Fog Service Placement Optimization: A Survey of State-of-the-Art Strategies and Techniques by Hemant Kumar Apat, Veena Goswami, Bibhudatta Sahoo, Rabindra K. Barik, Manob Jyoti Saikia

“…In the present survey, we first describe the fundamental and mathematical aspects of the three-layer IoT–fog–cloud computing model. …”
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Preface: AgriVoltaics World Conference 2024 by Alexis Pascaris, Jordan Macknick, Greg Barron-Gafford

“…AgriVoltaics2024 showcased the leading edge of agrivoltaics research and development practice. …”
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AI-Enhanced Threat Intelligence in Remote Patient Monitoring Systems: A Survey on Recent Advances, Challenges and Future Research Directions by Jolly Trivedi, Mohammad Tahir, Jouni Isoaho

“…To secure the sensitive data in RPM, this survey discusses how AI can be applied to various architectural solutions, including edge computing, cloud integration, blockchain technology, and Federated Learning (FL). …”
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NFE-YOLO: A Lightweight and Efficient Detection Network for Low, Slow, and Small Drones by Dan Tian, Chen Wang, Dong Zhou, Xin Yan, Liaoyuan Zeng

“…Furthermore, edge inference devices typically have limited computational power, which hampers real-time processing capabilities. …”
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Bayesian Optimized Enhanced Ensemble Multi-Layer Perceptron for Rear-End Collision Prediction in IoV by Dilna Vijayan, Mohamed Saad, Ahmed M. Khedr

“…The complexity entailed in tackling this problem, specifically concerning the prediction of rear-end crashes, demands the application of cutting-edge methodologies. Learning-based techniques have shown promise, but traditional methods are not very successful in offering solutions. …”
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Remote Sensing Image Compression via Wavelet-Guided Local Structure Decoupling and Channel–Spatial State Modeling by Jiahui Liu, Lili Zhang, Xianjun Wang

“…To address these issues, we present an innovative architecture for distant sensing image compression, called the Multi-scale Channel Global Mamba Network (MGMNet). …”
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Automated and efficient Bangla signboard detection, text extraction, and novel categorization method for underrepresented languages in smart cities by Tanmoy Mazumder, Fariha Nusrat, Abu Bakar Siddique Mahi, Jolekha Begum Brishty, Rashik Rahman, Tanjina Helaly

“…The development of such automated systems faces significant challenges due to variable lighting, intricate backgrounds, fonts, designs, and varying name patterns. This study presents an efficient End-to-End Automated Bangla Signboard Detection, Text Extraction, and novel Categorization System optimized for edge devices. …”
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Methods for Brain Connectivity Analysis with Applications to Rat Local Field Potential Recordings by Anass B. El-Yaagoubi, Sipan Aslan, Farah Gomawi, Paolo V. Redondo, Sarbojit Roy, Malik S. Sultan, Mara S. Talento, Francine T. Tarrazona, Haibo Wu, Keiland W. Cooper, Norbert J. Fortin, Hernando Ombao

“…We present the strengths and limitations of each method in capturing neural dynamics and connectivity. …”
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Fairness-Aware Graph Neural Networks for ICU Length of Stay Prediction in IoT-Enabled Environments by Angelos Christos Maroudis, Konstantina Karathanasopoulou, Charithea C. Stylianides, George Dimitrakopoulos, Andreas S. Panayides

“…To address the loss of static information, we introduce a custom graph neural network that dynamically reconstructs patient relationships over time, adapting from static demographics to evolving inter-patient correlations via multi-modal embeddings (e.g., medications, procedures, vitals, conditions) and learned feature-driven edge formation. We evaluate our approach on MIMIC-IV across diverse time-series formats and demonstrate its superiority over top performing LOS prediction methods, showcasing notable performance improvements while maintaining comparable computational complexity. …”
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Unified 3D Networks: Architecture, Challenges, Recent Results, and Future Opportunities by Mohamed Rihan, Dirk Wubben, Abhipshito Bhattacharya, Marina Petrova, Xiaopeng Yuan, Anke Schmeink, Amina Fellan, Shreya Tayade, Mervat Zarour, Daniel Lindenschmitt, Hans Schotten, Armin Dekorsy

“…We outline the foundational principles, drawn from standardization endeavors and cutting-edge research initiatives, to articulate the envisioned architecture poised to redefine network capabilities. …”
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De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level by Qingyuan Fan, Xuyang Zhao, Junyao Li, Ronghui Liu, Ming Liu, Qishun Feng, Yanping Long, Yang Fu, Jixian Zhai, Qing Pan, Yi Li

“…However, rapidly decoding these “molecular keys” with corresponding basecallers remains challenging. We present DeepSME, a nanopore sequencing and deep-learning based framework towards single-molecule encryption, demonstrated by using 5-hydroxymethylcytosine (5hmC) substitution for individual nucleotide recognition rather than sequential interactions. …”
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YOLOv8n-GBE: A Hybrid YOLOv8n Model With Ghost Convolutions and BiFPN-ECA Attention for Solar PV Defect Localization by Likitha Reddy Yeddula, Archana Pallakonda, Rayappa David Amar Raj, Rama Muni Reddy Yanamala, K. Krishna Prakasha, Mallempati Sunil Kumar

“…Reliable photovoltaic (PV) module defect detection is essential for maintaining long term energy efficiency and lowering solar power system maintenance costs. The deep learning model presented in this research is based on a hybridized YOLOv8n architecture and is lightweight and high performing. …”
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Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review by Xikuan Zhang, Jin Chai, Yongfu Zhan, Danfeng Cui, Xin Wang, Libo Gao

“…Real-time data processing requires innovative solutions such as edge computing and machine learning algorithms, ensuring low-latency, high-accuracy data interpretation while preserving the flexibility of sensor arrays. …”
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A Review on the Lifetime Estimation Methods of XLPE Power Cables by Mohammad AlShaikh Saleh, Alamera Nouran Alquennah, Ali Ghrayeb, Shady S. Refaat, Haitham Abu-Rub, Sunil P. Khatri

“…This article next examines artificial intelligence–based life models, a cutting-edge approach that integrates traditional knowledge with advanced computational techniques, such as machine learning and data analytics, for enhanced prediction of cable life expectancy. …”
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GeoFAN: Point Pattern Recognition in Spatial Vector Data by Zhuoyi Yang, Zeyi Li, Haitao Zhang, Wei Zhang, Yanwei Wang, Yihang Huang

“…Firstly, these data are low signal-to-noise ratio data in which the point patterns are mixed with a large number of normal point clusters; thus, it is difficult to recognize point patterns from these unstructured data using traditional clustering or machine learning methods. Secondly, the lack of edge connectivity relationships in spatial vector data directly hinders the application of graph models. …”
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A comprehensive IoT cloud-based wind station ready for real-time measurements and artificial intelligence integration by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Accurate and efficient wind measurement and monitoring are crucial for various applications, including renewable energy, meteorology, public safety, and environmental research. This paper presents an integrated approach for a cloud-computing Internet of Things-based Automated Weather Station, with edge devices, designed to provide real-time wind measurements in diverse environments. …”
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Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…By dissecting the foundational ''four core effects'' intrinsic to HEAs—high entropy, sluggish diffusion, severe lattice distortion, and cocktail effect—we illuminate the path towards predictable and tailored material properties. Central to the present discourse is the application of valence electron concentration (VEC) and cutting-edge strategies, including the CALculation of PHAse Diagrams (CALPHAD) method, first-principles approach, and machine-learning algorithms, which collectively empower the prediction and understanding of HEA behavior. …”
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Smart Safety Helmets with Integrated Vision Systems for Industrial Infrastructure Inspection: A Comprehensive Review of VSLAM-Enabled Technologies by Emmanuel A. Merchán-Cruz, Samuel Moveh, Oleksandr Pasha, Reinis Tocelovskis, Alexander Grakovski, Alexander Krainyukov, Nikita Ostrovenecs, Ivans Gercevs, Vladimirs Petrovs

“…We examine core VSLAM algorithms (feature-based, direct, hybrid, and deep-learning-enhanced) and discuss their adaptation to wearable platforms. …”
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Understanding mushroom farm environment using TinyML-based monitoring devices by Segun Adebayo, Halleluyah Oluwatobi Aworinde, Oluranti Olayinka Olufemi, Christian Okechukwu Osueke, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba

“…A Smart Environmental Monitoring System for Mushroom Farms is presented in this paper that makes use of advanced Tiny Machine Learning (TinyML) and Internet of Things (IoT) technologies for evaluating and controlling key parameters that impact the growth of mushrooms. …”
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SNUH methylation classifier for CNS tumors by Kwanghoon Lee, Jaemin Jeon, Jin Woo Park, Suwan Yu, Jae-Kyung Won, Kwangsoo Kim, Chul-Kee Park, Sung-Hye Park

“…Conclusions This study presents SNUH-MC, an innovative methylation-based classification tool that significantly advances the field of neuropathology and bioinformatics. …”
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