Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…We evaluated the model against several benchmark neural network models by: 1) testing different forecast window sizes ranging from 1.5 to 24 hours, 2) assessing model performance across multiple households, and 3) performing large-scale forecasting by aggregating predictions from 100 households. …”
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Enhancing Situational Awareness of Helicopter Pilots in Unmanned Aerial Vehicle-Congested Environments Using an Airborne Visual Artificial Intelligence Approach by John Mugabe, Mariusz Wisniewski, Adolfo Perrusquía, Weisi Guo

“…To this end, we aim to combine the strengths of both spatial and temporal deep learning models and classic computer stereo vision to (1) estimate the depth of UAVs, (2) predict potential collisions with other UAVs in the sky, and (3) provide alerts for the pilot with regards to the drone that is likely to collide. …”
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SA-I Mechanoreceptor Position in Fingertip Skin May Impact Sensitivity to Edge Stimuli by Gregory J. Gerling

“…The second result was that both models were equally capable of predicting the spatial structure within the in vivo neural responses, and therefore the addition of intermediate ridges did not help in differentiating the indenters. …”
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Toward Accurate Physics‐Based Specifications of Neutral Density Using GNSS‐Enabled Small Satellites by Eric K. Sutton, Jeffrey P. Thayer, Marcin D. Pilinski, Shaylah M. Mutschler, Thomas E. Berger, Vu Nguyen, Dallas Masters

“…Simultaneously, a new era of CubeSat constellations is set to provide data with which to calibrate our upper‐atmosphere models at higher spatial resolution and temporal cadence. …”
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Study on Dynamic Disaster in Steeply Deep Rock Mass Condition in Urumchi Coalfield by Xing-Ping Lai, Mei-Feng Cai, Fen-Hua Ren, Peng-Fei Shan, Feng Cui, Jian-Tao Cao

“…The stress-lever-rotation-effect (SLRE) model of fault-like mobilization was proposed preliminarily. …”
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Assessing Rainfall Erosivity with Artificial Neural Networks for the Ribeira Valley, Brazil by Reginald B. Silva, Piero Iori, Cecilia Armesto, Hugo N. Bendini

“…Soil loss is one of the main causes of pauperization and alteration of agricultural soil properties. Various empirical models (e.g., USLE) are used to predict soil losses from climate variables which in general have to be derived from spatial interpolation of point measurements. …”
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Simulated Directional Wave Spectra of the Wind Sea and Swell under Typhoon Mangkhut by Yu Yan, Mengxi Hu, Yugen Ni, Chunhua Qiu

“…A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). …”
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Dynamic Amplification of Subtropical Extreme Precipitation in a Warming Climate by Jesse Norris, Gang Chen, Chao Li

“…Abstract Projected precipitation changes in a warming climate vary considerably, spatially, and between intensities. The changes can be greater or less than the ∼7% K−1 Clausius‐Clapeyron (CC) prediction, owing to dynamic effects. …”
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A novel method for grading urban socio-economic development levels based on NTL data and Landsat data by Xiang Hua, Jiehai Cheng, Yuke Meng, Rongji Luo

“…Experimental results demonstrate that the proposed hybrid model achieves strong performance in predicting urban socio-economic development levels, with an accuracy of 86.2%. …”
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DMLU-Net: A Hybrid Neural Network for Water Body Extraction from Remote Sensing Images by Ziqiang Xu, Mingfeng Li, Haixiang Guo

“…To tackle these challenges, in this study, we present DMLU-Net, a U-shaped neural network integrated with a dynamic multi-kernel large-scale attention mechanism. The model employs a dynamic multi-kernel large-scale attention module (DMLKA) to enhance cross-scale feature capture; a spectral–spatial attention module (SSAM) in the decoder to boost water region sensitivity; and a dynamic upsampling module (DySample) in the encoder to restore image details. …”
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Design and parameter identification of the wireless torque test system for hybrid vehicles by LI Jie, ZHOU Yijian, GENG Chong, PANG Jinlu

“…These results validate the reliability of the test data and provide an effective data foundation for the accurate torque model prediction.…”
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Tooth segmentation in panoramic dental radiographs using deep convolution neural network -Insights from subjective analysis by Suvarna Bhat, Gajanan K. Birajdar, Mukesh D. Patil

“…Also, a subjective analysis of the model’s predicted mask output from the practitioners is carried out. …”
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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…The model predictions are explained using the XAI techniques. …”
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Potential of EnMAP Hyperspectral Imagery for Regional-Scale Soil Organic Matter Mapping by Yassine Bouslihim, Abdelkrim Bouasria

“…While these results are promising, this study identified limitations in the ability of PLSR to extrapolate predictions beyond the sampled areas, suggesting the need to explore non-linear modeling approaches. …”
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Assessment of Normalized Difference Vegetation Index based vegetation dynamics for monitoring rice growth and yield forecasting in the Mahaweli H region of Sri Lanka by Ganewatte Visal P., Abannikov Victor N., De Seram Osanda L., Wijayaratne Bimasha S., Vichare Aniket S.

“…In the regions of Talawa, Meegalewa, and Galnewa, negative correlation coefficients were recorded. Yield forecasting models developed for the subregions with positive correlations demonstrated high accuracy, confirming the potential of Normalized Difference Vegetation Index as a reliable indicator for rice yield prediction. …”
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Neutrino Follow-Up Analysis of GRB 221009A with KM3NeT by Palacios González Juan

“…Despite no neutrinos have been detected so far in coincidence with these violent phenomena, numerous models predict neutrino emissions by different mechanisms. …”
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Human attention-guided visual perception is governed by rhythmic oscillations and aperiodic timescales. by Isabel Raposo, Ian C Fiebelkorn, Jack J Lin, Josef Parvizi, Sabine Kastner, Robert T Knight, Assaf Breska, Randolph F Helfrich

“…Our results extend the rhythmic sampling framework of attention by demonstrating that aperiodic neural timescales predict behavior in a spatially-, context-, and demand-dependent manner. …”
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Forecast of oil and gas reservoirs of the Sea of Okhotsk based on interpretation processing of seismic material by А. К. Shatyrov

“…Solving problems of forecasting hydrocarbon deposits through the development of a structural and technological scheme for prospecting and evaluation of a geological and geophysical model to identify images of oil and gas deposits.Materials and methods. …”
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The Analysis of Downscaling Results of Weather Parameters for Iran Future by Maryam Bayatvarkeshi, rojin fasihi

“…The purpose of this research is to predict the weather parameters changes under different scenario of LARS- WG downscaling model over the country in future. 2-Materials and Methods In this study, the effect of climate change on temperature, solar radiation and precipitation, as the most important parameters of country in future years, were evaluated. …”
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Numerical Simulation of Storm Surge-Induced Water Level Rise in the Bohai Sea with Adjoint Data Assimilation by Liqun Jiao, Youqi Wang, Dong Jiang, Qingrong Liu, Jing Gao, Xianqing Lv

“…Based on in situ water level measurements from five tide gauge stations, the model simulated the spatial distributions of water levels under different wind stress drag coefficients (<i>C_D</i>) schemes driven by reanalysis wind fields and interpolated wind fields. …”
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