• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.107-114
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• 2021

The purpose of this study is to investigate whether there is a difference in the effect of learning flow and teaching presence according to the lecturer's appearance and students' behavioral patterns in video learning. For this experiment, 183 freshmen from Xingtai University in China were selected as subjects. After being classified according to DISC, students were assigned to study the lecture videos with the appearance of the lecturer and the video without the appearance of the lecturer. After testing the level of their learning flow and teaching presence, the differences between groups were analyzed. According to the results of the analysis, the learning flow and teaching presence of groups who learned the videos in which the lecturer appeared were significantly higher than the groups who learned the videos without the appearance of the lecturer. Second, the effects of whether the lecturer appears or not according to DISC on learning flow were significant. However, the effects of DISC, and the interactive effect of DISC and the lecturer appearance were found to have no significant interactive effect on learning flow. Third, the effects of whether the lecturer appears or not according to DISC on teaching presence were significant, and the effects of DISC on teaching presence were not significant, but the interactive effect of lecturer appearance and DISC was significant. These findings suggest that lecture videos with the appearance of the lecturer generally have better effect. In particular, in order to enhance teaching presence, it is effective to decide whether the lecturer appears or not by considering its interactive effects with learners' DISC.

• ETRI Journal
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• v.41 no.4
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• pp.483-493
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• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.267-274
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• 2021

The purpose of this study is to investigate differences in learning flow and teaching presence according to the lecturer's appearance and the lecturer's speech rate. For this experiment, 183 freshman students from Xingtai University in China were selected as subjects of the experiment, and a total of four types of lecture videos were developed to test the lecturer's appearance and their speech rates. Data was analyzed through multivariate analysis of variance. According to the results of the analysis, first, learning flow and teaching presence of groups who experienced the presence of the lecturer appeared were significantly higher than the groups who learned without the appearance of the lecturer. Second, the groups who learned from videos with a fast speech rate showed higher learning flow and teaching presence than the group who learned at a slow speech rate. Third, there were no significant differences in both learning flow and teaching presence according to the lecturer's appearance and speech rate. This result provides a theoretical and practical basis for developing customized videos according to learners' characteristics.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.20-28
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• 2015

In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.

• Journal of Korean Society for Quality Management
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• v.43 no.2
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• pp.201-218
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• 2015

Purpose: This study surveyed the effects of instructors' verbal and nonverbal communication quality on students' learning flow and satisfaction. We divided the two types of communication into sub-factors - verbal communication into language, and nonverbal communication into kinesics, proxemics, paralanguage and physical appearance - to examine the causal relationship between learning flow and learning satisfaction. Methods: This study was conducted on the students (parents) of a paid early childhood education program run by "I" company located in Seoul, from November 12, 2014 to November 18, 2014. A total of 317 (90.5 %, effective) questionnaires were collected and analyzed using SPSS 18.0 and AMOS 18.0. Results: First, the verbal communication of the lecturers was found to have significantly positive (+) effects on learning satisfaction. Second, among the nonverbal communications, proxemics and physical appearance were found to have positive (+) effects on learning flow. Third, among the nonverbal communications, proxemics was found to have positive (+) effects on learning satisfaction. Fourth, the learning flow of students was found to have positive (+) effects on learning satisfaction. Conclusion: This study's findings can contribute to realizing desirable communication between instructors and students.

• The Journal of Korean Medicine
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• v.30 no.2
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• pp.1-16
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• 2009

Objectives: This study investigated the effect of Yukmijihwangtang on cerebral ischemia-induced learning and memory impairment by middle cerebral artery (MCA) occlusion in rats. Methods: The ability of learning and memory of rats was measured using the eight-arm radial maze and the passive avoidance test, and profile of cholinergic neuron was assessed in the medial septum and hippocampus region by immuno-histochemistry. Results: 1. No differences were found between groups in the number of correct choices in acquisition performance during the eight-arm radial maze task. 2. No differences were found between groups on day 1 in the error rate in acquisition performance, which is defined as the number of enters into the same arm more than once within five minutes. After 5 to 6 days of test, the number of errors was significantly reduced in the Yukmijihwangtang group (forebrain ischemia group with Yukmijihwangtang treatment), compared with the ischemia group. 3. The memory processes significantly improved in the Yukmijihwangtang group according to results of the passive avoidance test. 4. The appearance of AchE (acetylcholinesterase) in the CA1 region of hippocampus significantly decreased in the ischemia group, compared with the sham group (untreated group). The appearance of AchE in the same region significantly increased in the Yukmijihwangtang group, compared with the ischemia group. 5. The appearance of ChAT (choline acetyltransferase) in the CA1 region of the hippocampus and medial septum decreased in the ischemia group, compared with the sham group. The appearance of ChAT in the same region significantly increased in the Yukmijihwangtang group, compared with the ischemia group Conclusions: This study provides evidence that Yukmijihwangtang is effective for reviving the ability of learning and memory and damaged neurons in rats with experimental cerebral ischemia.

• Smart Media Journal
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• v.11 no.8
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• pp.84-92
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• 2022

Precision livestock monitoring promises greater management efficiency for farmers and higher welfare standards for animals. Recent studies on video-based animal activity recognition and tracking have shown promising solutions for understanding animal behavior. To achieve that, surveillance cameras are installed diagonally above the barn in a typical cattle farm setup to monitor animals constantly. Under these circumstances, tracking individuals requires addressing challenges such as occlusion and visual appearance, which are the main reasons for track breakage and increased misidentification of animals. This paper presents a framework for multi-cattle tracking in closed barns with appearance and motion models. To overcome the above challenges, we modify the DeepSORT algorithm to achieve higher tracking accuracy by three contributions. First, we reduce the weight of appearance information. Second, we use an Ensemble Kalman Filter to predict the random motion information of cattle. Third, we propose a supplementary matching algorithm that compares the absolute cattle position in the barn to reassign lost tracks. The main idea of the matching algorithm assumes that the number of cattle is fixed in the barn, so the edge of the barn is where new trajectories are most likely to emerge. Experimental results are performed on our dataset collected on two cattle farms. Our algorithm achieves 70.37%, 77.39%, and 81.74% performance on HOTA, AssA, and IDF1, representing an improvement of 1.53%, 4.17%, and 0.96%, respectively, compared to the original method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.49-58
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• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.

• Journal of the Korean Home Economics Association
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• v.50 no.7
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• pp.1-12
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• 2012

The purpose of this study was to identify the factor structure of self-efficacy, consumer behavior, and the learning effects of the unit 'Consumption Life' and to study the effects of self-efficacy on the consumer behavior, and the learning effects of the unit 'Consumption Life'. Questionnaires were administered to 370 female middle school students living in the Metropolitan City of Daegu. The data was analyzed by using the frequency, descriptive statistics, factor analysis, reliability analysis, multiple regression, and t-test. The findings are as follow. Self-efficacy was composed of five factors such as the capability in work performance, rational performance, fear, anxiety, and the ability to challenge oneself. Consumer behavior was composed of five factors such as emphasis on product display, emphasis on information, emphasis on fashion, emphasis on appearance, and the products/information exchange. The learning effects of the unit 'Consumption Life' was composed of two factors in the economical consumption, and rational consumption. The effects of consumer behavior and the learning effects of the unit 'Consumption Life' on each of the self-efficacy factors like the capability in work performance, rational performance, fear, anxiety, the ability to challenge oneself were explained by factors such as emphasis on product display, emphasis on information, emphasis on fashion, emphasis on appearance and products/information exchange, and economical consumption and rational consumption.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.401-408
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• 2013

In this paper, we propose a method that automatically detects organs having similar appearances in medical images by learning both context and appearance features. Since only the appearance feature is used to learn the classifier in most existing detection methods, detection errors occur when the medical images include multiple organs having similar appearances. In the proposed method, based on the probabilities acquired by the appearance-based classifier, new classifier containing the context feature is created by iteratively learning the characteristics of probability distribution around the interest voxel. Furthermore, both the efficiency and the accuracy are improved through 'region based voting scheme' in test stage. To evaluate the performance of the proposed method, we detect femur and tibia which have similar appearance from SKI10 knee joint dataset. The proposed method outperformed the detection method only using appearance feature in aspect of overall detection performance.