• 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.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.451-459
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• 2017

This study investigates the usage of smartphones in English listening activities. 71 students answered the 10-item questionnaire after doing listening activity using their own smartphone for one semester in the course of Practical English listening and reading. The findings show that listening activity done with smartphone enhanced students' interest in English listening and improved their English listening skills because smart phones made customized learning possible. However, the major limitation of using smart phone is that students are distracted during activity by smart phones' other functions such as SMS and messenger. To reduce such distraction, I suggest that individual listening activity with smart phones be mixed with instructor-led activity using a classroom computer in about 50 to 50 ratio. The ratio might vary depending on the level of students' English listening skills. These findings will make a contribution to the boost of digital convergence English learning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1329-1337
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• 2008

The project of Education information is promoted to maximize the efficiency of Teaching-Learning at schools. So Ministry of Education & Human Resources Development develops and spreads the Computer Assisted Instruction(CAI) and outstanding Educational Software to help learners who can utilize this software and make learning environment to form their own recognition. As the number of this software is increased, the necessity of management of Educational Software is required. This study divides Educational Software into three kinds, teaching-learning software, business management software, and system management software, and suggests how to use these softwares effectively according to this division. After the users log into the system through joining members, they are divided into manager module, teachers module, and students module. The manager manages all software like registration, revision, reference of date and so on. The teacher accesses properly. The student accesses teaching-learning software and prepares and reviews his lessons at any time.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.891-899
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• 2020

Objective: To assess the diagnostic performance of a deep learning-based algorithm for automated detection of acute and chronic rib fractures on whole-body trauma CT. Materials and Methods: We retrospectively identified all whole-body trauma CT scans referred from the emergency department of our hospital from January to December 2018 (n = 511). Scans were categorized as positive (n = 159) or negative (n = 352) for rib fractures according to the clinically approved written CT reports, which served as the index test. The bone kernel series (1.5-mm slice thickness) served as an input for a detection prototype algorithm trained to detect both acute and chronic rib fractures based on a deep convolutional neural network. It had previously been trained on an independent sample from eight other institutions (n = 11455). Results: All CTs except one were successfully processed (510/511). The algorithm achieved a sensitivity of 87.4% and specificity of 91.5% on a per-examination level [per CT scan: rib fracture(s): yes/no]. There were 0.16 false-positives per examination (= 81/510). On a per-finding level, there were 587 true-positive findings (sensitivity: 65.7%) and 307 false-negatives. Furthermore, 97 true rib fractures were detected that were not mentioned in the written CT reports. A major factor associated with correct detection was displacement. Conclusion: We found good performance of a deep learning-based prototype algorithm detecting rib fractures on trauma CT on a per-examination level at a low rate of false-positives per case. A potential area for clinical application is its use as a screening tool to avoid false-negative radiology reports.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2337-2339
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• 2016

Electronic presentations have become useful tools for surgeons, other clinicians and patients, facilitating medical and legal support and scientific research. Microsoft(R) PowerPoint is by far and away the most commonly used computer-based presentation package. Setting up surgical clinical cases with PowerPoint makes it easy to register and follow patients for the purpose of discussion of treatment plan or scientific presentations. It facilitates communication between professionals, supervising clinical cases and teaching. It is ofter useful to create a template to standardize the presentation, offered by the software through the slide master. The purpose of this paper was to show a simple and practical method for creating a Microsoft(R) PowerPoint template for use in presentations comcerning oral and maxillofacial cancer.

• Journal of The Korean Association For Science Education
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• v.11 no.1
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• pp.37-50
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• 1991

The CAI (Computer-Assisted Instruction) system for science teaching has been increasing both in quantity and in quality during the last two decades. However, science learning by computer has not played a leading role in the science teaching process. Therefore, the purpose of this study was to analyze the effectiveness of tutorial CAI programs according to the learner's characteristics such as sex, inquiry skills, attitudes toward science subject, logical thinking skills, achievement motivation, science content achievement in science teaching. One group pretest-posttest design was used as an experimental design. The three tutorial science CAI programs were used for thirty males and females selected in grade eight. According to the analysis of CAI achievement scores the female students showed significantly higher (P<0.05) than the male students. Also, one-way analysis of variance was used to investigate the effects of interaction between sex and achievement motivation. The significant difference on the effects of interaction between sex and achievement motivation has not found. The effects of tutorial CAI between logical thinking skills, attitudes toward science subject, inquiry skills, achievement motivation, science content achievement according to upper and lower levels were investigated by using the statistical analysis of one-way ANOVA. The results indicate that tutorial CAI might provides a good opportunities for the improvement of science achievement to the lower level students of attitudes toward science subject, inquiry skills, science content achievement.

• Journal of The Korean Association of Information Education
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• v.10 no.1
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• pp.155-161
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• 2006

Robots evolve from tools to information media since they generates information by interacting with human. As studies on robot-aided education are still in a starting phase, attempts need to be made to use robots for educational purposes and to investigate the effects of the use. It was showed that robot-aided learning was friendlier than other media assisted learning, and especially effective for motivating children. We developed the prototype robot Jenny that can help teachers as a educational media in class(i.e. as a T.A. robot, it can present robot contents on its chest to screen and explain about it when teacher asks). is a schoolmate for 5th or 6th grade children or an elder schoolmate for the rest. We performed the field trial at an elementary school. We carried out 9 classes for three subjects(english, korean, music) with -students in $4th{\sim}5th$ grade. They thought Jenny who was 13 years old as an elder schoolmate in 6th grade. Also, a significant difference was found in the interest and concentration of experimental groups from controlled groups.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.239-260
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• 2023

The underwater acoustic wireless communication networks are generally formed by the different autonomous underwater acoustic vehicles, and transceivers interconnected to the bottom of the ocean with battery deployed modems. Orthogonal frequency division multiplexing (OFDM) has become the most popular modulation technique in underwater acoustic communication due to its high data transmission and robustness over other symmetrical modulation techniques. To maintain the operability of underwater acoustic communication networks, the power consumption of battery-operated transceivers becomes a vital necessity to be minimized. The OFDM technology has a major lack of peak to average power ratio (PAPR) which results in the consumption of more power, creating non-linear distortion and increasing the bit error rate (BER). To overcome this situation, we have contributed our symmetry research into three dimensions. Firstly, we propose a machine learning-based underwater acoustic communication system through long short-term memory neural network (LSTM-NN). Secondly, the proposed LSTM-NN reduces the PAPR and makes the system reliable and efficient, which turns into a better performance of BER. Finally, the simulation and water tank experimental data results are executed which proves that the LSTM-NN is the best solution for mitigating the PAPR with non-linear distortion and complexity in the overall communication system.

• Journal of Korean Academy of Nursing
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• v.30 no.4
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• pp.1035-1044
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• 2000

The purpose of this study was to develop and evaluate an internet based program for nursing informatics. The course subject, Nursing Informatics, was made by a computerized instructional module using the internet. The program was developed after taking into consideration the level of competence and knowledge in the subjects. It was based on 10 steps of the CAI module developed by Alessi and Trollip. The subjects consisted of 76 junior nursing students taking a Nursing Informatics course. Two sets of questionnaires were used for this study. First, a questionnaire was administered to 76 students to collect general information on their experience while using computers and the internet. Secondly, another questionnaire was administrated to 76 students after they took the course. They were asked to evaluate the program in terms of easiness of use, precision of contents, freshness of contents, motivation in learning, effectiveness of learning, enhancement of communication, precision of screen, and interest in the contents. IDs and passwords were given to the students. The students were asked to write their IDs and passwords when they connected to Nursing Informatics (http://hallym.ac.kr/~yhyom/ inform.html). They were led the menu page which was categorized into 8 icons (i. e., syllabus, lecture notes, quick test, Q & A board, assignment, on-line test, related web sites and mailing lists) after confirming their IDs and passwords. The students' responses were very positive. This program was a very useful in increasing the effectiveness of learning and motivation in the students. Suggest to be use for other nursing courses.