Enhancing PV feed-in power forecasting through federated learning with differential privacy using LSTM and GRU by Pascal Riedel, Kaouther Belkilani, Manfred Reichert, Gerd Heilscher, Reinhold von Schwerin

“…By leveraging advanced FL algorithms such as FedYogi and FedAdam, we propose a method that not only predicts sequential energy data with high accuracy, achieving an R2 of 97.68%, but also adheres to stringent privacy standards, offering a scalable solution for the challenges of smart grids analytics, thus clearly showing that the proposed approach is promising and worth being pursued further.…”
Get full text

Simulating fluvial sediment pulses using remote sensing and machine learning: Development of a modeling framework applicable to data rich and scarce regions by Abhinav Sharma, Celso Castro-Bolinaga, Natalie Nelson, Aaron Mittelstet

“…Various combinations of predictor variables, training algorithms including linear regression and additional machine learning methods, and input data availability scenarios were examined to comprehend the factors influencing turbidity prediction on a regional scale. …”
Get full text

SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…By incorporating soft labels and soft central region loss, our model is guided to prioritize high-quality, well-aligned predictions. We evaluate SCoralDet on the Soft-Coral dataset, achieving an inference latency of 9.52 ms and an mAP50 of 81.9. …”
Get full text

Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…The methodology addresses the fundamental challenge of balancing computational efficiency with prediction accuracy in thermal system design. A validated CFD model generated 935 numerical cases across diverse operational and design parameters, which were used to train and evaluate three machine learning algorithms: linear regression (LR), support vector regression (SVR), and artificial neural networks (ANN). …”
Get full text

Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…Additionally, the study explores key applications of precision fertilization, including data-driven fertilizer recommendations, aerial crop monitoring, real-time nutrient deficiency prediction, automated and optimized fertilization systems, and organic and eco-friendly nutrient management practices. …”
Get full text

Imaging genomics of cancer: a bibliometric analysis and review by Xinyi Gou, Aobo Feng, Caizhen Feng, Jin Cheng, Nan Hong

“…It has been widely applied to explore heterogeneity and predict responsiveness and disease progression in cancer. …”
Get full text

High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
Get full text

Advanced Soft Computing Ensemble for Modeling Contaminant Transport in River Systems: A Comparative Analysis and Ecological Impact Assessment by Jafar Chabokpour

“…The research employed various techniques, including Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Support Vector Regression (SVR), and Genetic Algorithms (GA), to predict pollutant concentrations and estimate transport parameters. …”
Get full text

Pistachio Classification Based on Acoustic Systems and Machine Learning by Yavuz Türkay, Zekiye Seyma Tamay

“…These features are given as input to a support vector machine algorithm called FITCSVM for classification. FITCSVM is an algorithm that can perform one-class and two-class (binary) classification on low or medium-sized prediction datasets. …”
Get full text

Reinforcement learning in artificial intelligence and neurobiology by Tursun Alkam, Andrew H Van Benschoten, Ebrahim Tarshizi

“…In parallel, we discuss how neurobiological findings, especially the role of dopamine in encoding reward prediction errors, have inspired biologically grounded RL models. …”
Get full text

Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…The work opens new directions in learning over complex structures, transcending transformer-based and traditional hypergraph-based algorithms. We validate results through theoretical analysis and real-world experiments, while demonstrating superior performance in, e.g., stock market prediction.…”
Get full text

A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
Get full text

Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. …”
Get full text

3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Improving survival time and predicting prognosis for distinct molecular profiles is substantial. …”
Get full text

Driver drowsiness shield (DDSH): a real-time driver drowsiness detection system by Archita Bhanja, Dibyajyoti Parhi, Dipankar Gajendra, Kreetish Sinha, Arup Kumar Sahoo

“…An algorithm has been proposed to classify eye states as open or closed using Transfer Learning based on the MobileNet architecture. …”
Get full text

Identification of common genetic variation that modulates alternative splicing. by Jeremy Hull, Susana Campino, Kate Rowlands, Man-Suen Chan, Richard R Copley, Martin S Taylor, Kirk Rockett, Gareth Elvidge, Brendan Keating, Julian Knight, Dominic Kwiatkowski

“…The functional consequences of these SNPs could not be predicted using bioinformatic algorithms. Our findings suggest that phenotypic variation in splicing patterns is determined by the presence of SNPs within flanking introns or exons. …”
Get full text

Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…The primary aim is to identify the most effective model for predicting energy consumption based on historical data, contributing to the relationship between energy systems and urban well-being. …”
Get full text

Improving Sharpness-Aware Minimization Using Label Smoothing and Adaptive Adversarial Cross-Entropy Loss by Tanapat Ratchatorn, Masayuki Tanaka

“…Recent advances in learning algorithms have identified loss surface sharpness as an effective metric for reducing the generalization gap. …”
Get full text

AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
Get full text

Cable Force Optimization of Circular Ring Pylon Cable-Stayed Bridges Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization by Shengdong Liu, Fei Chen, Qingfu Li, Xiyu Ma

“…The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. …”
Get full text