• Archives of Plastic Surgery
• /
• v.40 no.4
• /
• pp.312-319
• /
• 2013

Over the past decade, driven by advances in educational theory and pressures for efficiency in the clinical environment, there has been a shift in surgical education and training towards enhanced simulation training. Microsurgery is a technical skill with a steep competency learning curve on which the clinical outcome greatly depends. This paper investigates the evidence for educational and training interventions of traditional microsurgical skills courses in order to establish the best evidence practice in education and training and curriculum design. A systematic review of MEDLINE, EMBASE, and PubMed databases was performed to identify randomized control trials looking at educational and training interventions that objectively improved microsurgical skill acquisition, and these were critically appraised using the BestBETs group methodology. The databases search yielded 1,148, 1,460, and 2,277 citations respectively. These were then further limited to randomized controlled trials from which abstract reviews reduced the number to 5 relevant randomised controlled clinical trials. The best evidence supported a laboratory based low fidelity model microsurgical skills curriculum. There was strong evidence that technical skills acquired on low fidelity models transfers to improved performance on higher fidelity human cadaver models and that self directed practice leads to improved technical performance. Although there is significant paucity in the literature to support current microsurgical education and training practices, simulated training on low fidelity models in microsurgery is an effective intervention that leads to acquisition of transferable skills and improved technical performance. Further research to identify educational interventions associated with accelerated skill acquisition is required.

• Journal of Gifted/Talented Education
• /
• v.11 no.3
• /
• pp.245-270
• /
• 2001

Math and Science Olympians participated in a study of the role of environmental influences in their talent development. The questions they got was about family and school factors contribute / or hinder to the development of their scientific talents, and the parents' child rearing styles. The questionnaires were originally developed by Campbell(1996) for cross-cultural studies. The major findings were as follows: ⑴ The professional job of the Olympians'father, the high SES, Their parents'discovering their child's talents were positive factors, ⑵ Their family support and learning environment were reported strong and positive, especially books and reading atmosphere, ⑶ The Olympians participated in the accelerated and enriched educational programs, ⑷ The quality of the class and the rigidity of the curriculum were hindering factors, ⑸ Their parents'rearing style were permissive, affective, and supportive.

• Journal of Engineering Education Research
• /
• v.17 no.4
• /
• pp.43-47
• /
• 2014

The rapid development of science & technology and the globalization of society have accelerated the fractionation and specialization of academic disciplines. Accordingly, Korean colleges and universities are continually dropping antiquated courses to make room for new courses that better meet societal demands. With emphasis placed on providing students with a broader range of choices in terms of course selection, compulsory courses have given way to elective courses. On average, 4 year institutions of higher learning in Korea currently offer somewhere in the neighborhood of 1,000 different courses yearly. The classification of an ever growing list of courses offered and the practical use of such data would not be possible without the aid of computers. For example, if we were able to show the pre/post requisite relationship among various courses as well as the commonalities in substance among courses, such data generated regarding the interrelationship of different courses would undoubtedly greatly benefit the students, as well as the professors, during course registration. Furthermore, the GT system's relatively simple approach to course classification and coding will obviate the need for the development of a more complicated keyword based search engine, and hopefully contribute to the standardization of the course coding scheme in the future..Therefore, as a sample case project, this study will use GT to classify and code all courses offered at the College of Engineering of K University, thereby developing a system that will facilitate the scanning of relevant courses.

• Journal of Gifted/Talented Education
• /
• v.20 no.3
• /
• pp.867-883
• /
• 2010

Recognizing the importance of motivation, goal orientation, and attitudes toward schools is an important component for educators to consider as they establish positive learning communities for gifted learners. The purpose of this study was to describe attitudes toward school and self relationship to schoolwork for students who are enrolled in the 5th, 6th, and 7th grade, identified as gifted, accelerated in at least one subject (mathematics), and living in Korea or the United States. Comparisons were conducted for country of origin and gender for all subscales on the School Attitude Assessment Survey-Revised (McCoach & Siegle, 2004). Of the 507 participants (278 Korean and 229 American), girls scored higher on the motivation/self-regulation scale than boys and American students scored higher than Korean students on attitudes toward school, academic self perceptions, goal orientation, and motivation. There were no differences by country or gender on attitudes toward teachers.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.6
• /
• pp.223-234
• /
• 2021

Recent advances in the 4th Industrial Revolution have accelerated the change of the shopping behavior from offline to online. Search queries show customers' information needs most intensively in online shopping. However, there are not many search query research in the field of search, and most of the prior research in the field of search query research has been studied on a limited topic and data-based basis based on researchers' qualitative judgment. To this end, this study defines the type of search query with data-based quantitative methodology by applying machine learning to search research query field to define the 15 topics of search query by conducting topic modeling based on search query and clicked document information. Furthermore, we present a new classification system of new search query types representing searching behavior characteristics by extracting key variables through principal component analysis and analyzing. The results of this study are expected to contribute to the establishment of effective search services and the development of search systems.

• The Journal of the Korea Contents Association
• /
• v.22 no.7
• /
• pp.540-547
• /
• 2022

Online education is a major trend in the future education change and the COVID-19 pandemic has further accelerated the process. Online education has become an important part of the modern education system because of its stability and continuity. However, the disadvantages of traditional online education can reduce users' experience, thus upgrading online education is the key to future education. Metaverse, as a new platform for online education, redefines the occurrence space of online education, changes the teaching mode and learning and evaluation methods of online education, and shows its development potential. This research analyzed the characteristics of Metaverse and its technological development status, and then proposed an intelligent online education environment construction scheme based focused on Metaverse of art education.

• The Korea Journal of Herbology
• /
• v.30 no.2
• /
• pp.43-48
• /
• 2015

Objectives : The aim of this study was to investigate the memory enhancing properties of extract of Hoelen Cum Radix (HCR) and its possible mechanism in mice of normal condition. Methods : We evaluated the effects of HCR on cognitive function and memory enhancement in normal mice. Male ICR mice were orally administrated with HCR 100 mg/kg for 7 days and equal volume of saline was administrated to the control group in the same condition. We conducted two behavioral tests which measure the spatial working memory (Y-maze test) and cognitive fear memory (passive avoidance test). We also investigated whether HCR affects the hippocampal neurogenesis in the brain. To assess the effects of HCR on neural progenitor cell differentiation and neurite outgrowth in the early stage of hippocampal neurogenesis, we performed doublecortin (DCX), a direct neurogenesis marker, immunohistochemical analysis in the dentate gyrus (DG) of the mouse hippocampus. Results : HCR significantly enhanced memory and cognitive function as determined by the Y-maze test (p<0.05) and passive avoidance test (p<0.001). Moreover, HCR increased DCX positive cells (p<0.01) and neurite length (p<0.01) compared to the control group. These results indicated that HCR stimulates differentiation of neural progenitor cells and promotes neurite outgrowth in hippocampal DG of the mice. Conclusion : We concluded that HCR shows memory enhancing effects through the stimulation of hippocampal neurogenesis as a consequence of accelerated neuronal differentiation and neurite outgrowth in the DG of the hippocampus after HCR treatment.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.10
• /
• pp.299-308
• /
• 2023

As the spectrum shortage problem has accelerated by the emergence of various services, New Radio-Unlicensed (NR-U) has appeared, allowing users who communicated in licensed bands to communicate in unlicensed bands. However, NR-U network users reduce the performance of Wi-Fi network users who communicate in the same unlicensed band. In this paper, we aim to simultaneously maximize the fairness and throughput of the unlicensed band, where the NR-U network users and the WiFi network users coexist. First, we propose an optimal power allocation scheme based on Monte Carlo Policy Gradient of reinforcement learning to maximize the sum of rates of NR-U networks utilizing rate-splitting multiple access in unlicensed bands. Then, we propose a channel occupancy time division algorithm based on sequential Raiffa bargaining solution of game theory that can simultaneously maximize system throughput and fairness for the coexistence of NR-U and WiFi networks in the same unlicensed band. Simulation results show that the rate splitting multiple access shows better performance than the conventional multiple access technology by comparing the sum-rate when the result value is finally converged under the same transmission power. In addition, we compare the data transfer amount and fairness of NR-U network users, WiFi network users, and total system, and prove that the channel occupancy time division algorithm based on sequential Raiffa bargaining solution of this paper satisfies throughput and fairness at the same time than other algorithms.

• (The)Study of the Eastern Classic
• /
• no.37
• /
• pp.377-410
• /
• 2009

In the East Asian Confucianism society, Hakmun was aimed to bring human beings and nature into harmony, and to explore a unity between knowledge and conducts. For example, Neo-Confucianism aspired they could explain the human existence and society through a single concept of Iki(理氣, the basic principles and the atmospheric force of nature). In this philosophy, humanics and natural sciences had not been differentiated at all. The East-West cultural interchanges at the beginning of modernity caused a crack in the traditional academic concepts. Through the Hundred Days of Reform(變法自疆運動, a movement of Strenuous Efforts through Reforming the Law), the Western Affairs Movement(洋務運動) in China, Meiji Restoration(明治維新) in Japan, or Innovation Movements(開化運動) and the Patriotic Enlightenment Movement(愛國啓蒙運動) in Korea, the traditional meanings of Hakmun was degraded while it became a target of the criticism of the enlightenment movements. Accordingly, East Asians' perception of Hakmun rapidly began to change. Although there had been the Silhak(實學, practical science) movement in Korea, which tried to differentiate its conceptualization of Hakmun from that of Neo-Confucianism during the 18th and 19th century, the fundamental shift in meaning occurred with the influx of the modern Western culture. This change converted the ultimate objective of Hakmun as well as its methods and substances. The separation of humanics and natural sciences, rise in dignity of the technological sciences, and subdivision of learning into disciplines and their specialization were accelerated during the Korean enlightenment period. The inflow of the modern western science, humanized thought, and empiricism functioned as mediators in these phase and they caused an irreversible crack in the traditional academic thoughts. Confronting the western mode of knowledge, however, the East Asian intellectuals had to explain their new learning by using traditional terms and concepts; modification was unavoidable when they tried to explain the newly imported knowledge and concepts. This presentation focuses on the traditional concepts of 'gyeogchi'(格致, extending knowledge by investigating things) and 'gungni'(窮理, investigation of principles), pervasively used in philosophy, physics and many other fields of study. These concepts will mark the key point with which to trace changes of knowledge and to understand the way how the concept of Hakmun was converted into a modern one.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.29-45
• /
• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.