Hybrid Machine Learning and Reinforcement Learning Framework for Adaptive UAV Obstacle Avoidance by Wojciech Skarka, Rukhseena Ashfaq

“…Interdisciplinary approaches combining robotics, AI, and aeronautics are suggested to improve UAV performance in complex environments.…”
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A comprehensive review of fiber-reinforced topology optimization for advanced polymer composites produced by automated manufacturing by Bence Szederkenyi, Norbert Krisztian Kovacs, Tibor Czigany

“…Furthermore, this paper examines the potential transformation of the conventional role of TO algorithms in structural optimization by integrating Artificial Intelligence (AI) into the optimization process [1]. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli, Rani Kumari, Adnan Akhunzada, Korhan Cengiz, Santosh Kumar Sharma, Rakesh Ranjan Kumar, Dinesh Kumar Sah

“…Furthermore, we have utilized seven Explainable AI methodologies: Vanilla Gradients (VG), Guided Backpropagation (GBP ), Integrated Gradients ( IG), Guided Integrated Gradients (GIG), SmoothGrad, Gradient-weighted Class Activation Mapping (GCAM), and Guided Grad-CAM (GGCAM) for interpretability examination, aiding in the advancement of dependable and credible automation of healthcare detection of glaucoma.…”
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Overview of Agricultural Machinery Automation Technology for Sustainable Agriculture by Li Jiang, Boyan Xu, Naveed Husnain, Qi Wang

“…Key enabling technologies include multi-source positioning fusion (e.g., RTK-GNSS/LiDAR), intelligent perception systems utilizing multispectral imaging and deep learning algorithms, adaptive control through modular robotic systems and bio-inspired algorithms, and AI-driven data analytics for resource optimization. …”
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Source Tracing of Raw Material Components in Wood Vinegar Distillation Process Based on Machine Learning and Aspen Simulation by Siqi Liao, Wanting Sun, Haoran Zheng, Qiyang Xu

“…In this study, we explore the application of advanced machine learning models in optimizing the dual-column distillation process for wood vinegar production, such as Random Forest algorithms. Through the integration of Aspen Plus simulation and deep learning, an adaptive control strategy is proposed to enhance the separation efficiency of key components under varying feed conditions. …”
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Performance of two different artificial intelligence models in dental implant planning among four different implant planning software: a comparative study by Pathompong Roongruangsilp, Walita Narkbuakaew, Pathawee Khongkhunthian

“…Abstract Background The integration of artificial intelligence (AI) in dental implant planning has emerged as a transformative approach to enhance diagnostic accuracy and efficiency. …”
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Nanoscale frontiers in cancer diagnosis and therapy by Tamer A. Addissouky

“…Overcoming translational and regulatory hurdles—through multidisciplinary collaboration, innovative clinical trial design, and the integration of AI—will be pivotal in realizing the full clinical impact of nanotechnology-enabled cancer care. …”
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Advances in methods for evaluating anti-wrinkle efficacy in the periocular and perioral areas by TAN Huiling, LV Hua, WEN Si, YE Li, LIU Zhenfeng

“…This paper systematically reviews the research progress of subjective assessment methods and objective analysis methods (such as 3D skin detection, dynamic facial expression capture, biomarker detection), focusing on the innovative application of AI algorithms in wrinkle classification and quantification, as well as the potential of the integration of multimodal technologies (such as AI+3D imaging+biomechanical testing) to enhance the reliability of the evaluation. …”
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Ultrasound Assessment in Polycystic Ovary Syndrome Diagnosis: From Origins to Future Perspectives—A Comprehensive Review by Stefano Di Michele, Anna Maria Fulghesu, Elena Pittui, Martina Cordella, Gilda Sicilia, Giuseppina Mandurino, Maurizio Nicola D’Alterio, Salvatore Giovanni Vitale, Stefano Angioni

“…<b>Conclusions</b>: The continual evolution of ultrasound, encompassing higher probe frequencies, 3D enhancements, and now AI-assisted algorithms, has expanded our ability to characterize PCOM accurately. …”
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Global influences of digital transformation on behavioral factors in tourism: a systematic literature review by Yuan Zhang, Árpád Papp-Váry, Zoltán Szabó

“…Findings reveal: (1) Hybrid frameworks dominate digital adoption research but ignore emotional and cultural factors; (2) Integrating AI, AR, and blockchain boosts satisfaction but overwhelms users and raises privacy worries; (3) Cultural contingencies—collectivism, uncertainty avoidance, and power distance—significantly mediate risk perception and institutional trust in technology adoption; (4) Behavioral adaptation trajectories show generational divides in algorithmic reliance and transparency expectations; (5) Policy integration mechanisms, including government-led digital infrastructure, GDPR-aligned regulations, and public-private partnerships, strengthen destination resilience but remain contingent on regional capacity and cultural alignment. …”
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Emerging technologies in finance: challenges for a sustainable finance by Dhouha Nefla, Sana Jellouli

“…Emerging technologies, such as artificial intelligence (AI), blockchain, and fintech, have profoundly reshaped the financial sector driving unprecedented innovation and creating transformative opportunities for development. …”
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Sex determination through analysis of mandibular indices using lateral cephalogram: An Artificial intelligence diagnostics by P. Shalini Prabha, Anuradha Ganesan, Krithika Chandrasekar Lakshmi, Arul Jothi Murugan

“…However, AI integration in forensic odontology is still in early stages. …”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…AI algorithms can analyse individual patient data to adjust insulin doses and predict glucose fluctuations, paving the way for more responsive, customised treatment plans. …”
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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

“…This underscores the importance of thermal parameters in gasification and supports the systematic integration of AI in biofuel production to enhance predictive accuracy.…”
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Developing and validating an artificial intelligence-based application for predicting some pregnancy outcomes: a multi-phase study protocol by Fatemeh Shabani, Ata Jodeiri, Sakineh Mohammad‑Alizadeh‑Charandabi, Fatemeh Abbasalizadeh, Jafar Tanha, Mojgan Mirghafourvand

“…In Phase 2, an artificial intelligence model will be developed using machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and neural networks, followed by model training, validation, and integration into a user-friendly application. …”
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YOLOT: Multi-scale and diverse tire sidewall text region detection based on You-Only-Look-Once(YOLOv5) by Dehua Liu, Yongqin Tian, Yibo Xu, Wenyi Zhao, Xipeng Pan, Xu Ji, Mu Yang, Huihua Yang

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Wireless real-time monitoring based on triboelectric nanogenerator with artificial intelligence by Dexin Tang, Yuankai Zhou, Xin Cui, Yan Zhang

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Deep Reinforcement Learning-Based Anti-Jamming Approach for Fast Frequency Hopping Systems by Sixi Cheng, Xiang Ling, Lidong Zhu

“…Increasing the hopping frequency speed and integrating artificial intelligence (AI) technologies are currently two of the most effective strategies for enhancing the anti-jamming performance of frequency hopping (FH) systems. …”
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Implementing and evaluating the quality 4.0 PMQ framework for process monitoring in automotive manufacturing by Fathy Alkhatib, Mohamed Allam, Vikas Swarnakar, Juman Alsadi, Maher Maalouf

“…The findings contribute to academic literature and industrial practice by bridging conceptual frameworks and real-world implementation strategies for AI-enhanced quality assurance.…”
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Development and testing of an open source mobile application for audiometry test result analysis and diagnosis support by Michał Kassjański, Marcin Kulawiak, Tomasz Przewoźny, Dmitry Tretiakow, Andrzej Molisz

“…All implemented algorithms and models were optimized for functionality on mobile devices. …”
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