How Predictable Is Electric Vehicle Adoption? Exploring the Broader Role of Renewables in Transportation Using a Data-Driven Approach by Simona-Vasilica Oprea, Adela Bara

“…This study harnesses data from a questionnaire carried out in May 2022 from the Pew Research Center to explore energy sources, climate change issues and factors influencing the adoption of Electric Vehicles (EVs). …”
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Bioinformatic and clinical experimental assay uncovers resistance and susceptibility mechanisms of human glioblastomas to temozolomide and identifies new combined and individual su... by Alexander Modestov, Marianna Zolotovskaia, Maria Suntsova, Galina Zakharova, Aleksander Seryakov, Ivana Jovcevska, Jernej Mlakar, Elena Poddubskaya, Aleksey Moisseev, Grigory Vykhodtsev, Sergey Roumiantsev, Maksim Sorokin, Victor Tkachev, Aleksander Simonov, Anton Buzdin

“…Conclusion: In this study, a comprehensive analysis of the expression of 361 DNA repair genes and activation levels of 38 DNA repair pathways revealed 13 potential survival biomarkers with increased prognostic potential compared to MGMT methylation. We algorithmically reconstructed the TMZ sensitivity pathway with strong predictive capacity in GBM.…”
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Advanced 3D Artistic Image Generation with VAE-SDFCycleGAN by Dorcas Oladayo Esan, Pius Adewale Owolawi, Chunling Tu

“…Most existing artistic GAN-based frameworks lack robust algorithms lack suitable 3D data representations that can fit into    GAN    to produce high-quality 3D artistic images. …”
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Software Defect Prediction Using Deep Q-Learning Network-Based Feature Extraction by Qinhe Zhang, Jiachen Zhang, Tie Feng, Jialang Xue, Xinxin Zhu, Ningyang Zhu, Zhiheng Li

“…Unfortunately, all the previous research conducted without effective feature reduction suffers from high-dimensional data, leading to unsatisfactory prediction performance measures. …”
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A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems by Achin Jain, Arun Kumar Dubey, Shakir Khan, Arvind Panwar, Mohammad Alkhatib, Abdulaziz M Alshahrani

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Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes. by Helene Bei Thomsen, Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, Charline Bour, Guy Fagherazzi, William P T M van Doorn, Tibor V Varga, Adam Hulman

“…We aimed to evaluate algorithmic fairness in glucose predictions. This study utilized continuous glucose monitoring (CGM) data from 101 White and 104 Black participants with type 1 diabetes collected by the JAEB Center for Health Research, US. …”
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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

“…However, medical imaging datasets frequently exhibit class imbalance, posing significant challenges for traditional classification algorithms that rely on balanced data distributions. …”
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A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…We examine traditional compression algorithms, machine learning-based approaches, dynamic parameter adjustment strategies, and hybrid models, each offering unique strengths and limitations. …”
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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder by Shubham Chaudhry, Azzedine Abdedou, Azzeddine Soulaïmani

“…The proposed models offer a robust framework for future research and applications in the field of additive manufacturing, providing high precision and efficiency.…”
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Comprehensive Analysis of the Influence of Technical and Biological Variations on De Novo Assembly of RNA-Seq Datasets by Gonzalez Sergio Alberto, Rivarola Maximo, Ribone Andres, Lew Sergio, Paniego Norma

“…One problem to overcome is the research gap regarding the best method to use in each study to obtain high-quality de novo assembly. …”
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Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks by Nurettin Selcuk Senol, Mohamed Baza, Amar Rasheed, Maazen Alsabaan

“…Competitive performance from OCSVM-FL and LOF-FL, along with the comparable results of K-Means-FL, highlighted the robustness of clustering-based detection methods in this context. …”
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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

“…In contrast, the average PSNR values of the attacked images reached 34.0692 dB, demonstrating the method’s superior robustness and visual quality. Compared to existing zero-watermarking algorithms, the proposed method shows superior robustness and security, making it highly effective for multimedia copyright protection.…”
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Classification of Software Engineering Documents Based on Artificial Immune Systems by Nada Saleem, Rasha Saeed

“…These methods have achieved good speed and classification's accuracy and researchers still investigate in this field to accomplish more accuracy and less time. …”
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Classification of the Condition of Cancer Patients Receiving Home Health Care with Machine Learning Methods by Mürsel Kahveci

“…SVM classifier reached the highest accuracy compared to other classifiers with 90.2% accuracy. …”
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Review of Surface-Defect Detection Methods for Industrial Products Based on Machine Vision by Quan Wang, Mengnan Wang, Jiadong Sun, Deji Chen, Pei Shi

“…The paper organizes industrial defect datasets by type (multi-product and single-product), evaluates data quality and availability, and summarizes common evaluation metrics for accuracy, efficiency by task requirements. It also compares the latest methods on two public datasets to guide further research in defect detection. …”
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Development of a deep learning model to predict smoking status in patients with chronic obstructive pulmonary disease: A secondary analysis of cross-sectional national survey by Sudarshan Pant, Hyung Jeong Yang, Sehyun Cho, EuiJeong Ryu, Ja Yun Choi

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Rationale for the Choice of a Positioning System for Mobile Agricultural Robot Movement Controlling by A. V. Teterev

“…A correctly selected positioning system for controlling the mobile robotic means movement ensures high positioning accuracy of the robotic platform in the garden, allows to automate precise operations in the garden and systematize route planning algorithms.(Research purpose) To substantiate the rational choice of a positioning system for controlling the mobile robotic device movement.…”
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Infrared Small Target Detection Based on Double Gray-Values Descend Angle Contrast Measure by Song Guan, Dali Zhou, Xiaodong Wang, Pengji Zhou

“…Experimental evaluations were conducted on four publicly available datasets, comparing our proposed approach with seven existing algorithms. …”
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Unravelling the importance of spatial and temporal resolutions in modeling urban air pollution using a machine learning approach by Alireza Zhalehdoost, Mohammad Taleai

“…This study proposes a structured machine learning (ML)-based framework to examine how temporal and spatial resolution choices affect the accuracy of urban air pollution modeling. The research is conducted in two distinct phases. In the temporal phase, the impact of incorporating pollutant autocorrelation into ML models (Multilayer Perceptron (MLP) and Random Forest (RF)) is analyzed by comparing results with and without temporal lag features derived through autoregressive (AR) modeling. …”
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The Role of Education in Building National Soft Power: An Empirical Analysis From a Global Perspective Using Deep Neural Networks by Yun Bai

“…Thirdly, we evaluate the model’s performance using several performance metrics, such as accuracy, RMSE, MAE, and precision. Finally, we compare the performance of our proposed DNN model with other machine learning algorithms, such as Random Forest and Support Vector Machines, demonstrating superior predictive accuracy. …”
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