Evaluation of Neural, Systemic and Extracerebral Activations During Active Walking Tasks in Older Adults Using fNIRS by Meltem Izzetoglu, Roee Holtzer

“…However, current literature utilizing fNIRS in mobility research has not been uniform in terms of fNIRS instrumentation characteristics and the accompanying signal processing methods to separate various signal sources (i.e. neural activations, extracerebral signals, systemic responses) which can raise questions about prior research findings. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…Publicly available multi-sensor satellite data, such as Landsat, Sentinel-1, and Sentinel-2, from 2018 to 2020 were employed, providing temporal observation frequencies of up to five days, which represents a 25% increase compared to traditional monitoring approaches. Sophisticated algorithms were developed and implemented to improve the accuracy of fire detection while minimizing false alarms. …”
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Prediction of volcanic fractures based on prestack azimuthal anisotropy: A case study of LFS area in southern Songliao Basin by LI Ning,MIAO He,CAO Kaifang

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Rethinking model prototyping through the MedMNIST+ dataset collection by Sebastian Doerrich, Francesco Di Salvo, Julius Brockmann, Christian Ledig

“…Finally, by establishing a standardized evaluation framework, we aim to enhance transparency, reproducibility, and comparability within the MedMNIST+ dataset collection as well as future research. …”
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Event recognition technology and short-term rockburst early warning model based on microseismic monitoring and ensemble learning by Zibin Li, Dengpan Qiao, Tianyu Yang, Jun Wang, Hao Chen

“…The rockburst early warning model V-soft achieves peak accuracy and F1 scores of 0.9394 and 0.9173, respectively, demonstrating performance improvements of 6.59–15.68% in accuracy and 14.11–27.21% in F1 score compared to conventional machine learning algorithms and ensemble classifiers. …”
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Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning by Jing Zhang, Yong-feng Fu, Hao Shen, Quan Liu, Li-ning Sun, Li-guo Chen

“…The experimental results demonstrate that the proposed liquid lens microscope with DRLAF exhibits high robustness, achieving a 79% increase in speed compared to traditional search algorithms, a 97.2% success rate, and enhanced generalization compared to other deep learning methods.…”
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ROBO-ADVISORS AND AI-DRIVEN FUNDS: CATALYSTS IN THE DYNAMIC EVOLUTION OF ASSET MANAGEMENT by Amirul Ammar Anuar, Mohammad Taqiuddin Mohamad, Ahmad Azam Sulaiman @ Mohamad

“…This study lays the groundwork for future research on AI's long-term impact and scalability in the industry, enriching the understanding of AI's evolving role in finance. …”
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Unsupervised Action Anticipation Through Action Cluster Prediction by Jiuxu Chen, Nupur Thakur, Sachin Chhabra, Baoxin Li

“…Apart from the action anticipation method, we propose an innovative evaluation scheme GreedyMapper, a unique many-to-one mapping scheme that provides a practical solution to the many-to-one mapping challenge, a task that existing mapping algorithms struggle to address. Through comprehensive experimentation conducted on demanding real-world cooking datasets, our unsupervised method demonstrates superior performance compared to weakly-supervised approaches by a significant margin on the 50Salads dataset. …”
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Machine-Learning-Driven Analysis of Wear Loss and Frictional Behavior in Magnesium Hybrid Composites by Barun Haldar, Hillol Joardar, Arpan Kumar Mondal, Nashmi H. Alrasheedi, Rashid Khan, Murugesan P. Papathi

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Near Miss Detection Using Distancing Monitoring and Distance-Based Proximal Indicators by Lek Ming Lim, Lu Yang, Wen Zhu, Ahmad Sufril Azlan Mohamed, Majid Khan Majahar Ali

“…YOLOv7+CNeB significantly reduces the time required to collect evidence from specific roads, provides visual reports, and addresses technical limitations in current algorithms. Future research should explore additional factors contributing to near-miss events, such as road environment, lane changes, and driver behaviours.…”
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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection by Jiayi Zheng, Jiayi Zheng, Yaping Wan, Xin Yang, Hua Zhong, Minghua Du, Gang Wang, Gang Wang

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Mordo2: A Personalization Framework for Silent Command Recognition by Chunzhi Yi, Baichun Wei, Jianfei Zhu, Changbing Chen, Yuefan Wang, Zhiyuan Chen, Yifan Huang, Feng Jiang

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Transmission Line Connection Fittings and Corrosion Detection Method Based on PCSA-YOLOv7 Former by Zhiwei SONG, Xinbo HUANG, Chao JI, Fan ZHANG, Ye ZHANG

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Reinforcement learning and digital twin-driven optimization of production scheduling with the digital model playground by Arne Seipolt, Ralf Buschermöhle, Vladislav Haag, Wilhelm Hasselbring, Maximilian Höfinghoff, Marcel Schumacher, Henrik Wilbers

“…A promising avenue of research is the optimization of digital twins through Reinforcement Learning (RL). …”
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Strategic Demand Response for Economic Dispatch in Wind-Integrated Multi-Area Energy Systems by Peng Li, Li Wang, Peiqiang Zhang, Peng Yan, Chongyang Li, Zhe Nan, Jun Wang

“…This study highlights the potential of collaborative energy management in multi-area systems and provides a pathway for future research to explore advanced control algorithms and the integration of additional renewable energy sources.…”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…In this study, utilizing the EGM2008 satellite gravity model, we conducted a comprehensive analysis of three machine learning algorithms—random forest, support vector machine, and recurrent neural network—and compared their performances against the traditional Kriging interpolation method. …”
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Bio-Inspired Object Detection and Tracking in Aerial Images: Harnessing Northern Goshawk Optimization by Agnivesh Pandey, Rohit Raja, Sumit Srivastava, Krishna Kumar, Manoj Gupta, Chanyanan Somthawinpongsai, Aziz Nanthaamornphong

“…This study presents a novel approach for object detection and tracking in aerial images using a multi-scale Northern Goshawk Pyramid Generative Adversarial Network (NGPGAN). The research evaluates different algorithms and features to identify people, trees, cars, and buildings in real-world drone videos, addressing challenges in pinpointing specific objects among multiple entities. …”
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Intracranial aneurysm instability prediction model based on 4D-Flow MRI and HR-MRI by Fei Peng, Jiaxiang Xia, Fandong Zhang, Shiyu Lu, Hao Wang, Jiashu Li, Xinmin Liu, Yao Zhong, Jiahuan Guo, Yonghong Duan, Binbin Sui, Chuyang Ye, Yi Ju, Shuai Kang, Yizhou Yu, Xin Feng, Xingquan Zhao, Rui Li, Aihua Liu

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Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census by Yilin Li, Cen Chen, Xiaoyu Ji, Ningxiao Jiang, Fei Wang, Xiangqian Gao, Weiwei Chen, Qiang Tang, Yan Li, Shinan Zhang, Gaofeng Qin, Yingjiang Xu, Yanlin Wang, Lingwen Kong, Lei Han, Jie Mei

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Scene Text Detection and Recognition Using Maximally Stable Extremal Region by Golda Jeyasheeli P, Athinarayanan B, Manish T, Mohamad Umar M

“… In recent years, scene text detection and recognition have become important research areas in computer vision and machine learning. …”
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