ABL-SMOTE: A Novel Resampling Method by Handling Noisy and Borderline Challenge for Imbalanced Dataset for Software Defect Prediction by Kamal Bashir, Sara Abdelwahab Ghorashi, Ali Ahmed, Abdolraheem Khader

“…Noise and marginal samples become problematic during oversampling operations since they reduce the performance of classification models. This paper proposes an advanced version of Borderline-SMOTE (BL-SMOTE), called ABL-SMOT approach that utilizes INFFC for noise filtering to optimize data quality in the dataset. …”
Get full text

Enhancing Agricultural Surveillance: An Edge‐A and LoRa‐Based Vision Mote System for Infrastructure‐Deficient Regions by Simant Kamal Dutta, Rajesh Singh, Anita Gehlot, Puneet Chandra Srivastava, Kiran Srivastava, Praveen Kumar Malik, Gunjan Gupta

“…The system deploys Vision Surveillance Motes equipped with cameras, motion sensors, and acoustic inputs, and uses lightweight artificial intelligence models (MobileNet‐SSD for vision and support vector machines for sound) processed locally on Raspberry Pi boards. …”
Get full text

Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…The primary objective is to establish clear relationships between tool angles, material removal mechanisms, defect generation (dislocations, phase transformation, amorphization), and final surface integrity, thereby providing foundational knowledge for optimizing ultra-precision machining processes. MethodsTo achieve these objectives, a rigorous multi-scale investigation is conducted, combining molecular dynamics simulation with experimental verification. …”
Get full text

Bayesian Methods for Predicting the Shape of Chinese Yam in Terms of Key Diameters by Mitsunori Kayano, Koki Kyo, Mitsuru Hachiya

“…We have developed automatic, rapid, and low-cost yam-processing machines based on the Bayesian estimation model and predictive model. …”
Get full text

Propensity score methodology for confounding control in health care utilization databases by Elisabetta Patorno, Alessandra Grotta, Rino Bellocco, Sebastian Schneeweiss

“…This article provides an overview of the use of propensity score methodology for pharmacoepidemiologic research with large health care utilization databases, covering recent discussions on covariate selection, the role of automated techniques for addressing unmeasurable confounding via proxies, strategies to maximize clinical equipoise at baseline, and the potential of machine-learning algorithms for optimized propensity score estimation. …”
Get full text

Towards New Strategies for Investing: Insights on Sustainable Exchange-Traded Funds (ETFs) by Nini Johana Marín-Rodríguez, Juan David González-Ruíz, Sergio Botero

“…Future trends reveal the growing role of blockchain technology for ESG verification, crisis-specific ETF models, and the development of more inclusive screening strategies. …”
Get full text

A Review of Vessel Time of Arrival Prediction on Waterway Networks: Current Trends, Open Issues, and Future Directions by Abdullah Al Noman, Aaron Heuermann, Stefan Wiesner, Klaus-Dieter Thoben

“…With the vast majority of global trade volume and value reliant on maritime transport, accurate prediction of vessel estimated time of arrival (ETA) is crucial for optimizing supply chain efficiency and managing logistical complexities in port operations. …”
Get full text

Innovations in Robot-Assisted Surgery for Genitourinary Cancers: Emerging Technologies and Clinical Applications by Stamatios Katsimperis, Lazaros Tzelves, Georgios Feretzakis, Themistoklis Bellos, Ioannis Tsikopoulos, Nikolaos Kostakopoulos, Andreas Skolarikos

“…The role of 3D virtual modeling, intraoperative augmented reality, and fluorescence-guided surgery in improving surgical planning and precision is examined for both kidney and prostate procedures. …”
Get full text

A Python Framework for Crop Yield Estimation Using Sentinel-2 Satellite Data by Konstantinos Ntouros, Konstantinos Papatheodorou, Georgios Gkologkinas, Vasileios Drimzakas-Papadopoulos

“…The findings highlight the importance of the Tillering to the Grain Filling stage in predictive modeling. The developed web application, integrating Python with Google Earth Engine, enables real-time automated crop monitoring, optimizing resource allocation, and supporting precision agriculture. …”
Get full text

Adaptive Beam Steering and Divergence Control for Underwater Optical Wireless Communication Using Reinforcement Learning by Takumi Ishida, Chedlia Ben Naila, Hiraku Okada

“…To address these challenges, we propose a neural network-based beam adaptation technique for UOWC systems, combining deep Q-networks (DQN) and long short-term memory (LSTM) models. These models dynamically optimize beam divergence and steering angles based on the properties of sea waves. …”
Get full text

Prescriptive Maintenance: A Systematic Literature Review and Exploratory Meta-Synthesis by Marko Orošnjak, Felix Saretzky, Slawomir Kedziora

“…Notably, while predictive models are widely adopted, the translation of these capabilities to PsM remains limited. …”
Get full text

Multi-dimensional feature extraction of EEG signal and its application in stroke classification by Teng Wang, Wenhui Jia, Fenglian Li, Xirui Liu, Xueying Zhang, Fengyun Hu

“…Abstract Feature extraction based on EEG signals and construction of classification models using machine learning methods are key to intelligent assisted diagnosis of brain diseases (such as stroke classification). …”
Get full text

Understanding the role of the gut microbiome in solid tumor responses to immune checkpoint inhibitors for personalized therapeutic strategies: a review by Mi Young Lim, Seungpyo Hong, Young-Do Nam

“…Moreover, we review studies investigating the possibility of patient outcome prediction using machine learning models based on gut microbiome data before starting ICI therapy and clinical trials exploring whether gut microbiota modulation, for example via fecal microbiota transplantation or live biotherapeutic products, can improve results of ICI therapy in patients with cancer. …”
Get full text

Hybrid Random Feature Selection and Recurrent Neural Network for Diabetes Prediction by Oyebayo Ridwan Olaniran, Aliu Omotayo Sikiru, Jeza Allohibi, Abdulmajeed Atiah Alharbi, Nada MohammedSaeed Alharbi

“…The method first trains multiple LSTM/BiLSTM base models on dynamically sampled feature subsets to promote diversity, followed by a meta-learner that integrates predictions into a final robust output. …”
Get full text

Empowering Education: Leveraging Clustering and Recommendations for Enhanced Student Insights by Kheira Ouassif, Benameur Ziani, Jorge Herrera-Tapia, Chaker Abdelaziz Kerrache

“…This paper introduces an unsupervised machine learning approach for student clustering and personalized recommendations in education. …”
Get full text

Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence by Yi-Ming Chen, Tzu-Hung Hsiao, Ching-Heng Lin, Yang C. Fann

“…Through the synergistic approach of integrating AI across diverse data sets, clinicians gain a holistic view of patient health and potential risks. Machine learning models excel at identifying high-risk patients, predicting disease activity, and optimizing therapeutic strategies based on clinical, genomic, and immunological profiles. …”
Get full text

Recent Advancements in Artificial Intelligence in Battery Recycling by Subin Antony Jose, Connor Andrew Dennis Cook, Joseph Palacios, Hyundeok Seo, Christian Eduardo Torres Ramirez, Jinhong Wu, Pradeep L. Menezes

“…AI technologies, particularly machine learning and deep learning models, are revolutionizing battery sorting, classification, and disassembly processes. …”
Get full text

Convolutional Neural Decoder for Surface Codes by Hyunwoo Jung, Inayat Ali, Jeongseok Ha

“…Recently, various decoding algorithms based on machine learning have been proposed to improve the decoding performance and latency of QEC codes. …”
Get full text

The specification game: rethinking the evaluation of drug response prediction for precision oncology by Francesco Codicè, Corrado Pancotti, Cesare Rollo, Yves Moreau, Piero Fariselli, Daniele Raimondi

“…Despite the proliferation of machine learning models for Drug Response Prediction (DRP), their validation remains critical to reliably assess their usefulness for drug discovery, precision oncology and their actual ability to generalize over the immense space of cancer cells and chemical compounds. …”
Get full text

Unveiling the carbon neutrality pathways of compact cities: a simulation-based scenario analysis from China by Tianhui Fan, Yujie Ren, Andrew Chapman

“…This study examines the core mechanisms of carbon reduction in compact cities, using Chinese cities as case studies. By employing machine learning models, we analyze how key features of compact cities—such as population density, land-use mix, and public transportation development—contribute to the achievement of carbon neutrality. …”
Get full text