Task Allocation and Path Planning Method for Unmanned Underwater Vehicles by Feng Liu, Wei Xu, Zhiwen Feng, Changdong Yu, Xiao Liang, Qun Su, Jian Gao

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Smart photonic wristband for pulse wave monitoring by Renfei Kuang, Zhuo Wang, Lin Ma, Heng Wang, Qingming Chen, Arnaldo Leal Junior, Santosh Kumar, Xiaoli Li, Carlos Marques, Rui Min

“…Several different speckle pattern processing algorithms and POFs with different core diameters were evaluated. …”
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Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…<b>Method:</b> This proposal methodology involves sourcing Alzheimer’s disease-related MRI images and extracting features using convolutional neural networks (CNNs) and the Gray Level Co-occurrence Matrix (GLCM). The Harris Hawks Optimization (HHO) algorithm is applied to select the most significant features. …”
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Reconstruction of 12-lead ECG: a review of algorithms by Ekenedirichukwu N. Obianom, G. André Ng, G. André Ng, G. André Ng, G. André Ng, Xin Li, Xin Li, Xin Li

“…Linear and nonlinear (including artificial intelligence) algorithms showed promising performances. …”
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An Adapted Ant Colony Optimization for Feature Selection by Duygu Yilmaz Eroglu, Umut Akcan

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TinderAI: Support System for Matching AI Algorithms and Embedded Devices by Matteo Francobaldi, Allegra De Filippo, Andrea Borghesi, Nikola Pizˇurica, Igor Jovančević, Tim Llewellynn, Miguel de Prado

“…We propose a data-driven approach to assist AI adopters and developers in choosing the optimal HW resource. Our approach is based on three key elements: i) fair benchmarking of target AI algorithms on a set of hetero- geneous platforms, ii) creation of ML models to learn the behaviour of these AI algorithms, and iii) support guidelines to help identify the best deployment option for a given AI algorithm. …”
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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

“…To solve the non-convex problem, we develop a quantization-aware alternating optimization algorithm that decomposes the problem into interrelated subproblems for detection probability maximization, false alarm minimization, energy harvesting optimization, and SU throughput enhancement. …”
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Quaternion generative adversarial -driven Soc estimation using Tyrannosaurus optimizer for improving hybrid electric vehicles renewably powered energy management by M. Sivaramkrishnan, Jaganathan Subramani, Mohammad Mukhtar Alam, Liew Tze Hui

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Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

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Path Planning Approaches in Multi‐robot System: A Review by Semonti Banik, Sajal Chandra Banik, Sarker Safat Mahmud

“…In this article, path‐planning approaches for multiple robots are categorized primarily into classical, heuristic, and artificial intelligence‐based methods. Among the heuristic approaches, bio‐inspired approaches are mostly employed to optimize the classical approaches to enhance their adaptability. …”
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Enhancing User Experiences in Digital Marketing Through Machine Learning: Cases, Trends, and Challenges by Alexios Kaponis, Manolis Maragoudakis, Konstantinos Chrysanthos Sofianos

“…Online marketing environments are rapidly being transformed by Artificial Intelligence (AI). This represents the implementation of Machine Learning (ML) that has significant potential in content personalization, enhanced usability, and hyper-targeted marketing, and it will reconfigure how businesses reach and serve customers. …”
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An Efficient Anomalous Sound Detection System for Microcontrollers by Yi-Cheng Lo, Tsung-Lin Tsai, Chieh-Wen Yang, An-Yeu Wu

“…In this paper, we propose an ASD system that is efficiently optimized for both software and hardware considerations regarding edge intelligence. …”
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Prediction of the packaging chemical migration into food and water by cutting-edge machine learning techniques by Behzad Vaferi, Mohsen Dehbashi, Reza Yousefzadeh, Ali Hosin Alibak

“…Additionally, implementing a leverage algorithm for outlier detection further affirms the reliability of this modeling study.…”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…Recent advancements in artificial intelligence (AI), particularly deep learning (DL)-based techniques, have demonstrated significant potential in machinery condition monitoring and fault diagnosis. …”
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Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler by Kleber Padovani, Rafael Cabral Borges, Roberto Xavier, André Carlos Carvalho, Anna Reali, Annie Chateau, Ronnie Alves, Ronnie Alves

“…We expand upon the previous approach found in the literature to solve this problem by carefully exploring the learning aspects of the proposed intelligent agent, which uses the Q-learning algorithm. …”
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Deep learning-based prediction of nodal metastasis in lung cancer using endobronchial ultrasoundCentral MessagePerspective by Tsukasa Ishiwata, MD, PhD, Terunaga Inage, MD, PhD, Masato Aragaki, MD, PhD, Alexander Gregor, MD, PhD, Zhenchian Chen, MD, Nicholas Bernards, PhD, Kamran Kafi, MD, Kazuhiro Yasufuku, MD, PhD

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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…The rich data at the edge enables it to serve artificial intelligence model training, and design wireless resource management strategies with the goal of optimizing learning performance (such as optimizing model training time, learning convergence, etc.). …”
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Deep learning-based prediction of individualized Real-time FSH doses in GnRH agonist long protocols by Na Kong, Yu Xia, Zhilong Wang, Hui Zhang, Liyan Duan, Yingchun Zhu, Chenyang Huang, Guijun Yan, Jie Mei, Wujun Li, Haixiang Sun

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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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