Effective deep learning aided vehicle classification approach using Seismic Data by Sherief Hashima, Mohamed H. Saad, Ahmad B. Ahmad, Takeshi Tsuji, Hamada Rizk

“…Experimental results validate the efficacy of our approach, achieving state-of-the-art performance using seismic signal classification tasks with limited training data. Our approach achieves an impressive accuracy of 99.8%, underscoring its potential for robust and precise VC in ITSs using seismic data, particularly in data-scarce scenarios. …”
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Development of a Data‐Driven Lightning Scheme for Implementation in Global Climate Models by Vincent Verjans, Christian L. E. Franzke

“…Abstract This study proposes a new lightning scheme applicable at the global scale, predicting lightning rates from climatic variables. …”
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Estimation the validity of remote sensed rainfall data over selected regions in Iraq by Zahraa Al-Montaser

“…These results show that rainfall estimations using TRMM data may be valuable in various applications, including agriculture and water resources. …”
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OpenSTARLab: open approach for spatio-temporal agent data analysis in soccer by Calvin Yeung, Kenjiro Ide, Taiga Someya, Keisuke Fujii

“…Abstract Sports analytics has become both more professional and sophisticated, driven by the growing availability of detailed performance data. This progress enables applications such as match outcome prediction, player scouting, and tactical analysis. …”
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A strategy for recovering continuous behavioral telemetry data from Pacific walruses by Anthony Fischbach, Chadwick V. Jay

“…Our strategy for developing a telemetry system may be applicable to any study requiring intelligent algorithms to continuously monitor behavior, and then compress those data into meaningful information that can be efficiently transmitted. …”
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Gait data generation using generative adversarial network based on human dynamics by Ryoya OBA, Yusuke OSAWA, Keiichi WATANUKI, Kazunori KAEDE

“…Consequently, some generated data exhibited unnatural values for human gait. Additionally, the constructed model was based on experimental data from eight young males wearing age-simulation suits, raising concerns about its applicability to actual older adults. …”
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Estimating intersections' near-crash conflicts with the drone-based image-recording data by Yen-Lin Huang, Yen-Hsiang Chen

“… Recognizing the fact that the information from historical crash data cannot sufficiently reflect the risk level of target intersections under the current driving populations, some traffic safety researchers proposed to use various surrogate measures of safety (SMoS) from either roadside video records or simulation results for estimating near-crash conflicts and performing proactive safety assessment. …”
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Benchmarking Deep Learning for Wetland Mapping in Denmark Using Remote Sensing Data by Muhammad Rizwan Asif

“…We also assess the impact of incorporating near-infrared and DEM data in addition to traditional optical imagery. …”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

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Revolutionizing FANETs With Reinforcement Learning: Optimized Data Forwarding and Real-Time Adaptability by Yasir Ibraheem Mohammed, Rosilah Hassan, Mohammad Kamrul Hasan, Shayla Islam, Huda Saleh Abbas, Muhammad Asghar Khan, Muhammad Attique Khan

“…This work also combines developments in large-scale data collecting from Wireless Sensor Networks (WSNs), using mobile sinks supported by FANETs in conjunction with multi-objective optimization approaches to improve data collecting efficiency greatly. …”
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Towards Integrated Data Management and Analysis for Spatio-Temporal Digital Terrain Models by R. Liu, P. Kuper, T. Grombein, C. Naab, M. Al-Doori, M. Breunig

“…In this paper we introduce a GeoDBMS-based approach to manage, sustainably provide, analyse and visualize spatio-temporal DTM data. First, we review current approaches for the management and temporal modelling of DTM data. …”
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Spatiotemporal Data Augmentation of MODIS‐Landsat Water Bodies Using Adversarial Networks by Soukaina Filali Boubrahimi, Ashit Neema, Ayman Nassar, Pouya Hosseinzadeh, Shah Muhammad Hamdi

“…As a result, there is a clear trade‐off between space and time when considering a single data source. For the efficient monitoring of multiple environmental resources, various Earth science applications need data at high spatial and temporal resolutions. …”
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Minimum Data Set and Metadata for Active Vaccine Safety Surveillance: Systematic Review by Mengdi Zhang, Junting Yang, Yan Li, Yuan Li, Tong Li, Ziqi Dong, Shuo Gong, Yahui Wu, Minrui Ren, Chunxiang Fan, Lina Zhang, Yi Wang, Yali Wang, Jingtian Ren, Feng Sun, Chuanyong Shen, Keli Li, Zhike Liu, Siyan Zhan

“…Guided by the WHO and Council for International Organizations of Medical Sciences guidelines (CIOMS), we developed a 4D framework for Minimum Data Sets (MDSs), including “Vaccine,” “Outcome,” “Demographic Data,” and “Covariate.” …”
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Data-Driven Technologies for Energy Optimization in Smart Buildings: A Scoping Review by Joy Dalmacio Billanes, Zheng Grace Ma, Bo Nørregaard Jørgensen

“…Data-driven technologies in smart buildings offer significant opportunities to enhance energy efficiency, sustainability, and occupant comfort. …”
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Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

“…Comparing it to an existing method, we find that while achieving similar results, our model outperforms the baseline regarding training time by a factor of approximately 20, thus making it more applicable for other datasets. The method has been tested on in situ data from the Wind spacecraft between 1997 and 2015 with a True Skill Statistic of 0.64. …”
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Hearts, Data, and Artificial Intelligence Wizardry: From Imitation to Innovation in Cardiovascular Care by Panteleimon Pantelidis, Polychronis Dilaveris, Samuel Ruipérez-Campillo, Athina Goliopoulou, Alexios Giannakodimos, Panagiotis Theofilis, Raffaele De Lucia, Ourania Katsarou, Konstantinos Zisimos, Konstantinos Kalogeras, Evangelos Oikonomou, Gerasimos Siasos

“…Ethical considerations and regulatory frameworks are evolving, with governing bodies establishing guidelines for AI-driven medical applications. To fully harness the potential of AI, interdisciplinary collaboration among clinicians, data scientists, and engineers is essential, alongside open science initiatives to promote data accessibility and reproducibility. …”
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OMAL: A Multi-Label Active Learning Approach from Data Streams by Qiao Fang, Chen Xiang, Jicong Duan, Benallal Soufiyan, Changbin Shao, Xibei Yang, Sen Xu, Hualong Yu

“…It is also noted that the data that emerge in real-world applications tend to become more complex. …”
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LEAVES: An Expandable Light-curve Data Set for Automatic Classification of Variable Stars by Ya Fei, Ce Yu, Kun Li, Xiaodian Chen, Yajie Zhang, Chenzhou Cui, Jian Xiao, Yunfei Xu, Yihan Tao

“…Experimental results prove that the classifier is more compatible than the classifier established based on a single band and a single survey, and has wider applicability while ensuring classification accuracy, which means it can be directly applied to different data types with only a relatively small loss in performance compared to a dedicated model.…”
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Real-Time Compression Scheme for Urban Rail Transit Train Operation Data by LI Dexiang, WANG Linmei, WANG Shu

“…Tests and applications show that it takes only 0.16 ms for the real-time data compression with the proposed scheme, meeting the 20.00 ms data acquisition cycle requirement. …”
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Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey by Yizhe Wang, Ruifa Luo, Xiaoguang Yang

“…In practical applications, ETC data has demonstrated enormous potential in real-time monitoring and signal control optimization, traffic prediction and artificial intelligence technologies, environmental impact assessment, and other fields. …”
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