Machine learning-based prediction of in-hospital mortality in patients with chronic respiratory disease exacerbations by Seung Yeob Ryu, Seon Min Lee, Young Jae Kim, Kwang Gi Kim

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Enhancing multi-temporal drought forecasting accuracy for Iran: Integrating an innovative hidden pattern identifier, recursive feature elimination, and explainable ensemble learnin... by Mahnoosh Moghaddasi, Mansour Moradi, Mehdi Mohammadi Ghaleni, Mehdi Jamei

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Virtual Physical Education: Google Meet as an alternative platform for learning skill-based concepts by Joseph Lobo

“…The said videoconferencing platform is highly efficient based on previously published scholarly works. To further assess these claims in the current study’s situation, this paper is designed to explore the factors linked with students’ acceptance and observation of Google Meet as an alternative educational platform to learn concepts in various Physical Education courses which are skill-based by adopting the Technology Acceptance Model. …”
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Deep Learning-Based Imagery Style Evaluation for Cross-Category Industrial Product Forms by Jianmin Zhang, Yuliang Li, Mingxing Zhou, Sixuan Chu

“…This ambiguity often results in suboptimal market positioning and design decisions. Existing methods, primarily limited to single product categories, rely on labor-intensive user surveys and computationally expensive data processing techniques, thus failing to support cross-category collaboration. …”
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Early Breast Cancer Detection Based on Deep Learning: An Ensemble Approach Applied to Mammograms by Youness Khourdifi, Alae El Alami, Mounia Zaydi, Yassine Maleh, Omar Er-Remyly

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Fault diagnosis of shearer cutting unit gearbox based on improved cascaded broad learning by LI Xin, LI Shuhua, CHEN Hao, SI Lei, WEI Dong, ZOU Xiaoyu

“…The vibration monitoring data of the shearer cutting unit gearbox has a complex structure and is prone to class imbalance issues, leading to frequent false positives in traditional machine learning-based fault diagnosis methods. …”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Temporal Analysis Based Driver Drowsiness Detection System Using Deep Learning Approaches by Furkan Kumral, Ayhan Küçükmanisa

“…In this work, within the scope of Advanced Driver Assistance Systems (ADAS), deep learning based driver drowsiness detection system is proposed. …”
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Deep learning-based temperature detection for group-raised pigs via thermal images by Xiaowen Liu, Xueting Zeng, Mengyuan Chu, Qian Li, Gang Liu

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Printed document layout analysis and optical character recognition system based on deep learning by Dong-Lin Li, Shih-Kai Lee, Yin-Ting Liu

“…Abstract This paper proposes a layout analysis and text recognition system for printed documents based on deep learning. Initially, scanned documents or image files are processed using a layout analysis algorithm based on YOLOv4 and YOLOv8 deep learning to identify the positions of titles, text paragraphs, tables, and images within the document. …”
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Supervised Reinforcement Learning-Based Collaborative Master–Slave Harvest Control Study in Wheat by Zhikai Ma, Chao Zhang, Wei Wang, Hao Wang, Helong Yu, Chunjiang Zhao

“…Aiming at the difficulty of controlling the longitudinal relative position of agricultural machines during the agricultural master–slave navigation cooperative operation and the weak adaptability of the unitary traditional control method in the face of the working conditions of complex farmland environments, this paper proposes a supervised reinforcement learning (SRL)-based longitudinal stable and safe control method applicable to master–slave navigation harvesting and unloading operations. …”
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Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

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Adaptive Transformer-Based Deep Learning Framework for Continuous Sign Language Recognition and Translation by Yahia Said, Sahbi Boubaker, Saleh M. Altowaijri, Ahmed A. Alsheikhy, Mohamed Atri

“…In this paper, we propose an Adaptive Transformer (ADTR)-based deep learning framework that enhances SL video processing for robust and efficient SLT. …”
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The Effect of Reflective Thinking Based Practices on Retention Scores: A Mixed-Meta Method by Emrah Cinkara, Cihan Salma, Veli Batdi

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The Effect of Reflective Thinking Based Practices on Retention Scores: A Mixed-Meta Method by Emrah Cinkara, Cihan Salma, Veli Batdi

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The Effect of Reflective Thinking Based Practices on Retention Scores: A Mixed-Meta Method by Emrah Cinkara, Cihan Salma, Veli Batdi

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Detection of Apple Sucrose Concentration Based on Fluorescence Hyperspectral Image System and Machine Learning by Chunyi Zhan, Hongyi Mao, Rongsheng Fan, Tanggui He, Rui Qing, Wenliang Zhang, Yi Lin, Kunyu Li, Lei Wang, Tie’en Xia, Youli Wu, Zhiliang Kang

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An Optimal Two-Step Approach for Defense Against Poisoning Attacks in Federated Learning by Yasir Ali, Kyung Hyun Han, Abdul Majeed, Joon S. Lim, Seong Oun Hwang

“…Through extensive experimentation on three real-world benchmark datasets, we demonstrate that TDF-PAD outperforms state-of-the-art defense methods by achieving a 0% false positive rate on these benchmark datasets, showing it is generally applicable to any dataset.…”
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Trajectory Tracking Control Based on Visual Localization and Adaptive Radial Basis Function Sliding Mode Control by Hung-Yih Tsai, Shih-Min Liao, Chang-Hong Liu

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