Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials by Mar Ariza-Sentís, Hilmy Baja, Sergio Vélez, Rick van Essen, João Valente

“…While most research concentrates on data processing algorithms, this study focused on the preceding step: collecting reliable data. …”
Get full text

A novel and sturdy MPPT architecture for grid-tied EV charging stations using Ali Baba and forty thieves optimization by Debabrata Mazumdar, Hassan Abdurrahman Shuaibu, Chiranjit Sain, Taha Selim Ustun

“…This concept outperforms existing approaches and offers a workable strategy to advance the EV revolution while reducing environmental impact. Even in unpredictable conditions, it ensures a consistent power supply and optimises energy management. …”
Get full text

A Spatiotemporal Dataset of Soil Properties in Northeast China Based on Soil Sampling and Interpolation From 2009 to 2020 by Shuzhen Li, Jieyong Wang, Xu Lin, Yaqun Liu

“…By integrating a spatiotemporal covariance function with the Kriging interpolation algorithm, the study systematically resolves the challenge of spatiotemporal collaborative modelling for multi‐year discontinuous observational data. …”
Get full text

Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…Subsequently, the synthesised data quality was evaluated using a logistic regression model in parallel with an optimised support vector machine algorithm (polynomial kernel). …”
Get full text

An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…Optimising heat transfer in biomedical systems, especially in blood-mediated liquids, is essential for precise medication administration and thermal ablation treatments. …”
Get full text

Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
Get full text

Optimized Quality of Service for Real-Time Wireless Sensor Networks Using a Partitioning Multipath Routing Approach by Mohammed Zaki Hasan, Tat-Chee Wan

“…The proposed approach significantly improves the network lifetime, while reducing energy consumption and decreasing average end-to-end delays within the sensor network via optimised resource sharing in intermediate nodes compared with existing routing algorithms.…”
Get full text

Digital Twin Based on CFD Modelling for Analysis of Two-Phase Flows During Pipeline Filling–Emptying Procedures by Duban A. Paternina-Verona, Oscar E. Coronado-Hernández, Vicente S. Fuertes-Miquel, Manuel Saba, Helena M. Ramos

“…Among the 31 algorithms tested, decision trees, efficient linear models, and ensemble classifiers achieved 100% accuracy for filling processes, while k-Nearest Neighbours (KNN) provided 97.2% accuracy for emptying processes. …”
Get full text

Investigating the feasibility of utilising bagasse ash and reclaimed asphalt pavement dust in geopolymer mortar by Sajan Sharma, Shailja Bawa

“…This study provides valuable insights into optimising mixtures for targeted properties while facilitating large-scale landfill waste recovery, reducing environmental hazards, and replacing cement-based mortar, thereby contributing to sustainable construction practices.…”
Get full text

Short-Term Prediction of Origin–Destination Passenger Flow in Urban Rail Transit Systems with Multi-Source Data: A Deep Learning Method Fusing High-Dimensional Features by Huanyin Su, Shanglin Mo, Huizi Dai, Jincong Shen

“…Short-term origin–destination (OD) passenger flow forecasting is crucial for urban rail transit enterprises aiming to optimise transportation products and increase operating income. …”
Get full text

Accelerating machine learning at the edge with approximate computing on FPGAs by Luis Gerardo León-Vega, Eduardo Salazar-Villalobos, Jorge Castro-Godínez

“… Performing inference of complex machine learning (ML) algorithms at the edge is becoming important to unlink the system functionality from the cloud. …”
Get full text

Tofacitinib monotherapy as maintenance treatment in juvenile dermatomyositis: a case report by Enrique Calvo-Aranda, Delia Argüelles Balas, Estefanía Barral Mena, M Ángeles Martín Díaz

“…We present the case of a child with JDM who achieved sustained remission with tofacitinib monotherapy following the failure of previous therapies. While its use is currently restricted to refractory cases, these findings suggest its potential for earlier integration into treatment algorithms. …”
Get full text

A machine learning-powered energy consumption prediction system with API by Toyeeb Adekunle Abd’Azeez, Lanre Olatomiwa

“…The lower MAPE and the higher R2 score indicate the superiority of the ExtraTreeRegressor over other algorithms. While energy consumption is characterised by high variance, our optimised model effectively interprets interactions between input features and predicts the equivalent energy consumed with a lower RMSE of 11.75. …”
Get full text

Using artificial intelligence for sustainable crop production – a comprehensive review with a focus on potato production by Magdalena Piekutowska

“…By utilizing big data analysis, precision monitoring, and automation, AI can significantly improve agricultural outcomes. For instance, AI algorithms can optimise the use of natural resources and chemical inputs, leading to improved yield forecasting and more effective management of diseases and pests that affect crops. …”
Get full text

Mathematical modeling of fastening conditions in piggyback transport: ensuring safety and stability across different transport modes by Ziyoda Mukhamedova, Diyor Boboyev, Shukhrat Saidivaliev, Rustam Abdullaev, Jamshid Kobulov, Sardorbek Akhmedov, Sherzod Fayzibayev

“…This study has employed Newtonian mechanics and the D'Alembert principle to analyse how different forces, such as gravity, inertia, aerodynamic resistance, and centrifugal forces, affect the stability of semi-trailers while in motion. Systematic algorithms and simulation tools, such as MATLAB, were utilised to determine how speed and external factors affected the forces acting on the fasteners and the resulting movement of the cargo. …”
Get full text

Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…We employed the following three algorithms that represent different clustering methodologies: partition-based, density-based, and probabilistic approaches. …”
Get full text

Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…Current fault diagnosis methods heavily depend on manual visual inspection, leading to inefficiency and inaccuracies. While computer vision algorithms have been developed, their high requirements for running environments limit their applicability on edge devices. …”
Get full text

Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing by Katarzyna Antosz, Lucia Knapčíková, Jozef Husár

“…A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. …”
Get full text

A Literature Review on Security in the Internet of Things: Identifying and Analysing Critical Categories by Hannelore Sebestyen, Daniela Elena Popescu, Rodica Doina Zmaranda

“…From leveraging machine learning and blockchain for anomaly detection and real-time threat response to optimising lightweight algorithms for resource-limited devices, researchers propose innovative and adaptive solutions to address emerging threats. …”
Get full text

A hybrid theoretical–numerical–experimental framework for robust health monitoring of thin-walled hollow composite members using guided waves by Akshay Prakash Kalgutkar, Shirsendu Sikdar, Sauvik Banerjee, Karl Walton, Rakesh Mishra

“…These findings contribute to the development of robust damage identification algorithms for structural health monitoring, providing valuable insights for optimising the maintenance and performance of composite structures in critical engineering environments, ensuring safety and operational efficiency.…”
Get full text