• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.276-279
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• 2022

The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning

• Analyses & Alternatives
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• v.1 no.2
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• pp.44-64
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• 2017

From the field survey of the main ethnic minority areas in the south China, it is found that political, economic, cultural and natural environmental changes are the main reasons leading to the change of customary law. The power mechanism of the customary law change include the three aspects, such as the promotion of country elite, the dominance of grassroots government, and the daily demands of the villagers, which promote the change of customary law alone or together. Through the application of customary law, the country elites can adjust and refine the rules of customary law in order to make out the new customary law and promote its development. In the current pattern of rural governance, grassroots self-government is actually the "official supervision of people's autonomy". The executive power of the grassroots government often intervene the practice of customary law and other informal rules. This is another mechanism of customary law change. Customary law arises from the practice of the daily life of the villagers. If the villagers think that the norms of customary law cannot meet the actual needs of daily life practice, the customary law will be promoted in the form of collective consultation. This is the most important dynamic practice mechanism of customary law change. Transformation and abandonment are the two ways to change customary law. No matter what kind of change does not lead to the demise of the customary law system, the demise of the customary law is only an outdated result, which is made by the universality, nature and objectivity of customary law. The procedure of customary law change is the process of continuation and rebirth about customary law. The result of the change is to produce the new customary law of keeping pace with the times, and the customary law will be presented with new content and form after the change. The continuation of customary law means the inheritance of traditional customary law, but it is based on the transformation of traditional customary law. The rebirth of customary law means that the traditional customary law is completely discarded. But it will produce new customary law rules and be based on the needs of social life practice. Customary law occupies a pivotal position in the normative system and the national law cannot be replaced. The purpose of customary law change will let the customary rules better adapt to the development of modern society, adjust the social relations more reasonably and better meet people's needs of production and life, which is decided by the character of customary law.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.207-212
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• 2024

The importance of hydrogen fuel cells continues to be emphasized, and there is a growing demand for education and training in this field. Among various educational environments, metaverse education is opening a new era of change in the global education industry, especially to adapt to remote learning. The most significant change that the metaverse has brought to education is the shift from one-way, instructor-centered, and static teaching approaches to multi-directional and dynamic ones. It is expected that the metaverse can be effectively utilized in hydrogen fuel cell engineer education, not only enhancing the effectiveness of education by enabling learning and training anytime, anywhere but also reducing costs associated with engineering education.In this research, inspired by these ideas, we are designing a fuel cell education platform. We have created a platform that combines theoretical and practical training using the metaverse. Key aspects of this research include the development of educational training content to increase learner engagement, the configuration of user interfaces for improved usability, the creation of environments for interacting with objects in the virtual world, and support for convergence services in the form of digital twins.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• Journal of The Korean Association For Science Education
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• v.29 no.1
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• pp.116-136
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• 2009

Since there are differences in the content, structure and functions of interpersonal communication during the practice of school science classes, it needs to articulate the difference of the modality of pedagogical practice in order to understand science teaching in detail. These characteristics of science teaching can be investigated by further insightful analysis on language in the science classroom. In this study, classroom discourse language codes using Bernstein's code theory were analyzed in the case of a middle school science class on the unit of minerals. The discourse language code was identified by the value of classification, which revealed power relations to the contexts of discourse and participants of discourse. It was also identified by the value of framing, which showed hierarchical relation between teacher and students as discourse subjects, and discursive control on the initiative of discourse. The results addressed that six types of discourse language codes were constructed and that those language codes reflected diverse modalities of science teaching from student-centered instruction to teacher-centered instruction in relation to classroom discourse. The modality of science teaching according to the transition tendencies of discourse language code showed dynamic variations of 'controlled student-centeredness inducing teaching' - 'positional student-centeredness permissive teaching' - 'controlled students' participation permissive teaching' - 'controlled student-centeredness facilitative teaching' - 'student-centeredness enhancing teaching'. In addition, results released that discursively and hierarchically weak control of discourse is necessary for enhancing student-centeredness of science teaching. Moreover, teaching practice enhancing student-centeredness can be accomplished by the harmony of a teacher's perception of discourse language code and his/her orientation to constructivist teaching and student-centered teaching.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.141-149
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• 2018

In this study, compacting, passing performance, segregation resistance and rheological properties were tested to improve the stability of fresh concrete in the production and construction of self-compacting concrete (SCC) using hollow glass powder(GB). As a result, T50 reaching time was shortened up to amount of GB $2.0kg/m^3$. The compacting according to the amount of GB was improved by ball bearing effect of GB. However, T50 reaching time was slightly increased at $4.0kg/m^3$. In the case of passing performance, the result showed that plain was Class 1, GB $0.5{\sim}2.0kg/m^3$ was Class 0, GB $4.0kg/m^3$ was Class 1. Therefore, the passing performance was improved with 'No blocking' up to amount of GB $2.0kg/m^3$. Passing performance Block step (PJ) number by J-ring method was also best at GB $1.0kg/m^3$. In the case of segregation resistance according to the amount of GB, dynamic segregation resistance was increased compared to plain regardless of the amount of GB. And static segregation resistance showed 2.5% of segregation rate at GB $1.0kg/m^3$. Therefore, it was greatly improved compared to plain (12.5%). In the case of rheology property according to the amount of GB, plastic consistency by increasing of GB content didn't show big difference. However, yield stress by increasing of GB content was decreased with GB $1.0kg/m^3$. In conclusion, GB $1.0kg/m^3$ was effective for improvement of compacting, passing performance and yield stress. Also, it will be useful for stability of SCC by improving segregation.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.4
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• pp.271-279
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• 1984

Effects of temperature and additives on the stability of actomyosin extracted from skeletal muscle of Israeli carp, Cyprinus carpio nudus, were studied by analyzing free SH-group, ATP-sensitivity and Ca-ATPase activity. The used additives were sucrose, sorbitol, Na-glutamate and L-cysteine. Furthermore, the denaturation constant($K_D$), protective effect(${\Delta}E/M$) and the other thermo-dynamic parameters on protein denaturation are systematically discussed. The actomyosin showed $4.12{\sim}4.68 mg/ml$ in protein concentration, $2.63{\sim}2.93\%$ in ribonucleic acid to the protein, $1:2.20{\sim}2.63$ in the binding ratio of myosin and actin, $4.33{\sim}5.26\%$ in fat content, 109.78 in ATP-sonsitivity, $0.159{\sim}0.201\;{\mu}M-Pi/min/mg-protein$ in Ca-ATPase activity and $3.3{\sim}3.4M/10^5$g-protein in free SH-group content. The first-order rate plots were obtained on the decrease of Ca-ATPase activity and ATP-sensitivity with an increase in temperature, while the free SH-group was increased to $60^{\circ}C$ and decreased rapidly above the temperature. The half-life of Ca-ATPase activity on the actomyosin Ca-ATPase was 280 min at $12^{\circ}C$, 125 min at $20^{\circ}C$, 55 min at $30^{\circ}C$ and 13 min at $40^{\circ}C$, and activation energy, activation enthalpy, activation entropy and free energy of the proteins at $20^{\circ}C$ wene 5,395 cal/mole, 4,814 cal/mole, -40.42 e.u. and 17,626 cal/mole, respectively. The protective effect of the additives on the actomyosin Ca-ATPase showed that the most effective material is $3\%$ sorbitol and followed in the order of $8\%$ Na-glutamate, $1\%$ sucrose and $1\%$ L-cysteine. The actomyosin was more stable at $-30^{\circ}C$ than at $0^{\circ}C$ and $-20^{\circ}C$. and when the additives were used in the low temperature storage, $8\%$ Na-glutamate was the most effective. $3\%$ sorbitol, $1\%$ sucrose and $1\%$ L-cysteine was to become lower in the order.

• Journal of Korean Academy of Nursing
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• v.7 no.2
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• pp.60-82
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• 1977

The purpose of this study is first, to analyse the present nursing education and the curriculum in Korea in view of the changes and the new tendency of nursing education and second, to compare our curriculum with that of America, where nursing activities are actively earring on and, third, to try to find out what we should reconsider and improve in our nursing education. The object of this study is the educational program and the curriculum from 1973 to 1976 by selecting each five from colleges and department of nursing in Korea and America. The results of the study were as fellows : . 1. The aim of nursing education puts impassion the role of leader, knowledge and technology of nursing, welfare of society and service of community in both the America and Korea. In Korea nursing is mainly restricted to the treatment of diseases, while in the America the items of the aim of nursing are mainly extended to the capacity for Self- realization of nurse, in Korea they are restricted to the treatment of diseases. 2. In Korea the rate of credit of the curriculum of nursing education is the highest in professional education, next in general education, next in supporting science and educational subject, while in America the rate of the credit is the highest in general education, next professional education and then supporting Science and educational subject isn′t included in the curriculum. 3. In both Korea and America the role of the animal credit allotment in general education, is the highest in the first year and the rate in supporting science is the highest in the second year. In Korea professional subjects are concentrated in the third year while in America there is a tendency that they are increasing in number in the grade order. 4. There is a tendency that the rate of the credit allotment of the main professional subjects in curriculum is higher in Korea than in America : that is, in Korea the rate of the allotment of the credit is the highest in medical - surgical nursing, next maternal - child nursing, next community - health nursing and the psychiatric nursing and there in a great difference in the rate of the allotment of each credit. While in America the rate of the allotment of the credit is the highest in community - health nursing, next in medical- surgical nursing, next in maternal - child nursing, and then in psychiatric nursing and there is little difference in the rate of tile allotment of each credit. 5. From general education, supporting science and professional education, they have considered the continuity and sequence in the structure of nursing curriculum of Korea and America. While in Korea we have partly made integration in tile content of the subjects. Most of the school in America, they have made integration in the content of subjects especially in all subjects, but in Korea we haven't made it in all subjects. 6. In the system and form of nursing education Problem solving method, Dialectical method and operational method are introduced in some America schools and in others there is a tendency that the whole nursing education has the system based on Preventive frame - work or Health -illness frame work ; while only one college has an attempt for Health - Illness continue in Korea. 7. In Korea nursing education, as the importance of health- nursing and team nursing, the aim which is also comparatively emphasized is about health management and service of collective community. The subject pertaining to the aim is the studies of community health nursing, which are more in number in America. 8. When we consider the association between the social, general aims ?f the nursing education and the formation of the curriculum in Korean nursing school the courses of study concerning "the role of leadership and cooperative personal relation": "nursing care for the group": dynamic nursing care": and "the system of the public health nursing associated with the understanding of the regional community" are insufficient as compared with those of America. Especially, the lack of the behavioral science including the nursing care connected with the care for the group, the basic science on the clinical and developmental psychology, anthropology in known to be a prominent issue.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.