• Journal of Engineering Education Research
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• v.23 no.3
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• pp.49-58
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• 2020

In the era of the fourth industrial revolution, the world is undergoing rapid social change. The purpose of this study is to predict the expected changes and necessary competencies and desired curriculum and teaching methods in the field of mechanical engineering in the near future. The research method was a Delphi study. It was conducted three times with 20 mechanical engineering experts. The results of the study are as follows: In the field of mechanical engineering, it will be increased the situational awareness by the use of measurement sensors, development of computer applications, flexibility and optimization by user's needs and mechanical equipment, and demand for robots equipped with AI. The mechanical engineer's career perspectives will be positive, but if it is stable, it will be a crisis. Therefore active response is needed. The competencies required in the field of mechanical engineering include collaborative skills, complex problem solving skills, self-directed learning skills, problem finding skills, creativity, communication skills, convergent thinking skills, and system engineering skills. The undergraduate curriculum to achieve above competencies includes four major dynamics, basic science, programming coding education, convergence education, data processing education, and cyber physical system education. Preferred mechanical engineering teaching methods include project-based learning, hands-on education, problem-based learning, team-based collaborative learning, experiment-based education, and software-assisted education. The mechanical engineering community and the government should be concerned about the education for mechanical engineers with the necessary competencies in the era of the 4th Industrial Revolution, which will make global competitiveness in the mechanical engineering fields.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.309-318
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• 2005

Learners show lower cooperation and responsibility at e-Learning(Electronic Learning) than face-to-face learners in class. Accordingly the LMS(Learning Management System) focus on collaborative learning design in order to promote the learner's interaction. In this paper, the Experience Learning Support System with JXTA-based P2P(Peer-to-Peer) architecture is proposed for an effective collaborative learning and a blended learning. It intends learners to develop a self-leading learning ability and a creative problem-solving ability through experience learning object's sharing. The experimental results described that the proposed system was more effective in an enhancing learner's learning ability and a cooperative learning than existing system.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Communications of Mathematical Education
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• v.25 no.1
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• pp.261-288
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• 2011

We examined the effects of pair assistant collaborative learning on academic achievement of the 2nd year middle school students in the three subjects such as the Probability, Properties of Figures and Similarities of Figures. In order to carry out this study, we selected 2 classes of 2nd year students in a girls middle school in the Fall semester of 2009 and set up the experiment group and comparison group by the result of academic achievement tests given in the end of the Spring semester of 2009. Pair assistant collaborative learning was adopted for students in problem solving 2 or 3 times per a week in the experiment group and each academic achievement was given at the end of each subject in both groups. Also, we had a final survey to find out students' attitude to this collaborative learning. The achievement and survey were analysed by statistical methods. We conclude that our pair assistant collaborative learning was effective in Probability and Similarities of Figures Units. According to the result of survey, this collaborative learning brought about an opportunity to promote students' community spirit through reflecting each one's role in the group.

• Journal of Elementary Mathematics Education in Korea
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• v.15 no.1
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• pp.57-75
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• 2011

This research aimed to explore the effects of collaborative writing activities in a mathematical context, specifically pertaining to areas such as numbers and operation, geometrical figure, and measurement in Mathematics: Level 5-b, on their mathematical achievement gain and disposition among Grade 5 students. To do this, out of a total of 62 students selected from two Grade 5 classes of J Elementary School in Dalseo-gu, Daegu City, who were found to be homogenic from the tests of math performance and dispositions, an experimental group(n=31) was designed and compared to a control group (n=31). Over a six week period from October to November in 2009, the experimental group was given collaborative writing lessons in math classes while the control group was given teacher-oriented regular lessons. The results were as follows. First, there was more or less considerable, though not significant, difference in overall mathematical achievement in the students experiencing collaborative writing activities when compared with the students in the control group. However, in terms of numbers and operation, a sub-category of mathematics, there was significant difference between the two groups. Second, the students experiencing collaborative writing activities were more positively affected in all sub-categories of mathematical disposition: confidence, flexibility, determination, curiosity, reflection, and value, than those in the control group. In summing up, the exposure of collaborative writing activities to mathematics learning was found to help students not only to have a concrete and proper grasp of the relevant problem solving process, which was observed from their mathematical achievement gain especially in the sphere of numbers and operation, but also to have their mathematical disposition set towards more positive direction, which was seen in all sub-categories of mathematical disposition measurement.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.149-159
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• 2001

There have been lots of researches for providing a personalized service to a customer using one-to-one marketing and collaborative filtering techniques in E-Commerce. However, there are technical difficulties for providing the recommendation of products far users, which often involve high complexity of computation. In this paper, we have presented an integrated method of classification problem solving method and constraint based configuration techniques. This method can reduce a complexity of computation by classifying a solution domain space that has a higher complexity of composition. Thereafter, we have modeled customers constraints and the components of products to configure a complete system by passing it to constraint processing module in Constraint Satisfaction Problems. Constraint-based configuration uses the constraint propagation using the constraints of buyers and the constraints among PC components to configure a proper product for a customer. We have transformed and applied vector space modeling method in the field of information retrieval to consider a customer satisfaction in addition to the CSP. Finally, we have applied our system to test data fur evaluating a customers satisfaction and performance of the proposed system.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1253-1272
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• 2016

For a nonlinear control system, there are many uncertainties, such as the structural model, controlled parameters and external loads. Although the significant progress has been achieved on the robust control of nonlinear systems through some researches on this issue, there are still some limitations, for instance, the complicated solving process, weak conservatism of system, involuted structures and high order of controllers. In this study, the computational structural mechanics and optimal control theory are adopted to address above problems. The induced norm is the eigenvalue problem in structural mechanics, i.e., the elastic stable Euler critical force or eigenfrequency of structural system. The segment mixed energy is introduced with a precise integration and an extended Wittrick-Williams (W-W) induced norm calculation method. This is then incorporated in the market-based control (MBC) theory and combined with the force analogy method (FAM) to solve the MBC robust strategy (R-MBC) of nonlinear systems. Finally, a single-degree-of-freedom (SDOF) system and a 9-stories steel frame structure are analyzed. The results are compared with those calculated by the $H{\infty}$-robust (R-$H{\infty}$) algorithm, and show the induced norm leads to the infinite control output as soon as it reaches the critical value. The R-MBC strategy has a better control effect than the R-$H{\infty}$ algorithm and has the advantage of strong strain capacity and short online computation time. Thus, it can be applied to large complex structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.579-587
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• 2008

In collaborative environment, since each agent generally uses different words for the same meaning, there is an obstacle for information sharing. In collaborative product development environment, each agent has different words for representing same product information. As a result, it is hard to share product information in this situation. For solving this problem, semantic-based product information is needed. In this paper, a ontology-based semantic searching system which is able to interact with legacy PDM systems is proposed for product information sharing in collaborative environment Product ontology is represented with OWL format, and the product ontology is processed by Pellet reasoning engine for semantic searching. The system is implemented as a web service which can be integrated with other systems. This paper also introduces the approach with which a PDM system provides a function of semantic search with this search system.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.47-53
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• 2021

Sparse ratings data hinder reliable similarity computation between users, which degrades the performance of memory-based collaborative filtering techniques for recommender systems. Many works in the literature have been developed for solving this data sparsity problem, where the most simple and representative ones are the methods of utilizing Jaccard index. This index reflects the number of commonly rated items between two users and is mostly integrated into traditional similarity measures to compute similarity more accurately between the users. However, such integration is very straightforward with no consideration of the degree of data sparsity. This study suggests a novel idea of applying different similarity measures depending on the numeric value of Jaccard index between two users. Performance experiments are conducted to obtain optimal values of the parameters used by the proposed method and evaluate it in comparison with other relevant methods. As a result, the proposed demonstrates the best and comparable performance in prediction and recommendation accuracies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.361-367
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• 2019

This exploratory study investigated the real time adaptability of industry training for college professors. For this study, the researcher whose college's professor in the department of early childhood education used collaborative action research. This research was conducted in a class of five year old children of a daycare center in D city. The researcher and the homeroom teacher interacted with each other through 4 steps during the researcher's training period. The first step was group formation between the researcher and the teacher. The second step was problem identification. The third step was a review of the literature. The forth step was problem-solving. The researcher and teacher finally developed a rhythm movement program that was based on fundamental motor performance of young children. Through this collaborative effort, the researcher and teacher had the opportunity to improve their professionalism. Especially, the researcher improved her understanding and knowledge of teaching young kids. The result of this study is meaningful in that it provided basic data to improve training of college professors.