PIFRNet: Position Information Guided Feature Reconstruction Network for Salient Object Detection in Remote Sensing Images by Zhen Wang, Ruixiang Li, Xiaotian Wang, Nan Xu, Zhuhong You

“…Finally, the Feature Reconstruction Module restores fine-grained details and sharp boundaries in the predicted saliency maps by leveraging spatial position information. …”
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Construction and Preliminary Validation of the Children's Academic Readiness Test to Enter Primary School in Afghanistan Country by Mohammad Naeem Rasooli, Ahmad Abedi, Mohammad Ashori

“…All the general model evaluation indices, in line with the predetermined desirable values, suggest the adequacy of the factorial model for the components of numerical reasoning, attention and memory, picture completion, quantitative reasoning, retrieval, associative recall, sentence repetition and counting, visual-spatial reasoning, problem-solving (connecting dots game), and visual-motor skills. …”
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A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images by Dawen Yu, Shunping Ji

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The choice of the number of processing channels in the radiomonitoring equipment on the basis of adaptive multibeam antenna arrays by S. V. Kozlov

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DTC-m6Am: A Framework for Recognizing N6,2′-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms by Hui Huang, Fenglin Zhou, Jianhua Jia, Huachun Zhang

“…The MCC value of 41.1% was achieved when using the independent test, which is 19.7% higher than the current state-of-the-art prediction method, m6Aminer. The results indicate that the DTC-m6Am model has high accuracy and stability and is an effective tool for predicting m6Am sites.…”
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Nonparametric quantification of uncertainty in multistep upscaling approaches: A case study on estimating forest biomass in the Brazilian Amazon by Denis Valle, Leo Haneda, Rafael Izbicki, Renan Akio Kamimura, Bruna Pereira de Azevedo, Silvio H.M. Gomes, Arthur Sanchez, Carlos A. Silva, Danilo R.A. Almeida

“…In these approaches, a series of models are fitted linking the information from these different sensors, often resulting in improved predictions over large areas. …”
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Analysis Method for Ground Settlement Induced by Ultra-Deep Excavation in Hangzhou Soft Clay Considering Time-Space Effect by XIONG Yifan, YING Hongwei, ZHANG Jinhong, CHENG Kang, LI Binghe

“…Finally, a rapid approach was proposed for predicting ground settlements while accounting for the temporal and spatial influences. …”
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Tsetse fly (G. f. fuscipes) distribution in the Lake Victoria basin of Uganda. by Mugenyi Albert, Nicola A Wardrop, Peter M Atkinson, Steve J Torr, Susan C Welburn

“…The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control.…”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Additionally, we provided an approach for evaluating spatial prediction uncertainty based on the models’ internal prediction agreement. …”
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Implications of Self-Potential Distribution for Groundwater Flow System in a Nonvolcanic Mountain Slope by Tada-nori Goto, Kazuya Kondo, Rina Ito, Keisuke Esaki, Yasuo Oouchi, Yutaka Abe, Maki Tsujimura

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Stochastic Portfolio Planning for Virtual Power Plants Using Stratified Sampling by Dosung Kim, Sung-Kwan Joo

“…Forecast errors are further modeled using a copula-based approach that captures spatial and temporal correlations. …”
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Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China by Quanxi Wang, Jun Ren, Maomao Zhang, Hongjun Sui, Xiaodan Li

“…This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. …”
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Georgia on Their Minds: Rethinking the Role of Geographic Scale in U.S. Elections by John Agnew, Michael Shin

“…Results from the 2022 Georgia senate runoff election between Raphael Warnock and Herschel Walker are examined with exploratory spatial data analysis (ESDA) and multi-level regression modeling (MLM) to illustrate how a more complete conception of geographic scale is implicated in electoral outcomes.…”
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Features of Conceptualization of Wine Drinking Situation in the Works of N. S. Leskov by O. A. Dimitrieva

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Identification and Spatiotemporal Characteristic Analysis of Compound Weather and Climate Extremes for Maize in Different Climate Zones of the Songliao Plain by Ziyuan Zhou, Ying Guo, Dan Chen, Kaiwei Li, Rui Wang, Xiao Wei, Jiquan Zhang, Chunli Zhao, Zhijun Tong, Xingpeng Liu

“…Abstract Due to global climate anomalies, the intensity and spatial extent of weather and climate extremes have increased notably. …”
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Decision-Aid Framework for Face Authentication Detection Using ResNext50 and BiLSTM to Enhance Media Integrity by Ayat Abd-Muti Alrawahneh, Siti Norul Huda Sheikh Abdullah, Tarik Abuain, Sharifah Nurul Asyikin Syed Abdullah, Sarah Khadijah Taylor, Nur Hanis Sabrina Suhaimi

“…Unlike conventional approaches focusing solely on spatial features, the proposed hybrid model incorporates temporal analysis, enabling the detection of subtle manipulations distributed across sequential video frames. …”
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Research on the influence of spontaneous commercial space on the commercial vitality of historical and cultural districts by Ruoyao Wang, Wei Shang, Guoliang Zhang

“…Abstract Spontaneous commercial spaces play a crucial role in shaping the vitality of historic districts, yet their spatial characteristics and impact on commercial activity remain understudied. …”
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An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics by Z. Tan, D. Xu, S. Taraphdar, J. Ma, G. Bisht, L. R. Leung

“…Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. …”
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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 AMPC module captures temporal features through multiscale convolutions and extracts spatial features using depthwise separable convolutions, while applying the ECA attention mechanism to weigh key channels, enhancing the model’s focus on crucial electrode channels. …”
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Breaking Down the Computational Barriers to Real‐Time Urban Flood Forecasting by Valeriy Y. Ivanov, Donghui Xu, M. Chase Dwelle, Khachik Sargsyan, Daniel B. Wright, Nikolaos Katopodes, Jongho Kim, Vinh Ngoc Tran, April Warnock, Simone Fatichi, Paolo Burlando, Enrica Caporali, Pedro Restrepo, Brett F. Sanders, Molly M. Chaney, Ana M. B. Nunes, Fernando Nardi, Enrique R. Vivoni, Erkan Istanbulluoglu, Gautam Bisht, Rafael L. Bras

“…Currently, there are no operational systems to forecast flooding at spatial resolutions that can facilitate emergency preparedness and response actions mitigating flood impacts. …”
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