Dong Jun Kim;Yu Jin Choi;Kyung Min Park;Ji Hyun Park;Jae-Moon Lee;Kitae Hwang;In Hwan Jung
The Journal of the Institute of Internet, Broadcasting and Communication
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v.23
no.4
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pp.107-113
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2023
This paper proposes a method for detecting smoking behavior in images using artificial intelligence technology. Since smoking is not a static phenomenon but an action, the object detection technology was combined with the posture estimation technology that can detect the action. A smoker detection learning model was developed to detect smokers in images, and the characteristics of smoking behaviors were applied to posture estimation technology to detect smoking behaviors in images. YOLOv8 was used for object detection, and OpenPose was used for posture estimation. In addition, when smokers and non-smokers are included in the image, a method of separating only people was applied. The proposed method was implemented using Google Colab NVIDEA Tesla T4 GPU in Python, and it was found that the smoking behavior was perfectly detected in the given video as a result of the test.
Chae-Eun Yu;Yeo-Reum Kim;Gyeong-Eon Noh;Jong-Myoung Kim
Fisheries and Aquatic Sciences
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v.26
no.5
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pp.355-365
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2023
The Pacific abalone, Haliotis discus hannai, is a highly valued and industrially important aquaculture species with growing demands of the expanding abalone aquaculture industry. To explore the feasibility of using the brown alga, Sargassum horneri, as a potential substitute for abalone feed, it is important to identify the feed preference and attractant effect of S. horneri on Pacific abalone. Our experiments indicated that the feeding-associated movement of abalone could be detected using a video tracking system under indirect illumination with dim red light. To further analyze the attraction potentials of various test materials, preference analysis was performed using Avicel-coated glass plates with ground powders of various seaweeds (e.g., S. horneri, Saccharina japonica, and Undaria pinnatifida) and commercial abalone feed, together with coffee waste. Heat map analysis indicated greater attraction by the kelp S. japonica than by S. horneri and commercial feed, which showed similar preference levels. Feeding preference based on the area of Avicel eaten by abalone showed a significant preference for U. pinnatifida over S. horneri (feeding area: 68.6 ± 20.1% vs. 37.5 ± 22.4%, p < 0.05). Additionally, the feeding area was significantly greater for plates with S. japonica than for plates with S. horneri (44.0 ± 16.6% vs. 22.6 ± 15.4%, p < 0.05). There was no significant difference in feeding area between commercial feed and S. horneri (31.7 ± 11.6% vs. 31.6 ± 20.2%, p > 0.05). The methanol extracts attracted abalone in the following order: U. pinnatifida > S. horneri > S. japonica > commercial feed > coffee waste. To determine the attractive effects of the components of methanol extracts, mixtures of methanol extracts of commercial feed with increasing amounts of S. horneri were examined. The results showed a significant increase in feeding preference upon addition of S. horneri up to 50% and 75%, suggesting its potential for use as an appetite-enhancing feed additive. This study identified conditions that can be successfully used to monitor the movement of Pacific abalone; the results of preference analysis confirmed that abalone exhibited similar attraction and feeding preference for S. horneri, compared with commercial feed.
Rumination in cattle is closely related to their health, which makes the automatic monitoring of rumination an important part of smart pasture operations. However, manual monitoring of cattle rumination is laborious and wearable sensors are often harmful to animals. Thus, we propose a computer vision-based method to automatically identify multi-object cattle rumination, and to calculate the rumination time and number of chews for each cow. The heads of the cattle in the video were initially tracked with a multi-object tracking algorithm, which combined the You Only Look Once (YOLO) algorithm with the kernelized correlation filter (KCF). Images of the head of each cow were saved at a fixed size, and numbered. Then, a rumination recognition algorithm was constructed with parameters obtained using the frame difference method, and rumination time and number of chews were calculated. The rumination recognition algorithm was used to analyze the head image of each cow to automatically detect multi-object cattle rumination. To verify the feasibility of this method, the algorithm was tested on multi-object cattle rumination videos, and the results were compared with the results produced by human observation. The experimental results showed that the average error in rumination time was 5.902% and the average error in the number of chews was 8.126%. The rumination identification and calculation of rumination information only need to be performed by computers automatically with no manual intervention. It could provide a new contactless rumination identification method for multi-cattle, which provided technical support for smart pasture.
For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.
Journal of The Korean Association For Science Education
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v.36
no.4
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pp.705-715
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2016
The purpose of this research is to analyze elementary students' attention characteristics through attention test and eye tracking on real science classes. The SMI's ETG(eye tracker glasses) mobile eye tracker was used to analyze the attention process of elementary students'. The sampling rate of the ETG is 30Hz. The participants of attention test were elementary 155 6th-grade elementary students and the participants for the eye-tracker were six 6th-grade male students. The eye movements were analyzed using the 'BeGaze Mobile Video Analysis Package' program. The results of this research are as follows. First, the attention test results of elementary students showed high correlation between selective attention and sustained attention (.85) and low correlation between selective attention and self-regulation (.32). Second, the attention types of elementary students were divided into four; attention, inattention, easygoing and hasty. Third, elementary students' attention were divided into top-down, bottom-up, default mode network through analysis of elementary students′ eye-movements during real science classes. Also their attention shift occurred frequently due to various reasons in real class situation. There were three reasons that made elementary students fail to handle knowledge-dependent top-down attention; 1) the cognitive failure of target caused by failing to focus attention, 2) the absence of prior knowledge on target object, 3) the analogical failure of prior knowledge. Finally, elementary students' attention process were schematized based on the analysis of students' eye movements and attention test. This research is expected to be utilized as basic data for developing effective teaching strategies, teaching-learning models and instructional materials.
Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.
The advent of new platforms each year along with the advancement of technology provides a new opportunity for digital media designers to develop creative and innovative contents. This phenomenon affect the same way the students that major in the digital media, and the use of the platforms that is based on the new technology in the development of contents gives a newer and useful opportunity for learning to the students who recently study the digital media area. As the main technology of the recent digital media that attract many students' attention, we are presenting virtual reality display, movement cognition, physical engine and the gesture interface, and developed the consolidated platform based on these four technologies, and designed them in a way that can be more easily implemented in a simpler way. In order to study the efficiency of the platform with the objective of the development of digital media contents, we have developed four different prototype contents, and have measured based on the user's preference, efficiency and satisfaction. In the results of usability evaluation, functionality, effectiveness, efficiency, satisfaction were rated as 'high'. This results shows that the suggested 3D platform environment provides students to develop a rapid prototype fast and easy, and this may have a positive influence on students major in the digital media to conduct creative development research.
Designers often hesitate to decide the shape, size, and layout of a product. Though ergonomic principles and data are absolutely needed in this process, they don have enough guidelines to refer. For the refrigerator designers, they also are not convinced of their decision: the vertical position of the freezing and refrigerating rooms, the height of shelves, the shape of door-handle, etc. To support the refrigerator design, we applied several ergonomic methods to the evaluation of refrigerator. EMG was measured to evaluate the load of users lumbar muscle. Based upon the experimental EMG data, we developed a model to estimate the relative load corresponding to the height of refrigerator shelves. Two different layouts of a refrigerator, R/F and F/R styles, were compared with the model. A three-dimensional motion analysis method was used to evaluate the users motion of using a refrigerator. Ten door-handles with the different shapes and positions were evaluated by tracking the rotations of the users arm. Video protocol analysis was used to evaluate the user interface of a control panel in a refrigerator. Finally, we suggested several ergonomic design guidelines based on the facts found in this research and the anthropometric data of the Korean adults. The results of this study can be applied to the ergonomic design of refrigerators
Duminda, S.K. Tilan Chamara;Kim, Yeo-Reum;Kim, Jong-Myoung
Fisheries and Aquatic Sciences
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v.24
no.1
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pp.32-40
/
2021
Monitoring fish movement is important to understand how physiology adapts to environmental change. To explore the applicability of a video tracking system for determining if chemical cues attract or repel aquatic animals, the movement patterns of rock bream, Oplegnathus fasciatus, were analyzed upon exposure to various materials, including extracts of sea urchin, rock worm, bait worm, krill, barley kernel, and commercial fish feed. Pellets were prepared by mixing freeze-dried tissues with a cellulose and corn flour mixture. Behavioral analysis was carried out with five fish that had been acclimated in the adaptation zone of a Y-shaped tank. Preference toward chemical cues was quantified by assessing the frequency rock bream were observed in a discrete zone around the test material located at the end of each arm and the duration each fish stayed in each zone. The analysis of fish movement upon exposure to commercial feed and barley kernel at each end, respectively, indicated a clear preference toward the feed relative to the barley kernel. Movement responses were further tested with pellets containing extracts of sea urchin, one of the species collected on a large scale, and other materials including krill and worms. A stronger preference toward sea urchin (100%) was observed based on the duration of stay in the test zone, compared to krill (90.1 ± 44.2%), bait worm (81.1 ± 39.1%), rock worm (73.7 ± 28.9%), and barley (63.9 ± 25.9%), under the conditions tested. A detailed comparison of rock bream movements toward each material revealed significant differences in frequency and duration, respectively, between pairs of test materials including krill (74 ± 29.8 and 375.6 ± 118.9) vs. rock worm (41.5 ± 18.7 and 160.2 ± 42.6), krill (86.3 ± 22.9 and 477.1 ± 84) vs. bait worm (36.2 ± 5.5 and 166.1 ± 50.7), and rock worm (45.9 ± 26.2 and 213.7 ± 100.1) vs. bait worm (34.6 ± 21.7 and 159.5 ± 98.5). Rock bream exhibited preference for the test materials in the following order: commercial fish feed > sea urchin > krill > rock worm > bait worm > barley. The results suggest a higher potency of sea urchin extract as a rock bream fishing bait compared to the other materials that are used as commercial bait.
The purpose of this study is to explore what elements and measures are necessary to grasp the content influence and competitiveness of each OTT platform, which is difficult to measure only with the existing TV broadcast ratings indicator, on the same basis. In this study, based on the RACOI, the daily Top 10 list provided by Netflix was scored to determine the correlation with the viewers' reaction to TV dramas, and a meaningful comparison criterion index was derived. Based on this, the study tried to analyze the share of content provided by the top 3 OTT platforms in Korea. Spearman's correlation analysis was performed for each indicator of RACOI and the Netflix popularity score. It was confirmed that the Netflix popularity score was correlated with the digital video views indicator of RACOI. As a result of analyzing the platforms, it was found that the popularity of the content provided by Netflix and Tving was relatively high. This study did not secure the company's sales data, and there is a limitation in that long-term tracking analysis could not be performed. However, the study extracted the viewer response indicators of TV that are correlated with popularity within Netflix. It is valuable as a basic study of an extended study that compares and confirms the long-term impact of content provided by each OTT platform in the future.
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