An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction by Zhiguo Xiao, Qi Shen, Changgen Li, Dongni Li, Qian Liu

“…However, the complex spatiotemporal characteristics of transportation networks pose significant challenges to precisely capturing their dynamic patterns. Existing methods predominantly rely on predefined static adjacency matrices and employ separate processing of spatial and temporal features, failing to adequately explore the intrinsic coupling relationships between them. …”
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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

“…CNNs extract mammographic features, including spatial hierarchies and malignancy patterns, whereas LSTM networks characterize sequential dependencies and temporal interactions. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…However, traditional spatial partitioning approaches, which divide cities into predefined police districts based on geographic and operational considerations, often fail to account for variations in crime patterns. …”
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Threshold responses of freshwater fish community size spectra to invasive species by Bradley Novak, Brent A. Murry, Jeff S. Wesner, Vojsava Gjoni, Caroline C. Arantes, Erin Shepta, Justin P. F. Pomeranz, James R. Junker, Kathrine Zipfel, Andrew Stump, Levi E. Solomon, Kristopher A. Maxson, Jason A. DeBoer

“…We used a community size spectra (CSS) approach to evaluate fish community size structure across temporal and spatial gradients of Silver Carp abundances. …”
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Comparative analysis of deep neural network architectures for renewable energy forecasting: enhancing accuracy with meteorological and time-based features by Sunawar Khan, Tehseen Mazhar, Muhammad Amir Khan, Tariq Shahzad, Wasim Ahmad, Afsha Bibi, Mamoon M. Saeed, Habib Hamam

“…In datasets abundant in spatial correlations, the CNN-LSTM hybrid demonstrated its utility by providing novel insights into spatial–temporal patterns; nonetheless, it lagged considerably in accuracy, with a mean squared error (MSE) of 0.020 and a R2 of 0.87. …”
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RotJoint-Based Action Analyzer: A Robust Pose Comparison Pipeline by Guo Gan, Guang Yang, Zhengrong Liu, Ruiyan Xia, Zhenqing Zhu, Yuke Qiu, Hong Zhou, Yangwei Ying

“…Finally, we propose TemporalRotNet, a Transformer-based network, trained via supervised contrastive learning to capture spatial–temporal motion features. …”
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Utilizing δ15N of biomonitors to assess N emission sources and deposition chemistry? by Meaghan I. Petix, Michael D. Bell, David G. Williams, R. Dave Evans

“…The δ15N of biomonitor organisms can be used to monitor Ndep at these diverse scales capturing the spatial and temporal heterogeneity of Ndep rates and source chemistries. …”
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Leveraging Land Cover Priors for Isoprene Emission Super-Resolution by Christopher Ummerle, Antonio Giganti, Sara Mandelli, Paolo Bestagini, Stefano Tubaro

“…Our approach integrates land cover priors as emission drivers, capturing spatial patterns more effectively than traditional methods. …”
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Attention-based multi-scale convolution and conformer for EEG-based depression detection by Ze Yan, Ze Yan, Ze Yan, Yumei Wan, Xin Pu, Xiaolin Han, Mingming Zhao, Haiyan Wu, Wentao Li, Xueying He, Yunshao Zheng

“…The Conformer module further captures both global and local temporal dependencies in EEG signals to ensure the capture of long-range dependencies and local patterns. …”
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Dynamic evolution characteristics and risk assessment of floor microseismic in close repeated mining by Jing JIA, Jinyan ZHOU, Qinghua NIU

“…The close proximity between upper and lower coal seams leads to secondary superposition failure during repeated mining, exacerbating the challenges associated with effective water control measures.Using 33200 working face of Pingmei 10 mine as a case study, this paper analyzes microseismic event spatial patterns, energy distribution, as well as extensive statistical data resulting from repetitive lower coal seam extraction actions. …”
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Discriminating spatiotemporal heterogeneity and environmental drivers of fish assemblages using environmental DNA metabarcoding in mosaic habitat ecosystems by Fenfen Ji, Jianzhong Shen, Wenqiang Zhang, Saihong Yan, Baoqing Shan, Jinmiao Zha

“…Although environmental DNA (eDNA) metabarcoding has been effectively used to evaluate fish diversity, studies exploring the spatial and temporal variability of fish communities in mosaic habitats and their connection to water quality after ecological project implementation are still scarce. …”
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A comparative study of multivariate CNN, BiLSTM and hybrid CNN–BiLSTM models for forecasting foreign exchange rate using deep learning by Elysee Nsengiyumva, Joseph K. Mung’atu, Charles Ruranga

“…While CNN effectively captures spatial patterns, it struggles with temporal dependencies, and BiLSTM, despite excelling in sequential data analysis, lacks spatial integration. …”
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The spatiotemporal heterogeneity of reactive oxygen species in the malignant transformation of viral hepatitis to hepatocellular carcinoma: a new insight by Huimin Yuan, Jia Liu, Ruochen Xu, Keshan Yang, Ruiyang Qu, Shuai Liu, Yonghui Zhang, Ming Xiang

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Medium-resolution Dynamic Habitat Indices from Landsat and Sentinel-2 satellite imagery by Elena Razenkova, Katarzyna E. Lewińska, Akash Anand, He Yin, Laura S. Farwell, Anna M. Pidgeon, Patrick Hostert, Nicholas C. Coops, Volker C. Radeloff

“…Biodiversity science requires effective tools to predict patterns of species diversity at multiple temporal and spatial scales. …”
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Bi-modal contrastive learning for crop classification using Sentinel-2 and Planetscope by Ankit Patnala, Scarlet Stadtler, Scarlet Stadtler, Martin G. Schultz, Martin G. Schultz, Juergen Gall, Juergen Gall

“…Crop data often consists of field parcels or sets of pixels from small spatial regions. Additionally, one needs to account for temporal patterns to correctly label crops. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…We gained invaluable insights into deer behavior by analyzing deer calls' frequency, timing, and duration. Additionally, the spatial distribution of deer calls in Taki enabled us to detect a breach in the city's protective fencing and an association between the spatial patterns of deer calls and crop damage in the two fields. …”
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City-level emergy metabolism accounts for China’s 281 cities from 2000 to 2020 by Miaohan Tang, Gengyuan Liu, Jingke Hong, Weier Liu, Chao Zhong, Dan Wang, Yuli Shan

“…A chronicled city-level quantification of emergy metabolic flows over time can significantly enhance the understanding of the temporal dynamics and urban metabolism patterns, which provides critical insights for the transitions to sustainability. …”
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Neural network-based symmetric encryption algorithm with encrypted traffic protocol identification by Jiakai Hao, Ming Jin, Yuting Li, Yuxin Yang

“…A key challenge lies in discerning subtle spatial distribution patterns within ciphertext data to infer the underlying cryptographic algorithms, which is essential for ensuring the communication security of power systems. …”
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Estimation the validity of remote sensed rainfall data over selected regions in Iraq by Zahraa Al-Montaser

“…Existing rain gauge networks lack the temporal and geographical coverage required for adequate monitoring. …”
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Effects of fishing restrictions on the recovery of the endangered Saimaa ringed seal (Pusa hispida saimensis) population. by Pekka Jounela, Miina Auttila, Riikka Alakoski, Marja Niemi, Mervi Kunnasranta

“…Over the past three decades, incidental bycatch has been the single most frequent verified cause of death of the endangered Saimaa ringed seal (Pusa hispida saimensis). Spatial and temporal fishing closures have been enforced to mitigate bycatch, which is mainly caused by the gillnets of recreational fishers. …”
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