Lab-to-Field Generalization Gap: Assessment of Transfer Learning for Bearing Fault Detection by Eleonora Iunusova, Andreas Archenti

Get full text

A Survey on Video Big Data Analytics: Architecture, Technologies, and Open Research Challenges by Thi-Thu-Trang Do, Quyet-Thang Huynh, Kyungbaek Kim, Van-Quyet Nguyen

“…Our analysis in this survey highlights emerging trends such as the shift toward hybrid cloud–edge architectures, the growing importance of explainable AI and federated learning, and the urgent need for secure and efficient video data management. …”
Get full text

Innovative mathematical correlations for estimating mono-nanofluids' density: Insights from white-box machine learning by Omid Deymi, Fahimeh Hadavimoghaddam, Saeid Atashrouz, Saptarshi Kar, Ali Abedi, Ahmad Mohaddespour, Mehdi Ostadhassan, Abdolhossein Hemmati-Sarapardeh

“…Accordingly, a comprehensive data bank encompassing 4004 experimental data-points was utilized to execute two rigorous machine-learning techniques: Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP). …”
Get full text

Time-Series Prediction of Failures in an Industrial Assembly Line Using Artificial Learning by Mert Can Sen, Mahmut Alkan

“…This study evaluates the efficacy of six artificial learning (AL) models—nonlinear autoregressive (NAR), long short-term memory (LSTM), adaptive neuro-fuzzy inference system (ANFIS), gated recurrent unit (GRU), multilayer perceptron (MLP), and CNN-RNN hybrid networks—for time-series data for failure prediction in aerospace assembly lines. …”
Get full text

Deep Learning Classification of Traffic-Related Tweets: An Advanced Framework Using Deep Learning for Contextual Understanding and Traffic-Related Short Text Classification by Wasen Yahya Melhem, Asad Abdi, Farid Meziane

Get full text

Machine learning-based prediction of speed of sound in fatty acid ethyl esters by Kusum Yadav, Shahad Almansour, Lulwah M. Alkwai, Anupam Yadav, Mehrdad Mottaghi

“…Laboratory data figures from earlier research were used to train the models. …”
Get full text

Prediction of Coalbed Methane Production Using a Modified Machine Learning Methodology by Hongyang Zhang, Kewen Li, Shuaihang Shi, Jifu He

Get full text

The effects of descriptive assessment on student learning and its relationship with mental health using structural equation modeling by Jameleh Farhudi, Vali Mehdinezhad, Mahnoosh Abedini

Get full text

A Global Coseismic InSAR Dataset for Deep Learning: Automated Construction from Sentinel-1 Observations (2015–2024) by Xu Liu, Zhenjie Wang, Yingfeng Zhang, Xinjian Shan, Ziwei Liu

“…With the continued advancement of InSAR technology, the growing volume of satellite-acquired data has opened new avenues for applying deep learning (DL) techniques to the analysis of earthquake-induced surface deformation. …”
Get full text

LAST-PAIN: Learning Adaptive Spike Thresholds for Low Back Pain Biosignals Classification by Freek Hens, Mohammad Mahdi Dehshibi, Leila Bagheriye, Ana Tajadura-Jimenez, Mahyar Shahsavari

“…The LAST encoder learns adaptive thresholds to transform continuous signals of varying dimensionality-ranging from time series data to high dimensional tensors-into sparse spike trains. …”
Get full text

Privacy–preserving dementia classification from EEG via hybrid–fusion EEGNetv4 and federated learning by Muhammad Umair, Muhammad Shahbaz Khan, Muhammad Hanif, Wad Ghaban, Ibtehal Nafea, Sultan Noman Qasem, Sultan Noman Qasem, Faisal Saeed

Get full text

Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…Abstract Background Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. …”
Get full text

A Combined Approach Of Adasyn And Tomeklink For Anomaly Network Intrusion Detection System Using Some Selected Machine Learning Algorithms by Nasiru Ige Salihu, Muhammed Nazeer Musa, Awujola J. Olalekan

“…Securing computer networks against malicious attacks requires an efficient Network Intrusion Detection System (IDS). While machine learning techniques are commonly used for anomaly-based intrusion detection, data imbalance challenges conventional algorithms, leading to biased predictions and reduced accuracy. …”
Get full text

MACHINE LEARNING BASED STRATEGY FOR MITM ATTACK MITIGATION UTILIZING HYBRID FEATURE SELECTION by Pratik Kumar Swain, Suneeta Satpathy, Srinivasa Rao Pokuri

“…Principal Component Analysis (PCA) is also adopted to address the high-dimensional character of cybersecurity data as well as helps in maximization of computing efficiency and helps to lower the danger of overfitting by shrinking the feature space while maintaining crucial variance. …”
Get full text

A Preliminary Investigation into the Design of Driver Evaluator Using a Physics-Assisted Machine Learning Technique by Mingke Hou, Francis Assadian

“…Physics-assisted machine learning is a powerful framework that enhances data efficiency by integrating the strengths of conventional machine learning with physical knowledge. …”
Get full text

Domain Knowledge Preservation in Financial Machine Learning: Evidence from Autocallable Note Pricing by Mohammed Ahnouch, Lotfi Elaachak, Erwan Le Saout

“…Machine learning applications in finance commonly employ feature decorrelation techniques developed for generic statistical problems. …”
Get full text

An interpretable deep learning framework using FCT-SMOTE and BO-TabNet algorithms for reservoir water sensitivity damage prediction by Yin-bo He, Ke-ming Sheng, Ming-liang Du, Guan-cheng Jiang, Teng-fei Dong, Lei Guo, Bo-tao Xu

“…Abstract This study proposes an interpretable deep learning framework to address the high-dimensional and inherently unpredictable challenges associated with oil and gas drilling and completion operations. …”
Get full text

Automated identification of autism spectrum disorder from facial images using explainable deep learning models by El-Sayed Atlam, Khulood O. Aljuhani, Ibrahim Gad, Elsaid Md. Abdelrahim, Ahmed E. Mansour Atwa, Ali Ahmed

“…However, existing machine learning and deep learning techniques frequently face challenges such as limited generalizability, inadequate interpretability, and insufficient performance on diverse datasets. …”
Get full text

Effective Feature Selection on Transfer Deep Learning Algorithm for Thyroid Nodules Ultrasound Detection by Ghufran Basim Alghanimi, Hadeel Aljobouri, Khaleel Akeash Alshimmari, Rasha Massoud

“…The second model integrates ResNet50 and principal component analysis (PCA) for feature selection, intending to reduce dataset dimensionality while maintaining the greatest data variance possible before classification. …”
Get full text

The Regressinator: A Simulation Tool for Teaching Regression Assumptions and Diagnostics in R by Alex Reinhart

Get full text