Performance Prediction of the Gearbox Elastic Support Structure Based on Multi-Task Learning by Chengshun Zhu, Zhizhou Lu, Jie Qi, Meng Xiang, Shilong Yuan, Hui Zhang

“…Neural networks offer a powerful means of capturing and interpreting the intricate associations linking structural parameters with performance metrics. …”
Get full text

Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…A multi-layer neural network emerged as the top predictor of pure tone averages, achieving a mean absolute error of just 3.05 dB. …”
Get full text

Accurate and lightweight oral cancer detection using SE-MobileViT on clinically validated image dataset by Md Firoz Kabir, Md Yousuf Ahmad, Roise Uddin, Martin Cordero, Shashi Kant

“…To further enrich feature representation and spatial attention, a Squeeze-and-Excitation block is embedded after the third convolutional layer. …”
Get full text

Hybrid method for automatic initialization and segmentation of ventricular on large-scale cardiovascular magnetic resonance images by Ning Pan, Zhi Li, Cailu Xu, Junfeng Gao, Huaifei Hu

“…Material and methods The proposed method comprises several key techniques: 1) a hybrid network integrating CNNs and Transformer as a encoder with the EFG (Edge feature guidance) module (named as CTr-HNs) to localize the target regions of the cardiac on MRI images, 2) initial shape acquisition by alignment of coarse segmentation contours to the initial surface model of 3D-ASM, 3) refinement of the initial shape to cover all slices of MRI in the short axis by complex transformation. …”
Get full text

Enhanced DL-Based Breast Cancer Diagnosis and Classification Using Modified DenseNet-121, DenseNet-201, and MobileNetV2: Optimized Architectures and Refined Activation Functions by Khaddouj Taifi, Yassine Sabbar, Hanin Ardah, Abdel-Haleem Abdel-Aty

“…Despite notable progress, further optimization of neural network architectures and activation functions remains critical for enhancing classification accuracy and model generalization. …”
Get full text

Understanding shading through home-use experience, measurement and modelling by Magdalena Baborska-Narożny, Karol Bandurski, Magdalena Grudzińska

“…A comparison of two airflow network modelling approaches was conducted, and tailored shading usage models were compared with a default TRNSYS model. …”
Get full text

Open-Set Recognition of Environmental Sound Based on KDE-GAN and Attractor–Reciprocal Point Learning by Jiakuan Wu, Nan Wang, Huajie Hong, Wei Wang, Kunsheng Xing, Yujie Jiang

“…Kernel Density Estimation then enforces Density Loss and Offset Loss to ensure these samples align with class boundaries. (2) How to optimize feature space organization: The closed-set classifier is constrained by an Attractor–Reciprocal Point joint loss, maintaining intra-class compactness while pushing unknown samples toward low-density regions. (3) How to evaluate performance in highly open scenarios: We validate the method using UrbanSound8K, AudioEventDataset, and TUT Acoustic Scenes 2017 as closed sets, with ESC-50 categories as open-set samples, achieving AUROC/OSCR scores of 0.9251/0.8743, 0.7921/0.7135, and 0.8209/0.6262, respectively. …”
Get full text

DEDANet: Mountainous Cropland Extraction From Remote Sensing Imagery With Detail Enhancement and Distance Attenuation by Liang Huang, Zixuan Zhang, You Yu, Bo-Hui Tang

“…To address the challenge of low automation accuracy in cropland extraction caused by complex mountainous terrain, severe cropland fragmentation, and ambiguous boundaries, this study proposes a novel semantic segmentation model for cropland in high-resolution remote sensing imagery, termed detail-enhanced and distance-attenuated network (DEDANet), which integrates detail enhancement and distance attenuation mechanisms. …”
Get full text

Predicting mother and newborn skin-to-skin contact using a machine learning approach by Sanaz Safarzadeh, Nastaran Safavi Ardabili, Mohammadsadegh Vahidi Farashah, Nasibeh Roozbeh, Fatemeh Darsareh

“…Methods This study implemented predictive SSC approaches based on the data obtained from the “Iranian Maternal and Neonatal Network (IMaN Net)” from January 2020 to January 2022. …”
Get full text

Epithelial zinc finger protein in lung adenocarcinoma: prognostic biomarker with molecular and clinical implications by Xiaofen Wen, Jianling Zhu, Didi Xi, Minna Chen, De Zeng, Wenwu Xue, Danxia Lin, Jiaxin Shen

“…Abstract Objective This study aimed to evaluate the prognostic significance of epithelial zinc finger protein (EZF/KLF4) in lung adenocarcinoma (LAC) and explore its potential roles in tumor progression and immune regulation. …”
Get full text

Comparative analysis of machine learning models and explainable AI for agriculture drought prediction: A case study of the Ta-pieh mountains by Lichang Xu, Shaowei Ning, Xiaoyan Xu, Shenghan Wang, Le Chen, Rujian Long, Shengyi Zhang, Yuliang Zhou, Min Zhang, Bhesh Raj Thapa

“…The framework employs four machine learning models: Extreme Gradient Boosting (XGBoost), Random Forest (RF), Long Short-Term Memory (LSTM) networks, and Backpropagation Neural Networks (BPNN). …”
Get full text

An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification by Ayesha Shaik, Shivanya Shomir Dutta, Ishaan Milind Sawant, Shreyas Kumar, Ananthakrishnan Balasundaram, Kanjar De

“…This work explores the integration of advanced Convolutional Neural Networks (CNNs) with Bidirectional Long Short Term Memory (BiLSTM) enhanced by spatial, channel, and temporal attention mechanisms to improve the classification of skin lesions. …”
Get full text

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

“…This paper presents a decision-aid framework for face authentication detection that integrates ResNext50 with Bidirectional Long Short-Term Memory (BiLSTM) networks to enhance media integrity and improve deepfake detection. …”
Get full text

Digital twin based deep learning framework for personalized thermal comfort prediction and energy efficient operation in smart buildings by Ahmad Almadhor, Nejib Ghazouani, Belgacem Bouallegue, Natalia Kryvinska, Shtwai Alsubai, Moez Krichen, Abdullah Al Hejaili, Gabriel Avelino Sampedro

Get full text

3D-SCUMamba: An Abdominal Tumor Segmentation Model by Juwita, Ghulam Mubashar Hassan, Amitava Datta

“…The SC module effectively prepares summarized features for robust global dependency processing by the Mamba component. 3D-SCUMamba explicitly addresses the prevalent limitations in current deep learning methods by prioritizing robust feature representation, training stability, and substantial accuracy improvements. …”
Get full text

Design and Analysis of Plasma-Based Reconfigurable Maxwell Fish-Eye-Lens Antennas by Jafar Bazrafshan, Fatemeh Sadeghikia, Mohamed Himdi, Ali Karami Horestani, Hajar Binti Ja'afar

“…Numerical simulations evaluate the performance of these plasma-based lens antennas, demonstrating promising results in beam focusing and gain enhancement. …”
Get full text

Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key c... by Nicholas Pudjihartono, Daniel Ho, Justin Martin O’Sullivan

“…The model weight magnitudes served as proxies for each SNP’s contribution to JIA risk. We evaluated the robustness of our model’s feature ranking across 50 cross-validation runs.Results The top-ranked SNPs included rs7775055, which tags the human leukocyte antigen (HLA) class II haplotype DRB1*0801-DQA1*0401-DQB1*0402, and rs6679677, a non-coding variant that is in 100% linkage with with a coding variant in PTPN22. …”
Get full text

Use of Vision Transformer to Classify Sea Surface Phenomena in SAR Imagery by Junfei Xia, Roland Romeiser, Wei Zhang, Tamay Ozgokmen

“…This study pioneers the application of vision transformers (ViTs) in classifying geophysical phenomena within SAR images, achieving higher recall (0.985), precision (0.984), and F1 scores (0.986) than existing methods and outperforming convolutional neural networks across multiple geophysical categories. We leveraged the single-polarization TenGeoP-SARwv dataset, comprising over 37 000 SAR vignettes, to train and evaluate the ViT models on a balanced subset, improving model generalizability by jointly using WV1 and WV2 images with advanced data augmentation techniques. …”
Get full text

THz-Enabled UAV Communications Under Pointing Errors: Tractable Statistical Channel Modeling and Security Analysis by Mohammad Javad Saber, Mazen Hasna, Osamah S. Badarneh

“…In this study, we present an analytical framework focused on evaluating the security performance of highly directional THz-enabled UAV communication links. …”
Get full text

Development of interpretable intelligent frameworks for estimating river water turbidity by Amin Gharehbaghi, Salim Heddam, Saeid Mehdizadeh, Sungwon Kim

“…Categorical Boosting (CatBoost), Light Gradient-Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and a deep learning method named Convolutional Neural Networks (CNN). To evaluate the performance of proposed models, two gauging river stations situated in United States (i.e. …”
Get full text