Journal of The Korean Association For Science Education
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v.44
no.1
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pp.77-86
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2024
This study analyzed students' discourse and learning to investigate the impact of using Google Docs in science classes. The researcher, who is also a science teacher, conducted classes for 49 second-year middle school students. The classes included one using Google Docs and another using traditional paper worksheets covering identical content. Students' discourse collected from each class was compared and analyzed using Epistemic Network Analysis (ENA). The findings indicated that in the class using Google Docs, the proportion of discourse related to task was higher compared to the traditional class. More specifically, discourse regarding taking and uploading photos was prominent. However, such discourse did not lead to peer learning as intended by the teacher. An analysis based on achievement levels revealed that the class utilizing Google Docs had a relatively higher proportion of discourse from lower-achieving students. Additionally, differences were observed in the types of utterances and connection structures between the higher and lower-achieving students. The higher-achieving students took a leading role in providing suggestions and explanations, while the lower-achieving students played a role in transcribing them, with this tendency being more pronounced in the class using Google Docs. Lastly, students' changes in perception regarding the cause of static electricity were visualized using ENA. Based on the research findings, this study proposes strategies to enhance collaborative learning using Google Docs, including the use of open-ended problems to allow diverse opinions and outputs, and exploring the potential use of ENA to assess the learning effects of conceptual learning.
Journal of Korean Library and Information Science Society
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v.55
no.1
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pp.99-122
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2024
The purpose of this study is to analyze domestic academic library development plans, check whether key components are reflected, and seek ways to improve the establishment of academic library development plans. To this end, a rubric evaluation technique derived from research related to evaluation of foreign universities and libraries was used. The libraries of the top 15 domestic universities were selected by referring to the QS World University Evaluation and THE World University Evaluation as the subjects of the study, and how much the core components of the development plan were reflected were evaluated. The results of the study are as follows. First, as a result of evaluating the university library development plan, most of the contents of 'purpose', 'goal', and 'action plan' were reflected, but vulnerabilities were found in 'mission' and 'vision'. Second, some private academic libraries were moving toward strategic planning at the level of advanced countries, including all of the core components. Third, although most academic libraries specified 'purpose', it showed limitations due to perfunctory description and connection. In the comprehensive evaluation, out of the highest score of 15, 12 were good and 3 were poor, indicating that the development plans of domestic academic libraries were generally at a 'good' level. As an improvement measure, it was suggested to form a task force for development plan establishment, to disclose and promote development plans, and to strengthen education on development plans for librarians.
Journal of agricultural medicine and community health
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v.42
no.1
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pp.13-23
/
2017
Objectives: This study was conducted to evaluate a relationship between the blood concentrations of toxic metals and the blood pressure in people living near the copper smelter. Methods: The study included 570 adults living within 4km of the smelter. We compared systolic and diastolic blood pressure between tertiary groups for blood cadmium, mercury and lead levels, respectively. Multiple regression analysis was performed to identify risk factors affecting systolic and diastolic blood pressures. Results: In male subjects, there is a significant difference in the mean of systolic and diastolic blood pressure between tertiary groups of blood cadmium and mercury levels, but in women, there was no significant difference in the mean systolic and diastolic blood pressures in all tertiary groups of heavy metals. The results of multiple regression analysis showed that age, BMI, and cadmium concentration in men were risk factors for blood pressure. In women, age and BMI, drinking and smoking, and blood mercury were significantly influenced to blood pressure. Conclusions: Residents living near the Janghang smelter showed high concentrations of blood lead and cadmium, suggesting that they were exposed to high concentrations of heavy metals released from the smelter in the past. Such exposure may have caused some blood pressure increase. Especially, the concentration of cadmium in the case of men and the concentration of mercury in blood in the case of women were found to be significantly related to the increase of blood pressure. The local population should be advised to make efforts to reduce exposure to environmental contaminants, in order to minimize cardiovascular disease, and to pay close attention to any health problems possibly related to toxic metal exposure.
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