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Article Agriculture Food Sciences
A Study on the Effectiveness of Glycerophosphocholine (α-GPC) as an e-Sports Supplement
by Yuki Kamioka - February 18, 2025
This study examined the effects of oral intake of Glycerophosphocholine (α-GPC) on stress response and cognitive function in e-sports. α-GPC is a precursor of acetylcholine and is sometimes used to treat Alzheimer's disease and other dementias, but its potential effects in e-sports have not been investigated. In this study, 21 participants from university e-sports clubs and other groups were given α-GPC for 2 weeks. We measured their stress responses induced by e-sports and their performance in cognitive tasks. The results showed that the placebo increased the rate of increase in salivary amylase after e-sports, but α-GPC significantly decreased this increase. It also suppressed the increase in heart rate after e-sports. Furthermore, 1g of α-GPC significantly increased the rate of correct responses in a 3-back task, a cognitive task involving working memory, after ingestion. These results suggest that 2-week intake of α-GPC may enhance cognitive function and contribute to stress reduction and suppression of autonomic nervous system disturbances caused by e-sports. Further study is needed to determine the minimum effective intake period of the supplement.
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Technical Article Engineering in General Information Sciences Others
by Edmund Soji Otabe - January 6, 2025
Division of Business Improvement and Digital Transformation of Iizuka City Hall in Fukuoka Prefecture and students from Faculty of Computer Science and Systems Engineering at Kyushu Institute of Technology collaborated to attempt to use IT to improve various aspects of Iizuka City Hall's operations. First, Division of the Business Improvement and Digital Transformation solicited themes from divisions in Iizuka City Hall, selected around 10 from these and assigned university students to the themes to be solved. The information science students had a range of skill levels. They solved the problems in a variety of ways, including using automated processing, using cloud services, and developing software for tablet devices. While some of these methods have actually been used, there are also cases where they are not. This is thought to be because the system was created without sufficient consideration of how it would be used in the real case.
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Special Issue Information Sciences
by Haruka Inoue - November 22, 2024
In recent years, the number of fatalities in traffic accidents involving motorcyclists has remained almost unchanged, with single-vehicle accidents accounting for 37.2% of all accidents by accident type in the past five years. In the development of overturn prevention devices for motorcycles, problems remain in post-mounting of the device as well as its downsizing. On the other hand, an existing study using deep learning has proposed a method for detecting dangerous objects on the road surface leading motorcycles to overturn, though this method still needs verification under different conditions. In this study, we apply a method for detecting dangerous objects on the road surface from video images using YOLO to two types of 360-degree cameras and verify that this method is versatile under different conditions.
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Special Issue Agriculture Electrical and Electronic Engineering Food Sciences Information Sciences
by Katsunori Oyama - November 22, 2024
This paper presents a custom-built IoT camera system designed for recognizing wild animal approaches, where data transmission and power consumption are critical concerns in resource-constrained outdoor settings. The proposed method involves the spectral analysis on both infrared and environmental sound data before uploading images and videos to the remote server. Experiments, including battery endurance tests and wildlife monitoring, were conducted to validate the system. These results showed that the system minimized false positives caused by environmental factors such as wind or vegetation movement. Importantly, adding frequency features from audio waveforms that capture sounds including wind noise and footsteps led to an improvement in detection accuracy, which increased the AUC from 0.894 to 0.990 in Random Forest (RF) and from 0.900 with infrared sensor data alone to 0.987 in Logistic Regression (LR). These findings contribute to applications in wildlife conservation, agricultural protection, and ecosystem monitoring.
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