System Layout and Grasp Efficiency Optimization for a Multirobot Waste Sorting System by Bart Engelen, Sander Teck, Jef R. Peeters, Karel Kellens

“…The findings demonstrate substantial improvements in picking efficiency of up to 3.6% and pick rates up to 37.5%, underscoring the potential of advanced heuristic algorithms in robotic waste sorting systems. Future work will focus on refining gripper designs and exploring predictive algorithms to further enhance grasp success rates.…”
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A Review of Research on Flight Delay Propagation: Current Situation and Prospect by N. Li, H. G. Yao

“…Among the methods for predicting delay propagation, models based on machine learning algorithms account for a large proportion and have shown good prediction performance. …”
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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

“…<b>Methods</b>: The paper presents the application of ML algorithms, with a focus on convolutional neural networks (CNN) and recurrent neural networks (RNN), in identifying biomarkers of anxiety disorders and predicting therapy responses. …”
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Validation of the Recording of Acute Exacerbations of COPD in UK Primary Care Electronic Healthcare Records. by Kieran J Rothnie, Hana Müllerová, John R Hurst, Liam Smeeth, Kourtney Davis, Sara L Thomas, Jennifer K Quint

“…Responses were reviewed independently by two respiratory physicians. Positive predictive value (PPV) and sensitivity were calculated.…”
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AI and Machine Learning in V2G technology: A review of bi-directional converters, charging systems, and control strategies for smart grid integration by Nagarajan Munusamy, Indragandhi Vairavasundaram

“…AI-powered predictive analytics can forecast energy demand and supply, enabling proactive charging and discharging strategies. …”
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Performance validation of global MPPT for efficient power extraction through PV system under complex partial shading effects by Muhammad Abu Bakar Siddique, Dongya Zhao, Khmaies Ouahada, Ateeq Ur Rehman, Habib Hamam

“…Abstract The photovoltaic (PV) energy is essential for the future of sustainable energy developments. Conventional algorithms perform well in maximum power extraction under uniform irradiance conditions (UIC). …”
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Key factors determination of hyperuricemia and association analysis among patients with breast cancer: results from NHANES data by Ting-ting Meng, Wen-rui Wang, Yan-qing Zheng, Guan-dong Liu

“…Logistic and XGBoost algorithms were used to rank the importance of influencing factors. …”
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AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices by Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, Naveen Kumar SK, George K Stylios

“…This review explores the synergistic potential of AI‐driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real‐time sensing. These advancements enable improved energy harvesting, predictive maintenance, and dynamic performance optimization, making TENGs more practical across industries. …”
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Accelerated discovery of high-density pyrazole-based energetic materials using machine learning and density functional theory by Muhammad Tukur Ibrahim, Muktar Musa Ibrahim, Adamu Uzairu, Gideon Adamu Shallangwa, Sani Uba

“…Using genetic function approximation algorithm, pertinent molecular descriptors were identified and used to build robust Quantitative Structure Property Relationship (QSPR) models for predicting crystalline density of energetic materials. …”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…These algorithms outperform traditional models by accurately handling complex, high-dimensional data more efficiently and cost-effectively. …”
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Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis by Chuang Yang, Yi-Hang Liu, Hai-Kuo Zheng

“…This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. …”
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Robotic Motion Intelligence Using Vector Symbolic Architectures and Blockchain-Based Smart Contracts by Daswin De Silva, Sudheera Withanage, Vidura Sumanasena, Lakshitha Gunasekara, Harsha Moraliyage, Nishan Mills, Milos Manic

“…The rapid adoption of artificial intelligence (AI) systems, such as predictive AI, generative AI, and explainable AI, is in contrast to the slower development and uptake of robotic AI systems. …”
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Integrated single-cell and transcriptome sequencing data reveal the value of IL1RAP in gastric cancer microenvironment and prognosis by Weifeng Yang, Xiaohua Wu, Jian Wang, Wenquan Ou, Xing Huang

“…The CIBERSORT and ssGSEA algorithms elucidated immune infiltration patterns, while TIDE and TCGA predicted immune-related outcomes. …”
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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

“…Moreover, the integration of metaheuristic algorithms with machine learning has enabled dynamic adaptability and predictive optimization, paving the way for real-time energy management. …”
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Insight Thoughts for Intelligent Traffic Management-Based SDN by Sara Sadiq Jawad, Dheyaa Jasim Kadhim, Yusmadi Yah Bt Jusoh

“…This paper introduces the integration of AI algorithms into the SDN controller so that you can make intelligent decisions using predictive analytics of future traffic, what it requires, and network capacity requirements. …”
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Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…ML algorithms are used also to solve both parametric and dynamic optimization problems. …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The diagnostic accuracy was 90.58%, with an overall positive predictive value of 89% and an overall negative predictive value of 86%. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…In axSpA, AI-driven models using imaging techniques such as sacroiliac radiography, magnetic resonance imaging, and computed tomography have increased diagnostic accuracy, especially for early inflammatory changes. Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…AI has emerged as a powerful solution to overcome the limitations of traditional breeding techniques, which often involve time-consuming, resource-intensive processes with limited predictive accuracy. Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
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Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas by Ping Chen, Hailing Han, Xuejie Wang, Bing Wang, Zhanfeng Wang

“…LASSO and Cox regressions were employed to filter cuproptosis-associated genes and construct prediction models. The accuracy of the predictive models was measured by using TCGA internal validation set and the CGGA external validation set. …”
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