Fast evaluation on the fatigue level of copper contact wire based on laser induced breakdown spectroscopy and supervised machine learning for high speed railway by Wenfu Wei, Langyu Xia, Zefeng Yang, Huan Zhang, Like Pan, Jian Wu, Guangning Wu

“…Twenty‐four combinations of spectral pre‐processing, feature extraction, and optimisation algorithms were used to compare the recognition results with the accuracy, recall rate, and time cost taken into accounted. …”
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LSTM‐based real‐time stress detection using PPG signals on raspberry Pi by Amin Rostami, Koorosh Motaman, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…Additionally, the authors’ optimised model exhibits substantial reductions in both size and latency while maintaining high accuracy. …”
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Model Reduction and Chattering Mitigation in Multi-Model Predictive Control for Quadrotor UAVs by Ghulam E. Mustafa Abro, Sufyan Ali Memon, Saddaf Rubab, Kaznah Alshammari, Faheem Khan

“…To improve performance, we implement an adaptive gain scheduling algorithm to mitigate the chattering effect frequently seen in multi-model approaches. …”
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Factors influencing docked bike-sharing usage in the City of Kigali, Rwanda by Jean Marie Vianney Ntamwiza, Hannibal Bwire

“…Researchers conducted numerous studies to examine the usage of bike-sharing systems. While earlier research has highlighted the benefits of bike-sharing, limited attention has been given to changes in docked bike-share systems and the use of machine learning algorithms to predict docked bike-sharing usage. …”
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Adaptive information-constrained mapping for feature compression in edge AI and federated systems by Viacheslav Kovtun

“…Efficient projection-gradient optimisation algorithms have been developed, suitable for implementation in constrained computational environments. …”
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Validating machine learning models for the prediction of labour induction intervention using routine data: a registry-based retrospective cohort study at a tertiary hospital in nor... by Jian Wu, Soumitra S Bhuyan, Xiaoli Fu, Quanman Li, Clifford Silver Tarimo, Michael Johnson J Mahande

“…Extensive research into the performance of other classifier algorithms is warranted.…”
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HOW IS ARTIFICIAL INTELLIGENCE CHANGING HR? ADAPTIVE MANAGEMENT FOR THE NEW ENVIRONMENT by Dmytro Antoniuk, Bjoern Sven Ivens, Olexandr Kolyada

“…Special attention is paid to ethical issues such as algorithmic bias and transparency, as well as organisational barriers that may prevent the implementation of AI. …”
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Métodos de geração de colunas para problemas de atribuição Column generation methods for assignment problems by Edson Luiz França Senne, Luiz Antonio Nogueira Lorena, Silvely Nogueira de Almeida Salomão

“…Computational experiments are presented in order to confirm the effectiveness of the proposed algorithms.…”
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Mixed Reality Human–Robot Interface With Adaptive Communications Congestion Control for the Teleoperation of Mobile Redundant Manipulators in Hazardous Environments by Krzysztof Adam Szczurek, Raul Marin Prades, Eloise Matheson, Jose Rodriguez-Nogueira, Mario Di Castro

“…The teleoperator was provided with immersive interactions while preserving precise positioning of the robot. …”
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A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…In order to support sustainable energy goals, these highlighted machine learning algorithms offer a potent environment for optimising energy flow, temperature regulation, and application stability. …”
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Advancing low‐light object detection with you only look once models: An empirical study and performance evaluation by Samier Uddin Ahammad Shovo, Md. Golam Rabbani Abir, Md. Mohsin Kabir, M. F. Mridha

“…The ExDark dataset is a dataset that consists of adequate low‐light images, modified to simulate realistic low‐light scenarios, and employed for evaluation. The deep learning algorithm optimises YOLO's architecture for low‐light detection by adapting the network structure and training strategies while preserving the algorithm's integrity. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…Methodologically, the study used CNN algorithms optimised by Bayesian techniques for the prediction of eight water quality indices, coupled with SHAPley Additive exPlanations (SHAP) analysis under XAI to interpret the complex decision-making processes of these models. …”
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Interactive Modelling in Augmented Reality with Subdivision Surfaces and Advanced User Gesture Recognition by Alessio Cellupica, Marco Cirelli, Oliviero Giannini, Pier Paolo Valentini

“…The methodology is developed from a geometry-sculpting algorithm based on the use of the subdivision surfaces approach to combine the ease and versatility of interactive modelling even of complex shapes, while maintaining high geometric continuity and smoothness. …”
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Determination of the area index of lettuce leaves with a monocular camera by Laimonas Kairiūkštis, Başak Yalçıner, Emre Özkul

“…By clustering pixel values using the Gaussian Mixture Models (GMM) algorithm, the cluster representing 1-week-old lettuce plants with the lowest pixel values has been identified, while the cluster representing 7-week-old lettuce plants had the highest pixel values. …”
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Prospective external validation of the automated PIPRA multivariable prediction model for postoperative delirium on real-world data from a consecutive cohort of non-cardiac surgery... by Mary-Anne Kedda, Kelly A Reeve, Nayeli Schmutz Gelsomino, Michela Venturini, Felix Buddeberg, Martin Zozman, Reto Stocker, Philipp Meier, Marius Möller, Simone Pascale Wildhaber, Benjamin T Dodsworth

“…Objectives Postoperative delirium (POD) is a common complication in surgical patients over 60, increasing morbidity, mortality and hospital stays. While international guidelines recommend risk screening, resource constraints limit implementation. …”
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Reprogramming Heritage: An Approach for the Automatization in the Adaptative Reuse of Buildings by Marta Domènech-Rodríguez, David López López, Sergi Nadal, Anna Queralt, Còssima Cornadó

“…The proposed methodology for a computational algorithm aims to systematise spatial characteristics, assess programmatic needs, and optimise building usage, while addressing challenges such as data integration and quality assurance. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…However, manually selecting parameters requires professional experience in a process that it is time-consuming and laborious, while the use of genetic algorithms is cumbersome. …”
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Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data by A. Gaspar-Cunha, G. Recio, L. Costa, C. Estébanez

“…The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…The Grey Wolf Optimizer(GWO) algorithm, a fast optimization algorithm with adaptive capabilities and an information feedback mechanism, is applied for hyperparameter optimization of the Long Short-term Memory (LSTM) neural network. …”
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Predictive Modelling of nephrotoxicity from vancomycin and piperacillin-tazobactam (VPT) combination and vancomycin as monotherapy: an artificial intelligence (AI) Approach by Dr Winnie Lee, Mr William J Bolton, Mr Richard C Wilson, Professor Pantelis Georgiou, Professor Alison H Holmes, Dr Nina Zhu, Dr Timothy M Rawson

“…Conclusion: Our results may provide clinicians with actionable insights into optimising empirical antimicrobial regimens while minimising nephrotoxicity risks through the use of AI, which can support better clinical decision-making.…”
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