Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles by Imran Khan, Suheel Abdullah Malik, Amil Daraz, Baitullah Bareer

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Advanced Deep Learning Approaches in Detection Technologies for Comprehensive Breast Cancer Assessment Based on WSIs: A Systematic Literature Review by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

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The Location Privacy Protection Technology of Mobile Intelligent Terminal by LI Zhi-peng, SUN Ming-song, SONG Zeng-lin

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Byzantine fault-tolerant distributed access control mechanism for the Internet of things by CHAI Rong, AI Liping, YANG Ningyu, LIANG Chengchao

“…Addresses IoT scenarios involving Byzantine nodes by investigating IoT access control technologies, a hierarchical blockchain network architecture was proposed which comprised a main cluster and multiple sub-clusters. Based on the computational power and communication rate of IoT devices, a node performance metric was defined to identify main cluster nodes and determine node association strategies to optimize system throughput. …”
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Design of multi-bandgap metamaterial plate based on composite cylindrical resonators by Zhi Miao, Jianfei Yin, Yu Yang, Yibo Ke, Zhoufu Zheng, Xiaoming Geng, Qian Wang

“…The first method utilizes a genetic algorithm to optimize the bandgap width of the CLRMP with periodically arranged resonators. …”
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Influence of Tire Parameters on Contact Patch and Axle Force Generation against Short Obstacles Using DOE Approach by Vikas Birajdar, Seyed Jamaleddin Mostafavi Yazdi, Madhu Kandampadath, Mohammad Behroozi, Javad Baqersad

“…DOE findings suggest optimization strategies for selecting tire parameters to achieve a high test-to-simulation correlation with improved computational efficiency. …”
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Age of Information Minimization in Multicarrier-Based Wireless Powered Sensor Networks by Juan Sun, Jingjie Xia, Shubin Zhang, Xinjie Yu

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The diagnostic value of MRI segmentation technique for shoulder joint injuries based on deep learning by Lina Dai, Md Gapar Md Johar, Mohammed Hazim Alkawaz

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A Vision-Based Procedure with Subpixel Resolution for Motion Estimation by Samira Azizi, Kaveh Karami, Stefano Mariani

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A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

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Initialization of cutting tools and milling paths for 5-axis CNC flank milling of freeform surfaces by Pengbo Bo, Siyu Xue, Xiwen Xu, Caiming Zhang

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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…., World Health Organization guidelines is implanted to decipher the values ranging from natural to anthropogenic contribution.In the Mahanadi River Basin, Odisha, however, this study has highlighted the evaluation of surface water quality (WQ) for drinking reasons by the combined use of Machine Learning (ML) methodologies like Genetic Algorithm Particle Swarm Optimization-based WQI (GAPSO-WQI), with dependability-oriented decision-making approaches such as Firefly Algorithm (FA) and Algorithm of Weeds (AW), that have been used for river water quality monitoring and assessment due to their dependability and feasibility. …”
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A Distributed Coalition Selection of Distribution Centers for Delivery Stations by Fan Wu, Ming Yu, Jingya Zhang, Yicheng Fan, Ming Li

“…In modern logistics networks, an essential challenge is determining how delivery stations autonomously select the appropriate distribution center for dispatching their shipments. Traditional optimization approaches often rely on centralized decision-making and global computations, leading to high computational costs and limited adaptability in dynamic environments. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…Compared to the existing approaches, the proposed approach addresses the entire intralogistic problem, including plant layout, task distribution, release and dispatching algorithms, and fleet size. Its autonomous movement rule generation and low computational complexity make it well suited for dynamic intralogistic environments. …”
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Enhanced and predictive modelling of direct shoot regeneration of Evolvulus alsinoides (L.) using ANN machine learning model and genetic stability studies by Collince Omondi Awere, Kasinathan Rakkammal, Andaç Batur Çolak, Mustafa Bayrak, Ogolla Fredrick, Valentine Chikaodili Anadebe, Manikandan Ramesh

“…Hence, the application of computational techniques (machine learning (ML) algorithms) is essential for predicting de novo direct regeneration. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

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Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…The Improved Whale Optimization Algorithm (IWOA) is employed to optimize parameters in this blueprint, facilitating real-time scheduling by rapidly converging to the global optimum. …”
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Framework for Personalizing Wearable Devices Using Real-Time Physiological Measures by Prakyath Kantharaju, Sai Siddarth Vakacherla, Michael Jacobson, Hyeongkeun Jeong, Meet Nikunj Mevada, Xingyuan Zhou, Matthew J. Major, Myunghee Kim

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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…In the evolving landscape of computer vision, the integration of machine learning algorithms with cutting-edge hardware platforms is increasingly pivotal, especially in the context of disruptive healthcare systems. …”
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