Advancing TinyML in IoT: A Holistic System-Level Perspective for Resource-Constrained AI by Leandro Antonio Pazmiño Ortiz, Ivonne Fernanda Maldonado Soliz, Vanessa Katherine Guevara Balarezo

“…Resource-constrained devices, including low-power Internet of Things (IoT) nodes, microcontrollers, and edge computing platforms, have increasingly become the focal point for deploying on-device intelligence. By integrating artificial intelligence (AI) closer to data sources, these systems aim to achieve faster responses, reduce bandwidth usage, and preserve privacy. …”
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Sentiment analysis of college students’ microblog posts regarding digital identity via knowledge integration framework by Quan Gan, Liang Yan, Xiaoyan Ren, Pengyu Lou

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Emerging Imaging Technologies in Forensic Medicine: A Systematic Review of Innovations, Ethical Challenges, and Future Directions by Feras Alafer

“…Techniques such as virtual autopsy, multi-detector computed tomography (MDCT), and artificial intelligence (AI)-driven imaging have revolutionized the identification of injuries and causes of death. …”
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ADeepWeeD: An adaptive deep learning framework for weed species classification by Md Geaur Rahman, Md Anisur Rahman, Mohammad Zavid Parvez, Md Anwarul Kaium Patwary, Tofael Ahamed, David A. Fleming-Muñoz, Saad Aloteibi, Mohammad Ali Moni, PhD

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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…The attention mechanism is built to highlight key features and convert the vector sequence into an annotation probability matrix. Thirdly, the CRF algorithm is utilized to decode the relationship between the output predicted labels and generate the optimal label sequence. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…The attention mechanism is built to highlight key features and convert the vector sequence into an annotation probability matrix. Thirdly, the CRF algorithm is utilized to decode the relationship between the output predicted labels and generate the optimal label sequence. …”
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An Optimal Adaptive Control of DC-Microgrid with the Aim of Accurate Current Sharing and Voltage Regulation According to the Load Variation and Gray-Wolf Optimization by Muhammad Hammad Saeed, Sajid Iqbal, Madni Sohail, Usman Akram

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Genetic algorithm in the design of soybean silos for airflow homogenization by Daniel Petravicius, Manuel O. Binelo, Marcia de F. B. Binelo, Vanessa Faoro, José A. G. da Silva

“…The objective of this study was to parameterize and to apply the Darcy-Forchheimer model for simulating airflow in soybean grain mass as function of grain layer height, and develop an artificial intelligence method based on genetic algorithm for optimizing grain storage bin dimensions and air inlet configurations to obtain a more homogeneous airflow in the grain mass. …”
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Predictive Modeling of Credit Card Rejection Using Machine Learning Algorithms: A Comparative Study by Shengyu Gu

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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…A coal gangue sorting cube is constructed, which can improve the accuracy of coal gangue sorting; An image-based coal gangue matching tracking and path planning method is proposed for dynamic coal gangue tracking, which can improve the accuracy and reliability of sorting; Aiming at the problem of intelligent collaborative sorting of multiple sorters, it is proposed to construct a comprehensive benefit function of sorters based on the coal gangue image information database to achieve optimal allocation of multiple tasks for multiple sorters, and to integrate reinforcement learning methods to achieve intelligent collaborative control of multiple sorters and optimal configuration of the number of sorters. …”
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OSFS‐Vague: Online streaming feature selection algorithm based on vague set by Jie Yang, Zhijun Wang, Guoyin Wang, Yanmin Liu, Yi He, Di Wu

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Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. …”
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A Novel Lightweight Algorithm for Sonar Image Recognition by Gang Wan, Qi He, Qianqian Zhang, Hanren Wang, Huanru Sun, Xinnan Fan, Pengfei Shi

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Detection of Welding Defects Tracked by YOLOv4 Algorithm by Yunxia Chen, Yan Wu

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Optimizing Semantic-Aware Video Compression Using Particle Swarm Optimization Technique for Automotive Applications by Vadivel Shanmugam, B. Uma Maheswari

“…This popular and fast-developing technology aims to increase vehicle safety through various sensors and advanced-level Artificial Intelligence (AI)- based algorithms. The camera is one of the vital components of AM systems, which captures real-time videos, processes, encodes, packetizes and transfers them to different processing units for further applications. …”
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A Novel Method for Reducing Vehicle Emissions Utilizing IoT-Based IS-APCPSO Algorithm by Ke Huang, Jianjun Zhu

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An Improved Scene Adaptive PRM Path Planning Algorithm by YANG Jingzhao, WANG Chao, ZHANG Yu

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Image processing algorithm of visual communication design based on deep learning in digital background by Xugang Hou, Qian Liu, Xiaoying Zhang

“…The algorithm integrates DL technologies to optimize image processing workflows and applies them to design practice, significantly improving processing efficiency. …”
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Spatiotemporal Fusion Algorithm Based on Multikernal Adaptive Network by Qiuhui Wang, Qiong Ran, Ke Zheng, Jiaxin Li

“…The experimental results demonstrate that MKAN excels in multiple evaluation metrics. Compared to optimal comparison algorithms, MKAN increases structural similarity by an average of 1.4% and reduces global dimensionless error by an average of 4.4%, fully demonstrating the rationality and superiority of its design. …”
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A new metaheuristic algorithm for solving multi-objective single-machine scheduling problems by Khraibet Tahani Jabbar, Kalaf Bayda Atiya, Mansoor Wafaa

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