• Journal of The Korean Association of Information Education
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• v.16 no.2
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• pp.265-273
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• 2012

Current computer education is moving its focus from using oriented education to improving students' creativity and problem solving ability by computer science education. Robot programming education is becoming a major research issue of computer education in the context of creativity education. One of the mainstream ideas of prior research about robot programming is the effect of robot programming. Another is curriculum development of robot programming. But, the focus of current research is moving toward teaching methods of robot programming. The theme of this research is to use examples in robot programming. Example programs are considered the most useful type of material both by the students and the teachers. Example programs play a important role in learning to program. They work as templates, guidelines, and hints for learners when developing their own programs. In this study, I developed a example-based robot programming support system. Due to the trends of smart learning, I developed this system as a mobile web application.

• Archives of Plastic Surgery
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• v.44 no.3
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• pp.223-227
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• 2017

Background Carpal tunnel release is one of the most common surgical procedures performed by hand surgeons. The authors created a surgical simulation of open carpal tunnel release utilizing a mobile and rehearsal platform app. This study was performed in order to validate the simulator as an effective training platform for carpal tunnel release. Methods The simulator was evaluated using a number of metrics: construct validity (the ability to identify variability in skill levels), face validity (the perceived ability of the simulator to teach the intended material), content validity (that the simulator was an accurate representation of the intended operation), and acceptability validity (willingness of the desired user group to adopt this method of training). Novices and experts were recruited. Each group was tested, and all participants were assigned an objective score, which served as construct validation. A Likert-scale questionnaire was administered to gauge face, content, and acceptability validity. Results Twenty novices and 10 experts were recruited for this study. The objective performance scores from the expert group were significantly higher than those of the novice group, with surgeons scoring a median of 74% and medical students scoring a median of 45%. The questionnaire responses indicated face, content, and acceptability validation. Conclusions This mobile-based surgical simulation platform provides step-by-step instruction for a variety of surgical procedures. The findings of this study help to demonstrate its utility as a learning tool, as we confirmed construct, face, content, and acceptability validity for carpal tunnel release. This easy-to-use educational tool may help bring surgical education to a new- and highly mobile-level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.632-634
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• 2013

Subjects that require the creation of lecture and tour diary system and on-the-spot investigation in class of educational institutions universities and smart the current era has increased. At this point, it is intended to ensure the convenience of the process of teaching the specified one by one, to create a history of the data. In this paper, we devised a work by introducing a system for authentication of the material and of such as tours and systems on-the-spot investigation in the various modules and position information of Android, to simplify a more convenient reporting and learning environment.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1226-1236
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• 2022

Because students majoring in construction-related fields must develop a broad repository of knowledge and skills, effective transferal of these is the primary focus of most academic programs. While inculcation of this body of knowledge is certainly critical, actual construction projects are complicated ventures that involve levels of risk and uncertainty, such as resistant neighboring communities, unforeseen weather conditions, escalating material costs, labor shortages and strikes, accidents on jobsites, challenges with emerging forms of technology, etc. Learning how to develop a level of discernment about potential ways to handle such uncertainty often takes years of costly trial-and-error in the proverbial "school of hard knocks." There is therefore a need to proactively expedite the development of a sharpened intuition when making decisions. The AGC Education and Research Foundation case study committee was formed to address this need. Since its inception in 2011, 14 freely downloadable case studies have thus far been jointly developed by an academics and industry practitioners to help educators elicit varied responses from students about potential ways to respond when facing an actual project dilemma. AGC case studies are typically designed to focus on a particular concern and topics have thus far included: ethics, site logistics planning, financial management, prefabrication and modularization, safety, lean practices, preconstruction planning, subcontractor management, collaborative teamwork, sustainable construction, mobile technology, and building information modeling (BIM). This session will include an overview of the history and intent of the AGC case study program, as well as lively interactive demonstrations and discussions on how case studies can be used both by educators within a typical academic setting, as well as by industry practitioners seeking a novel tool for their in-house training programs.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.28-34
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• 2010

In this paper, we proposed an algorithm for utilizing visual information for non-contact predicting method of friction coefficient. Coefficient of friction is very important in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. The proposed method, non-contacting approach, has advantage over other methods that extract material characteristic of road by sensors contacting road surface. This method is composed of learning group(experiment, grouping material) and predicting friction coefficient group(Bayesian classification prediction function). Every group include previous work of vision. Advantage of our algorithm before entering such terrain can be very useful for avoiding slippery areas. We make experiment on measurement of friction coefficient of terrain. This result is utilized real friction coefficient as prediction method. We show error between real friction coefficient and predicted friction coefficient for performance evaluation of our algorithm.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.