• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.44-52
• /
• 2019

We implement an educational indoor autonomous mobile robot system that integrates LiDAR sensing information with RGB-D camera image information and exploits the integrated information. This system uses the existing sensing method employing a LiDAR with a small number of scan channels to acquire LiDAR sensing information. To remedy the weakness of the existing LiDAR sensing method, we propose the 3D structure recognition technique using depth images from a RGB-D camera and the deep learning based object recognition algorithm and apply the proposed technique to the system.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.187-192
• /
• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.161-166
• /
• 2001

학생들에게 사고의 다양성과 창의성을 신장시킬 수 있는 가장 좋은 대안의 하나가 정보통신기술(ICT)을 활용한 수업을 들 수 있는데 아직까지 정보통신 기술을 활용한 수업이 실제적으로 학생들에게 어떠한 인지적, 정의적 영향을 미치는가에 대한 구체적인 연구결과는 없다. 따라서 상호작용이 풍부한 ICT 활용 수업이 정보화 사회가 요구는 자기 주도적 학습 능력을 얼마나 신장시키는지를 규명하기 위해 ICT활용 수업을 실시하기 위한 기초 자료를 제작한 후 홈페이지를 통한 정보 안내하기, 인터넷을 활용한 문제해결학습, 정보분석형 가상실습, 공동 협력 프로젝트 수업, 웹토론형 수업을 실시하여 ICT활용교육이 정보활용, 정보검색 능력, 학업성취도 향상 등에 어떠한 영향을 미치는지를 연구하였다.

• ETRI Journal
• /
• v.45 no.1
• /
• pp.105-118
• /
• 2023

We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

• Journal of the Korean Geographical Society
• /
• v.38 no.2
• /
• pp.275-291
• /
• 2003

It was essential to develop the DB-type teaching and teaming material for geography instruction using a method of ICT. The DB-type teaching and learning material was considered as a alternative in solving the problems of web-based geography instruction. Accordingly, in this study, the geography image DB program as developed, and based on this program the CD-ROM called GEO-DB, having the function of electronic dictionary of geography image for geography teaching and teaming was made. The GEO-DB was composed of 3,060 geography images collected by teachers and learners. The GEO-DB was made to be used simply by teachers and learners. Especially, the portfolio function was Included in the GEO-DB, and that was focused to the instructional system design of teacher and the self-directed teaming ability development of learner. Teachers and learners using this GEO-DB assessed that because the GEO-DB had the easiness of use, the speed of reference and the unlimitedness of extension, it could enlarge the possibility of using a method of In, and it could contribute to the development of geography teaming ability and the change of geography teaming attitude.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1407-1422
• /
• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.679-681
• /
• 2017

현 시점의 대학에서는 기존의 산업기술을 ICT와 창의적으로 융합해 새로운 부가가치를 창출하는 4차 산업혁명에 대비하여 창의적 인재를 양성해야한다. 이를 위해 많은 대학에서는 모든 강의에 플립러닝을 도입하여 적용시키고자 하는 노력이 이루어지고 있다. 본 연구에서는 산업기술과 ICT의 융합에 기본이 되는 프로그램 개발의 핵심 언어라고 할 수 있는 C 언어 수업에 MOOC 시스템을 기반으로 하는 플립러닝을 적용하는 수업을 설계한다. 플립러닝 수업의 경우 자기 주도적 학습이 이루어지지 않을 경우 수업의 효과가 미미할 수 있다. 이러한 문제를 해결하기 위해 학생들의 참여를 능동적으로 이끌어 내고, 학습 이해도를 높이기 위한 방법을 제시하여 플립러닝 수업의 성공적 적용을 이루고자 한다.

• Journal of Advanced Navigation Technology
• /
• v.25 no.1
• /
• pp.96-101
• /
• 2021

This paper presents a machine learning model that predicts stroke risks in atrial fibrillation patients using public big data. As the training data, 68 independent variables including demographic, medical history, health examination were collected from the Korean National Health Insurance Service. To predict stroke incidence in patients with atrial fibrillation, we applied deep neural network. We firstly verify the performance of conventional statistical models (CHADS2, CHA2DS2-VASc). Then we compared proposed model with the statistical models for various hyperparameters. Accuracy and area under the receiver operating characteristic (AUROC) were mainly used as indicators for performance evaluation. As a result, the model using batch normalization showed the highest performance, which recorded better performance than the statistical model.

• Journal of Korean Home Economics Education Association
• /
• v.19 no.2
• /
• pp.77-101
• /
• 2007

The purposes of this study were to develop ICT consumer education program for the second grade middle school students using in the Home Economics and Technology class and to test the effect of this program in terms of learning the knowledge and forming the attitude to be a wise consumer. The contents of a middle school Home Economics curriculum and 10 different textbooks were analyzed. Based on these analyses 5 ICT lesson plans on consumer education were developed. The second grade middle school students as an experimental group participated in 5 ICT consumer education classes during the middle school Home Economics and Technology classes. The control group of students who had same condition with the experimental group were taught by traditional instructional methods. After experiment, the changes in knowledge and attitude to be a wise consumer of both groups were analyzed using Analysis of Covariance. The significant improvements of knowledge and attitude of it were found among the experimental group of students compared with control group of students. Thus the conclusion is that the ICT consumer education program conducted in this study was found to be more effective than traditional one in terms of learning the knowledge and forming the attitude to be a wise consumer.

• Proceedings of the IEEK Conference
• /
• 2003.07d
• /
• pp.1367-1370
• /
• 2003

This paper has been studied Design and Implementation Using the ICT(Information & Communication Technology) Education System on the Web. And then this paper has designed a teaching and learning model for Using the ICT Education System on the Web of management substance in commercial high school, verified and implemented them. After this study, this web-based multimedia data with voice instruction and humanity education data in student's module to develop the local natural environments is more helpful to occur the students' motivations and interests and get higher achievements of study than teach only with the textbook.