Efficient self-attention with smart pruning for sustainable large language models حسب Samir Brahim Belhaouari (9427347)

"…Second, the Weight Matrix Folding method is introduced to efficiently prune the self-attention layer matrices in a simple and efficient mathematical model. …"

An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques حسب Fariha Haque (21485518)

"…To address these challenges, an end-to-end concatenated Convolutional Neural Network (CNN) attention model has been proposed for automatic lung cancer classification. …"

Agent Productivity Modeling in a Call Center Domain Using Attentive Convolutional Neural Networks حسب Ahmed , Abdelrahman

"…In this paper, we propose an objective framework for modeling agent productivity for real estate call centers based on speech signal processing. …"
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PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks حسب Rawan AlSaad (14159019)

"…<h3>Background</h3><p dir="ltr">Early identification of pregnant women at risk for preterm birth (PTB), a major cause of infant mortality and morbidity, has a significant potential to improve prenatal care. However, we lack effective predictive models which can accurately forecast PTB and complement these predictions with appropriate interpretations for clinicians. …"

Micro-Expression Recognition using Convolutional Variational Attention Transformer (ConVAT) with Multihead Attention Mechanism حسب Hafiz Khizer bin Talib (20571467)

"…To address these limitations, we propose the Convolutional Variational Attention Transformer (ConVAT), a novel model that leverages a multi-head attention mechanism integrated with convolutional networks, optimized specifically for detailed micro-expression analysis. …"

A hybrid 3D CNN-LSTM model with soft spatial attention mechanism for accurate hyperspectral image classification حسب Mohamed Sultan Mohamed Ali (17317003)

"…This study introduces a hybrid deep learning model that combines 3D Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks, incorporating residual connections and a soft spatial attention mechanism to overcome these limitations. …"

Dual-attention Network for View-invariant Action Recognition حسب Gedamu Alemu Kumie (19273711)

"…The DANet is composed of relation-aware spatiotemporal self-attention and spatiotemporal cross-attention modules. …"

Addition of sphingosine-1-phosphate to human oocyte culture medium decreases embryo fragmentation حسب Zreik, Tony

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Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematics حسب Md. Ahasan Atick Faisal (15302410)

"…<p dir="ltr">Ground reaction force and moment (GRF&M) measurements are vital for biomechanical analysis and significantly impact the clinical domain for early abnormality detection for different neurodegenerative diseases. …"

Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation حسب Rawan AlSaad (14159019)

"…Yet, modeling the non-stationarity in EHR data has received less attention. …"

Social attention as a cross‐cultural transdiagnostic neurodevelopmental risk marker حسب Thomas W. Frazier (4229593)

"…The best-fitting model included a general social attention factor and six specific factors. …"

Hierarchical multi-head attention LSTM for polyphonic symbolic melody generation حسب Ahmet Kasif (17787560)

"…As such, in this study, a hierarchical multi-head attention LSTM model is proposed for creating polyphonic symbolic melodies. …"

A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity حسب Wesam S. Ahmed (10170053)

"…Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable <u>bioluminescence </u>activity of NLuc in living cells and in vitro. …"

Does standalone phacoemulsification lower intraocular pressure in glaucomatous eyes? A systematic review and meta-analysis حسب Osama Hussein (21301202)

"…In conclusion, standalone phacoemulsification significantly lowers IOP and reduces the need for glaucoma medications in patients with glaucoma.…"

MACGAN: An All-in-One Image Restoration Under Adverse Conditions Using Multidomain Attention-Based Conditional GAN حسب Maria Siddiqua (17949149)

"…Furthermore, an ablation study is conducted to analyze the contributions of the discriminator and attention blocks within the MACGAN architecture. The results confirm that both components play significant roles in the effectiveness of MACGAN, with the discriminator ensuring adversarial training and the attention blocks effectively capturing and enhancing important image features.…"

Serum Vitamin D Concentration ≥75 nmol/L Is Related to Decreased Cardiometabolic and Inflammatory Biomarkers, Metabolic Syndrome, and Diabetes; and Increased Cardiorespiratory Fitn... حسب Vijay Ganji (8710491)

Exendin-4 alleviates steatosis in an in vitro cell model by lowering FABP1 and FOXA1 expression via the Wnt/-catenin signaling pathway حسب Olfa Khalifa (10914452)

Deep Models for Stroke Segmentation: Do Complex Architectures Always Perform Better? حسب Ahmed Soliman (4591621)

"…In this paper, we evaluated the performance of four types of deep models for stroke segmentation: 1) a pure Transformer-based architecture (DAE-Former), 2) two advanced CNN-based models (LKA and DLKA) with attention mechanisms, 3) a hybrid model that incorporates CNNs with Transformers (FCT), and 4) the well-known self-adaptive nnU-Net framework. …"

ASystematic Review on Blockchain Adoption حسب AlShamsi, Mohammed

"…Apart from the core variables of these two models, the results indicated that trust, perceived cost, social influence, and facilitating conditions were the significant determinants influencing several Blockchain applications. …"
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Traffic Transformer: Transformer-based framework for temporal traffic accident prediction حسب Mansoor G. Al-Thani (19237204)

"…This significant shift enhances the model's ability to capture long-range dependencies within time series data. …"