• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.4
• /
• pp.83-91
• /
• 2018

Land reclamation, coastal construction, coastline extension and port construction, all of which involve dredging, are increasingly required to meet the growing economic and societal demands in the coastal zone. During the land reclamation, a portion of landfills are lost from the desired location due to a variety of causes, and therefore prediction of sediment transport is very important for economical and efficient land reclamation management. In this study, laboratory disposal tests were performed using an open channel, and suspended sediment transport was analyzed according to flow velocity and grain size. The relationships between the average and standard deviation of the deposition distance and the flow velocity were almost linear, and the relationships between the average and standard deviation of deposition distance and the grain size were found to have high non-linearity in the form of power law. The deposition distribution of sediments was demonstrated to have log-normal distributions regardless of the flow velocity. Based on the experimental results, modeling of suspended sediment transport was performed using deep neural network, one of deep learning techniques, and the deposition distribution was reproduced through log-normal distribution.

• Journal of the Korean Society of Earth Science Education
• /
• v.15 no.1
• /
• pp.47-61
• /
• 2022

In this study, We developed VR (Virtual Reality) geological resources based on the Geo Big Data of the Big Data platform that provided by the Korea Institute of Geoscience and Mineral Material (KIGAM). So students selected the theme of lessons by using these resources and we operated Remote classes using the materials that developed as to Virtual Reality. Therefore, the geological theme maps provided by the Geo Big Data Open Platform were reconstructed and produced materials were created for Study about Real Korean geological outcrops grounded in Virtual Reality. And Topographic information data was used to produce class materials for Remote classes. Twenty students were selected by Random sampling, and data were collected by conducting a survey including interviews to confirm the change in students' perception of remote classes in virtual reality geological data development and the effect of the classes, so data were analyzed through inductive categorization. The results of this study are as follows. First, students showed positive responses in terms of interest, utilization, and knowledge utilization as taking remote classes for developing geological data in virtual reality geological data. This is the result of showing the adaptability of diverse and flexible learning getting away from a fixed framework by motivating and encouraging students and inducing cooperation for communication. Second, students recognized distance education in the development of Virtual Reality geological data as 'Realistic hands-on learning process', 'Immersive learning process by motivation', and 'Learning process of acquiring knowledge in the field of earth science'.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.491-500
• /
• 2021

In this study, we propose a method for detecting fall behavior using MS Kinect v2 RGBD Camera-based Human-Skeleton Keypoints and a 2-Stacked Bi-LSTM model. In previous studies, skeletal information was extracted from RGB images using a deep learning model such as OpenPose, and then recognition was performed using a recurrent neural network model such as LSTM and GRU. The proposed method receives skeletal information directly from the camera, extracts 2 time-series features of acceleration and distance, and then recognizes the fall behavior using the 2-Stacked Bi-LSTM model. The central joint was obtained for the major skeletons such as the shoulder, spine, and pelvis, and the movement acceleration and distance from the floor were proposed as features of the central joint. The extracted features were compared with models such as Stacked LSTM and Bi-LSTM, and improved detection performance compared to existing studies such as GRU and LSTM was demonstrated through experiments.

• Journal of IKEEE
• /
• v.26 no.2
• /
• pp.160-168
• /
• 2022

In this paper, we propose a 3D mesh reconstruction method from a single image using deep learning and a sphere shape transformation method. The proposed method has the following originality that is different from the existing method. First, the position of the vertex of the sphere is modified to be very similar to the 3D point cloud of an object through a deep learning network, unlike the existing method of building edges or faces by connecting nearby points. Because 3D point cloud is used, less memory is required and faster operation is possible because only addition operation is performed between offset value at the vertices of the sphere. Second, the 3D mesh is reconstructed by covering the surface information of the sphere on the modified vertices. Even when the distance between the points of the 3D point cloud created by correcting the position of the vertices of the sphere is not constant, it already has the face information of the sphere called face information of the sphere, which indicates whether the points are connected or not, thereby preventing simplification or loss of expression. can do. In order to evaluate the objective reliability of the proposed method, the experiment was conducted in the same way as in the comparative papers using the ShapeNet dataset, which is an open standard dataset. As a result, the IoU value of the method proposed in this paper was 0.581, and the chamfer distance value was It was calculated as 0.212. The higher the IoU value and the lower the chamfer distance value, the better the results. Therefore, the efficiency of the 3D mesh reconstruction was demonstrated compared to the methods published in other papers.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.79-89
• /
• 2021

Electronic learning (e-learning) empowers the higher education in providing sustainable instruction during the infrequent circumstance when the wide-spreading disastrous challenge of the COVID-19 results in the closure of various sectors in the society. During this time, e-learning serves the levels of the education sector such as higher education well by delivering and receiving materials from distance with respect to movement restrictions imposed by the government, for example the Movement Control Order (MCO) in Malaysia. In this qualitative survey, the existing e-learning challenges and the recommended solutions to the problems from the senior lecturers' perspectives were collected through an online open-ended questionnaire. A number of five senior lecturers out of eight at the Universiti Teknologi Malaysia (UTM) answered the questionnaire. The UTM has been capable of providing e-learning courses for all of its lecturers and students during the closure of higher education institutions owing to the pernicious health conditions stemmed from the crisis of the COVID-19. The major existing challenges found in the e-learning program at the UTM and the suggested solutions to address them are listed and the main themes are illustrated in the word cloud format using the NVivo software. In the end, the conclusion is paragraphed and the future work is proposed. Overall, the purpose of this study is to address the e-learning challenges and to prepare a list of recommendations that can serve as solutions from the standpoint of the UTM senior lecturers during the MCO in Malaysia.

• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.245-251
• /
• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Journal of Research and Publication Ethics
• /
• v.5 no.1
• /
• pp.19-27
• /
• 2024

Purpose: To prevent and respond to youth sexual problems that are becoming more serious with digital development, this study sought to develop a sex education program that applies gamification as an effective method for youth who are digital natives. Research design, data and methodology: To develop a sex education program for teenagers, elements of gamification were considered based on Dick and Kerry's teaching system design model. The learning content reflected UNESCO's 'Comprehensive Sex Education Guidelines'. In addition, it was designed to enable students to learn about ethics and morals from a social and emotional aspect. Results: A four-session distance learning sex education program was developed for first-year high school students. To learn about gender sensitivity, sexual relationships, sexuality, and healthy sexual behavior, we developed a story that reflects the mission and quest for sex education. It included leaderboards, time limits, and levels, and also utilized mechanics such as points and items. Edutech tools include video content, Google Sheets, Zoom, Padlet, and Mentimeter. Conclusions: This study aims to improve learning effectiveness, satisfaction, and immersion by developing a sex education program for youth using gamification that promotes active learner participation and motivation.

• Proceedings of the Ginseng society Conference
• /
• 1998.06a
• /
• pp.1-11
• /
• 1998

Ameliorating mechanisms of red ginseng on learning deficits were investigated in the following 3 experiments; its effects on 1) place learning deficits in aged rats and in young rats with selective hippocampal lesions (behavioral study), 2) long-term potentiation in the hippocampal formation (neuro- physiological study), and 3) ChAT (choline acetyl transferase) activity in various brain regions of aged rats (pharmacological study). In the behavioral study, first, performance in the place learning tasks were compared among 3 groups of young and aged rats; control young intact rats (10-12 week old) treated with water, aged rats (28-32 month old) treated with water, and aged rats (28-32 month old) treated with red ginseng (100 mghglday) suspended in water. Second, performance in the place learning tasks was compared among 3 groups of young rats; control intact rats treated with water, rats with bilateral hippocampal lesions treated with water, and rats with bilateral hippocampal lesions treated with red ginseng (100 mg/kg/day). Each rat in these 2 behavioral experiments was tested with the 3 types of the place learning tasks in a circular open field using intracranial self-stimulation (ICSS) as reward. The ICSS reward was delivered if the rat (1) moved distance of 100-160 cm (DMT): (2) entered an experiment-determined reward place within the open field, and this place was randomly varied in sequential trials (RRPST); or (3) entered 2 specific places, and did a shuttle behavior between the 2 places (PLT). Performance of the aged rats in the ginseng group was not significantly different from that of control young rats in ICSS (current intensity, bar press rates), DMT and RRPST. However, treatment with red ginseng significantly ameliorated place-navigation learning deficits in aged rats in the PLT. Similarly, red ginseng ameliorated learning and memory deficits in young rats with hippocampal lesions in the same tasks. In the neurophysiological study using young rats, perfusion of hippocampal slices with non-sapon in fraction of red ginseng significantly enhanced magnitudes of the long-term potentiation (LfP) in the CA3 subfield. In the pharmacological study, treatment with red ginseng did not affect ChAT activity in aged rat brain including the hippocampal formation. These results strongly suggest that red ginseng ameliorates learning and memory deficits in aged rats through actions on the CA3 subfield of the hippocampal formation, which were independent of the presynaptic components of the cholinergic system

• The Journal of Korean Academic Society of Nursing Education
• /
• v.18 no.2
• /
• pp.323-331
• /
• 2012

Purpose: Level of meta-cognition of students has been regarded as one of the crucial factors on web-based learning. This study aimed to describe interaction type in small group discussion of the nursing graduate students and to investigate learning consequences and interaction types in group discussion on meta-cognition level. Method: Twenty six graduate nursing students attending the class on-line at the K university in Seoul were included in the study. We measured their meta-cognition level and learning attitude. We also scored their individual and group reports as well as analyzed interaction type by reviewing the dialogue of the group discussion. Results: The participants showed low frequency of exploratory interaction and high frequency of integrative interaction in the cognitive interaction category. They showed frequent modification interaction in the meta-cognitive interaction category. Interestingly, the students with lower level of meta-cognition achieved significantly greater scores in the individual assignments. High functioning group consisting of the students with high meta-cognitive level produced greater group report. Conclusion: A new strategy is needed to encourage in-depth interaction in a group discussion of nursing students. Meta-cognitive level of the students should be considered to form a small group for discussion in order to improve group activities.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.397-407
• /
• 2015

The purpose of this study was to investigate the relationships among daily hassles, self-efficacy, and stress responses of RN-BSN (Registered Nurses-Bachelor of Science in Nursing) students in juggling both their jobs and learning as an adult learner of distance education in digital convergence era. The data were collected by a questionnaire from 229 nurses in a RN-BSN course of an open university from October to November, 2013. The mean score of facing task dimension was much higher than the interpersonal dimension score among daily hassles. The academic problem of the facing task and the family relationship of the interpersonal were the highest respectively. The mean score of self-efficacy was slightly higher than the median. Multiple regression showed that perceived health status, workload, occupation satisfaction, and values problem of daily hassles explained 44.2% of stress reponses and values problem was the main factor influencing stress responses. The distance education policies and strategies were required to manage their stress for the adult learners of distance education in digital convergence era.