Deep convolutional neural network architecture for facial emotion recognition by Dayananda Pruthviraja, Ujjwal Mohan Kumar, Sunil Parameswaran, Vemulapalli Guna Chowdary, Varun Bharadwaj

“…By combining convolutional and pooling layers, the model effectively captures both subtle facial details and higher-level emotional patterns. …”
Get full text

Public-Private Partnership as a Model of Public Infrastructure Development by A. S. Bednyakov

“…A public-private partnership (PPP), a long-term pooling of public and private partners’ resources, sharing risks, responsibilities, and results, is a successful tool employed in many countries to develop public infrastructure. …”
Get full text

Combining acoustic survey and citizen science data yields enhanced species distribution models for tropical rainforest birds. by Reid Rumelt, Carla Mere Roncal, Arianna Basto, Zuzana Buřivalová, Christopher Searcy

“…Our approach combined automated acoustic monitoring detections and eBird citizen science data available for the region as well as a high resolution land cover dataset of the region's key ecological gradients. The pooled models outperformed models constructed solely with eBird data for predicting fine grain species responses to habitat gradients in intact forest, but also retained information from the citizen science dataset about species occurrence patterns in non-vegetated areas away from intact forest, including those subject to human disturbance. …”
Get full text

Microclimate Refugia Are Transient in Stable Old Forests, Pacific Northwest, USA by Julia A. Jones, Christopher Daly, Mark Schulze, Christopher J. Stlll

“…The 45‐year seasonal patterns and rates of warming were similar throughout the forested landscape and matched regional rates observed at 88 standard meteorological stations in Oregon and Washington, indicating buffering, but not decoupling of long‐term climate change rates. …”
Get full text

Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Fault detection in photovoltaic (PV) panels using thermal images remains a significant challenge due to the complexity of thermal patterns, environmental noise, and the subtle nature of anomalies. …”
Get full text

Research on Electric Vehicle Charging Load Prediction Methods Combining Signal Noise Reduction and Time Series Modeling by Liyun Liu, Xiaomei Xu, Jinsong Zhang, Dong Li

“…Subsequently, it employs convolutional and pooling layers within the CNN to reduce the dimensionality of the data, thereby optimizing the input dimensions. …”
Get full text

ECG-GraphNet: Advanced arrhythmia classification based on graph convolutional networks by Myeonghun Lee, BS, Jiwoo Lim, MS, JinKook Kim, MS

“…A unique QRS-centered weighted average pooling method is employed to enhance beat-specific feature extraction. …”
Get full text

Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…Our framework incorporates dimension alignment strategies and attention mechanisms to capture temporal–spatial complementarity between acoustic feeding signals and visual behavioral patterns. Extensive experiments demonstrate superior performance compared to single-modal and conventional fusion approaches, with 6.4% accuracy improvement. …”
Get full text

Predicting changes in agricultural yields under climate change scenarios and their implications for global food security by Christine Li, James Camac, Andrew Robinson, Tom Kompas

“…We present updates to published estimates of crop yield responses to projected temperature, precipitation, and CO2 patterns and show that mixed effects models perform better than pooled OLS models on root mean squared error (RMSE) and explained deviance, despite the common usage of pooled OLS in previous meta-analyses. …”
Get full text

Residual NAPL Architectures in Fractures: Insights From Microfluidic Experiments by Kun Xing, Xiaoqing Shi, Amalia Kokkinaki, Zhibing Yang, Liangchao Zou, Jichun Wu

“…Three distinct residual NAPL architectures were identified, Pools Pattern (PP), Ganglia Pattern (GP), and Mixed Pattern (MP), affected by aperture heterogeneities and flow rates. …”
Get full text

ID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network by Xiao Feng, Xiao Feng, Zhongyuan Guo, Zhongyuan Guo, Sam Kwong

“…With the global average pooling (GAP) layer incorporated in the residual shrinkage network structure, we introduce an EEG-based Class Activation Map (ECAM) interpretable method to enable visualization analysis of sample-wise learned patterns to effectively explain the model decision. …”
Get full text

LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…This upgrade strengthens the network’s ability to capture fine details and complex patterns, improving multi-scale feature extraction without a significant increase in parameters. …”
Get full text

MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition by Cheng Fang, Sitong Liu, Bing Gao

“…A multi-scale CNN-Inception module extracts hierarchical spatial features via diverse convolutional kernels and pooling operations, capturing localized sensor activations and global brain network interactions. …”
Get full text

Key features of observational research data preparation for evidence synthesis by A. A. Lazarev, K. V. Sapozhnikov, D. G. Tolkacheva, N. A. Sableva

“…This work was conducted within a review of asymptomatic hyperuricemia (AH) and was intended to lead to the consensus among rheumatologists on the management patterns of patients with AH in the Russian Federation.Materials and methods. …”
Get full text

DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
Get full text

Leveraging U-Net and ASPP for effective fault detection in photovoltaic modules by Khalfalla Awedat, Masoud Alajmi, Mustafa Elfituri

“…This study presents a novel deep-learning-based approach to enhance fault detection in PV systems by customizing the Atrous Spatial Pyramid Pooling (ASPP) module within a U-Net architecture. …”
Get full text

A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging by Satyam Tiwari, Goutam Jain, Dasharathraj K. Shetty, Manu Sudhi, Jayaraj Mymbilly Balakrishnan, Shreepathy Ranga Bhatta

“…CNNs are particularly adept in automatically identifying complex patterns and features in pictures like X-rays, CT scans, and MRIs. …”
Get full text

Multisectoral coordination during the COVID-19 pandemic: practices, challenges and recommendations for future preparedness—a systematic literature review protocol by Themba Ginindza, Javan Solomon Okello, Julius N Odhiambo

“…This review aims to delineate the key elements, benefits, challenges and improvement strategies of multisectoral coordination during COVID-19 and to compare patterns between LMICs and high-income countries (HICs).Methods and analysis Eligible studies will include empirical qualitative, quantitative or mixed-methods research published in English between 1 January 2020 and 15 August 2024 that examines formal coordination mechanisms (eg, task forces, public-private partnerships, inter-agency committees) within the context of COVID-19. …”
Get full text

Regional Glacier Mapping and Change Analysis in the Gangshika Region of Qilian Mountain Based on Deep Learning and Satellite Data Time-Series by Lihao Chen, Wei Xu, Zhen Cao, Jiaqi Zhang, Zhizhong Kang

“…Time-series glacier change analysis that is closely linked to global climate patterns has drawn increasing attention. However, few studies focused on regional glacier mapping with high spatial resolution and accuracy. …”
Get full text

Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism by Wangyong Guo, Shijin Liu, Liguo Weng, Xingyu Liang

“…Optimizing short-term load forecasting performance is a challenge due to the non-linearity and randomness of electrical load, as well as the variability of system operating patterns. Existing methods often fail to consider how to effectively combine their complementary advantages and fail to fully capture the internal information in the load sequence, leading to a decrease in accuracy. …”
Get full text