• 공학교육연구
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• 제23권3호
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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.

• 디지털융복합연구
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• 제15권4호
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• pp.451-459
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• 2017

언어학습 도구로서 스마트폰은 강의실 밖과 비교했을 때 수업시간에 활용되는 경우는 흔하지 않다. 따라서 본 연구의 목적은 영어 듣기의 수업 활동에서 스마트폰의 유용성을 파악하는 것이다. 71명의 학생들이 한 학기 동안 Practical English Listening and Reading 과목에서 개별적으로 스마트폰을 이용하여 듣기 활동을 하였다. 학기 말에 학생들은 스마트폰 활동에 관한 10문항의 설문에 응답하였다. 설문을 분석한 결과 스마트폰을 이용한 듣기 활동은 학생들의 영어 듣기에 대한 흥미를 유발하였으며 개인별 맞춤 학습으로서 듣기 능력을 향상시키는 효과를 가져왔다. 그런데 스마트폰이 지닌 다른 기능들이 학생들의 듣기 활동을 방해한다는 사실이 스마트폰 활용의 가장 큰 단점으로 나타났다. 이를 해결하기 위해 듣기 활동을 모두 스마트폰 활동으로 할 것이 아니라 강의실 컴퓨터를 사용한 전체 활동도 병행할 것을 제안한다. 학생들이 원하는 혼합율은 50대 50 이었다. 학생 집단의 수준에 따라 그 혼합율은 달라질 수 있을 것이다. 이러한 연구결과는 디지털 융합 영어학습을 활성화하는데 기여할 것이다.

• 한국정보통신학회논문지
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• 제12권7호
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• pp.1329-1337
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• 2008

최근 학교교육 현장에서는 교수-학습의 효과 극대화를 위하여 교육정보화 사업이 추진되고 있다. 이를 위하여 교육인적자원부는 컴퓨터 기반 수업(CAI)을 지원하고 학습자가 인지적 구조를 구성할 수 있는 학습 환경 조성을 위해 우수한 교육용 소프트웨어를 개발.보급하여 활용할 수 있도록 지원하고 있다. 학교에서는 소프트웨어 구입에 따라 매년 그 보유수가 늘어나고 있으며, 이에 따른 교육용 소프트웨어의 효율적인 관리에 대한 필요성이 증대되고 있다. 이에 본 논문에서는 교육용 소프트웨어를 교수 학습용 소프트웨어, 업무지원용 소프트웨어, 시스템 관리 소프트웨어 등 3가지로 분류하여 등록하고 사용자별 사용 구분을 두어 보다 효과적으로 시스템을 사용할 수 있는 방법을 제안하고 구현한다. 시스템의 사용자 구분은 회원 가입을 통하여 로그인 하도록 하고, 로그인 후 관리자 모듈, 일반교사 모듈, 학생 모듈로 나누고 관리자는 자료의 등록, 수정, 검색 등 모든 관리를 한다. 일반 교사는 각 소프트웨어의 검색 및 열람이 가능하여 수업 시간에도 적절히 교육용 소프트웨어를 사용한 컴퓨터 기반 수업이 이루어 질 수 있도록 하였다. 학생은 교수 학습용 소프트웨어에 대한 검색 및 열람을 가능하게 하여 언제든지 수업 내용에 대한 예습 복습이 이루어 질 수 있도록 하였다.

• Korean Journal of Radiology
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• 제21권7호
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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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• 제17권4호
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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.

• 한국과학교육학회지
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• 제11권1호
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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.

• 정보교육학회논문지
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• 제10권1호
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• pp.155-161
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• 2006

유비퀴터스 로봇은 인간과 로봇 상호작용 즉 HRI를 통해 정보매체로 진화하고 있음에 따라, 최근 들어 로봇을 이용한 학습은 다른 매체보다 친근하고 동기유발에 효과적으로 나타나 로봇의 교육적 활용 연구가 시작되고 있다. 이에 본 연구에서는 교실에서 교육매체로서 교사 보조 로봇의 수업에서의 활용 가능성을 보기 위해, 초등학생 6학년의 기대역할을 갖는 프로토타입 로봇을 설계 개발하여 영어, 음악, 국어교과목 수업에 활용하는 실험을 $4{\sim}5$학년을 대상으로 실시하였다. 이를 통해 아동이 로봇에게 기대하는 역할이 실험자의 의도와 일치하는지와 교육적 효과 제고에 기여를 하는지를 알아보고자 하였다. 그 결과, 아동은 교사 보조 로봇을 자신보다 약간 높은 나이로 인식하고, 친근하지만 자신보다 우월하여 자신을 이끌어 줄 수 있는 역할을 기대한다는 것을 알 수 있었다. 또한 교사 보조 로봇 활용이 교사와 아동의 흥미 유발에 있어 매우 효과적임을 보여, 향후 교사 보조 로봇은 ICT 활용 교육의 또 다른 매체로서의 가능성을 확인하였다.

• Imaging Science in Dentistry
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• 제52권4호
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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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• 제17권1호
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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.

• 대한간호학회지
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• 제30권4호
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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.