• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.383-390
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• 2021

Recently, the drone industry is rapidly expanding as it is suggested that it will be used in various fields. As the size of the drone market grows, interest in drone-related certificates is also increasing. However, the current drone-related qualification system and education system are insufficient. Thus this study, analyzed the necessity of drone training, the features of functional games, and the effectiveness of educational training using AR through related technical studies to solve the practical difficulties of drone educational training. Later, drone educational training game contents using AR were divided into practice mode and test mode based on the drone national qualification course practical test, and the result screen was displayed at the end of the curriculum so that players could learn by level and evaluate the results on their own. In addition, constructed a hybrid processing system and network and AR operation system for response rate and response speed, implemented drone training game contents utilizing AR based on the design contents. It is expected that the use of game content using AR presented in this paper for drone training will further alleviate environmental difficulties and improve the sense of immersion in play, which will lead to a more effective drone educational training experience.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.328-334
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• 2022

The process that one may consciously focuses on necessary stimulation among tremendous amount of stimulation through human sensory systems is called attention in psychology. It is known that the attention can be affected by many factors such as room temperatures, humidity level, etc. In the field of sports science, ice packs are widely used for recovery from exercise fatigue providing fast heat transfer by conduction. However, the effect on attention by so-called iced-pack-cooling has not been tested. This research focuses on the attention levels when one is provided with a special cooling pad on their dorsal and lateral cervices. 40 subjects were divided into four groups and their attention level was evaluated based on the exposure conditions of combinations in reading and light walking with and without the cooling pad. The Frankfruter Aufmerksamkeits-Inventar, FAIR was used to evaluate the attention levels; the performance index, quality index, and continuity index consist of the FAIR test indicating the selectiveness of the attention, correctness of the attention, and maintaining term of the attention, respectively. Analysis of variance was carried out for those variables and post-hoc if applicable. When visual attention is constantly used for reading and studying, application of conductive heat transfer by the cooling pads is significantly helpful for improvement in selectiveness of the attention and maintaining terms of the attention levels. Also, light walking yielded improvement in selectiveness of the attention and maintaining terms of the attention levels; however one should presupposedly consider the loss of reading time.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.1
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• pp.33-47
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• 2021

This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.225-236
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• 2019

Viewing and approaching problems based on computational thinking can be improved through informatics education, which is essential for students to live in a future society. The purpose of this study is to analyze the operation status of informatics subjects that have become general electives in the 2015 revised curriculum, and to contribute to enhancing the effect of future informatics subject. To achieve this goal, a questionnaire was conducted for 400 students who graduated from high school in 2015-2016, and five students and five informatics subjects teachers were interviewed. Operation period of Infomatics subject, contents, method and evaluation method were analyzed. As a result, the operation of informatics subjects varied greatly from the second semester of the first year to the second semester of the third year. The most common method was teaching type, but the percentage of self-study was high in the second semester of the third year. The contents of the study did not learn all the contents, and the use rate of textbooks was low in the class. This study confirmed that the informatics subject class did not proceed in the form of observing the curriculum similarly to other subjects excluded. It is also significant that for the first time, the operational status of informatics subjects was analyzed.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.703-709
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• 2023

It is most desirable to train with a real crane in an environment similar to that of a port for crane operation training in charge of loading and unloading in a port, but it has time and space limitations and cost problems. In order to overcome these limitations, VR(Virtual Reality) based crane training programs and related devices are receiving a lot of attention. In this paper, we designed and implemented a VR-based harbor crane simulator operating on an HMD. The simulator developed in this paper consists of a crane simulator program that operates on the HMD, an IoT driving terminal that processes trainees' crane operation input, and a training server that stores trainees' training information. The simulator program provides VR-based crane training scenarios implemented with Unity3D, and the IoT driving terminal developed based on Arduino is composed of two controllers and transmits the user's driving operation to the HMD. In particular, the crane simulator in this paper uses a training server to create a database of environment setting values for each educator, progress and training time, and information on driving warning situations. Through the use of such a server, trainees can use the simulator in a more convenient environment and can expect improved educational effects by providing training information.

• Education of Primary School Mathematics
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• v.26 no.3
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• pp.163-180
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• 2023

This study aimed to investigate the factors influencing the intentions of elementary school teachers to use artificial intelligence (AI) in mathematics lessons and to identify the essential prerequisites for the effective implementation of AI in mathematics education. To achieve this purpose, we examined the structural relationship between elementary school teachers' TPACK(Technological Pedagogical Content Knowledge) and the TAM(Technology Acceptance Model) using structural equation model. The findings of the study indicated that elementary school teachers' TPACK regarding the use of AI in mathematics instruction had a direct and significant impact on their perceived ease of use and perceived usefulness of AI. In other words, when teachers possessed a higher level of TPACK competency in utilizing AI in mathematics classes, they found it easier to incorporate AI technology and recognized it as a valuable tool to enhance students' mathematics learning experience. In addition, perceived ease of use and perceived usefulness directly influenced the attitudes of elementary school teachers towards the integration of AI in mathematics education. When teachers perceived AI as easy to use in their mathematics lessons, they were more likely to recognize its usefulness and develop a positive attitude towards its application in the classroom. Perceived ease of use, perceived usefulness, and attitude towards AI integration in mathematics classes had a direct impact on the intentions of elementary school teachers to use AI in their mathematics instruction. As teachers perceived AI as easy to use, valuable, and developed a positive attitude towards its incorporation, their intention to utilize AI in mathematics education increased. In conclusion, this study shed light on the factors influencing elementary school teachers' intentions to use AI in mathematics classes. It revealed that teachers' TPACK plays a crucial role in facilitating the integration of AI in mathematics education. Additionally, the study emphasized the significance of enhancing teachers' awareness of the advantages and convenience of using AI in mathematics instruction to foster positive attitudes and intentions towards its implementation. By understanding these factors, educational stakeholders can develop strategies to effectively promote the utilization of AI in mathematics education, ultimately enhancing students' learning outcomes.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.42-42
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• 2022

지금까지도 유역에서의 녹조 모니터링은 현장채수를 통한 점 단위 모니터링에 크게 의존하고 있어 기후, 유속, 수온조건 등에 따라 수체에 광범위하게 발생하는 녹조를 효율적으로 모니터링하고 대응하기에는 어려운 점들이 있어왔다. 또한, 그동안 제한된 관측 데이터로 인해 현장 측정된 실측 데이터 보다는 녹조와 관련이 높은 NDVI, FGAI, SEI 등의 파생적인 지수를 산정하여 원격탐사자료와 매핑하는 방식의 분석연구 등이 선행되었다. 본 연구는 녹조의 모니터링시 정확도와 효율성을 향상을 목표로 하여, 우선은 녹조 측정장비를 활용, 7000개 이상의 녹조 관측 데이터를 확보하였으며, 이를 바탕으로 동기간의 고해상도 위성 자료와 실측자료를 매핑하기 위해 다양한Machine Learning기법을 적용함으로써 그 효과성을 검토하고자 하였다. 연구대상지는 낙동강 내성천 상류에 위치한 영주댐 유역으로서 데이터 수집단계에서는 면단위 현장(in-situ) 관측을 위해 2020년 2~9월까지 4회에 걸쳐 7291개의 녹조를 측정하고, 동일 시간 및 공간의 Sentinel-2자료 중 Band 1~12까지 총 13개(Band 8은 8과 8A로 2개)의 분광특성자료를 추출하였다. 다음으로 Machine Learning 분석기법의 적용을 위해 algae_monitoring Python library를 구축하였다. 개발된 library는 1) Training Set과 Test Set의 구분을 위한 Data 준비단계, 2) Random Forest, Gradient Boosting Regression, XGBoosting 알고리즘 중 선택하여 적용할 수 있는 모델적용단계, 3) 모델적용결과를 확인하는 Performance test단계(R², MSE, MAE, RMSE, NSE, KGE 등), 4) 모델결과의 Visualization단계, 5) 선정된 모델을 활용 위성자료를 녹조값으로 변환하는 적용단계로 구분하여 영주댐뿐만 아니라 다양한 유역에 범용적으로 적용할 수 있도록 구성하였다. 본 연구의 사례에서는 Sentinel-2위성의 12개 밴드, 기상자료(대기온도, 구름비율) 총 14개자료를 활용하여 Machine Learning기법 중 Random Forest를 적용하였을 경우에, 전반적으로 가장 높은 적합도를 나타내었으며, 적용결과 Test Set을 기준으로 NSE(Nash Sutcliffe Efficiency)가 0.96(Training Set의 경우에는 0.99) 수준의 성능을 나타내어, 광역적인 위성자료와 충분히 확보된 현장실측 자료간의 데이터 학습을 통해서 조류 모니터링 분석의 효율성이 획기적으로 증대될 수 있음을 확인하였다.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.619-626
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• 2019

This study was conducted to investigate the effects of a participatory rehabilitation program on sit-rise and rise-to-walk test performances, and perception and motor skills in adults with medically vulnerable individuals and, adults with developmental disabilities in particular. Seventeen adults with developmental disabilities participated in a participatory rehabilitation program using resistance bands and exercise balls, for 60 minutes once weekly over 13 weeks. Their performances were measured before and immediately after the intervention, and 12 weeks after. The findings were as follows. In the sit-rise test, the number of times rising from sitting posture increased after the intervention versus before, but the difference was not statistically significant. In the rise-to-walk test, the performance showed statistically significant difference over time, and the post-hoc test showed a significant effect after the intervention versus before. There was no significant difference in perception and motor skills. In sum, the participatory rehabilitation program positively influenced dynamic balancing related to functional activities but had no significant effect on perception and motor skills, which is related to motor control and motor learning. It is suggested that to increase the participation in community activities, reduce fall risk, and improve dynamic balancing abilities in adults with developmental disabilities, participatory rehabilitation programs should be utilized to promote the physical wellbeing.

• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.11-20
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• 2023

In this paper, we propose a novel deep learning-based motion reconstruction approach that facilitates the generation of full-body motions, including finger motions, while also enabling the online adjustment of motion generation delays. The proposed method combines the Vive Tracker with a deep learning method to achieve more accurate motion reconstruction while effectively mitigating foot skating issues through the use of an Inverse Kinematics (IK) solver. The proposed method utilizes a trained AutoEncoder to reconstruct character body motions using tracker data in real-time while offering the flexibility to adjust motion generation delays as needed. To generate hand motions suitable for the reconstructed body motion, we employ a Fully Connected Network (FCN). By combining the reconstructed body motion from the AutoEncoder with the hand motions generated by the FCN, we can generate full-body motions of characters that include hand movements. In order to alleviate foot skating issues in motions generated by deep learning-based methods, we use an IK solver. By setting the trackers located near the character's feet as end-effectors for the IK solver, our method precisely controls and corrects the character's foot movements, thereby enhancing the overall accuracy of the generated motions. Through experiments, we validate the accuracy of motion generation in the proposed deep learning-based motion reconstruction scheme, as well as the ability to adjust latency based on user input. Additionally, we assess the correction performance by comparing motions with the IK solver applied to those without it, focusing particularly on how it addresses the foot skating issue in the generated full-body motions.

• Journal of The Korean Association For Science Education
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• v.26 no.2
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• pp.212-221
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• 2006

The purposes of this study were to examine the characteristics of teacher help in small group Thinking Science(TS) activities and analyze the way students respond to teacher help. For this study, twenty-four 5th grade and twenty-four 7th grade students were selected, to undertake TS activities. Out of the 8 activities students participated in, the verbal interactions in activity 4 and 6, by students in four small groups, which incorporated relatively active argumentation was analyzed. Students' cognitive level was identified through a science reasoning task and the students were grouped heterogeneously according to their cognitive level. This study showed that teachers predominately used simple confirmation questions in preference to metacognitive question. Also, teacher help varied according to one's personal traits, work experience and degree of activity recognition. It was discovered that when the teacher provided student appropriate metacognitive questions and sufficient feedback, students actively engaged in argumentation. On the other hand, when the teacher asked simple confirmation questions and interfered in the activity, students did not participate in argumentation actively.