Optimizing Resource Allocation and Task Offloading in Multi-UAV MEC Networks by Manzoor Ahmed, Noor Fatima, Salman Raza, Hamid Ali, Abdul Qayum, Wali Ullah Khan, Muhammad Sheraz, Teong Chee Chuah

“…Uncrewed aerial vehicle (UAV)-assisted multi-access edge computing (MEC) is increasingly being adopted to meet the rising demand for low-latency and efficient data processing, particularly in environments with limited ground infrastructure. …”
Get full text

AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

“…The framework integrates machine learning (ML) algorithms for predictive temperature management, blockchain technology for secure data handling, and edge computing for real-time data processing, resulting in a highly efficient and secure system. …”
Get full text

A Comprehensive Evaluation of Monocular Depth Estimation Methods in Low-Altitude Forest Environment by Jiwen Jia, Junhua Kang, Lin Chen, Xiang Gao, Borui Zhang, Guijun Yang

“…However, achieving robust monocular depth estimation in low-altitude forest environments remains challenging, particularly in scenes with dense and cluttered foliage, which complicates applications in environmental monitoring, agriculture, and search and rescue operations. This paper presents a comprehensive evaluation of state-of-the-art deep learning-based MDE methods on low-altitude forest datasets. …”
Get full text

Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye by Enes Gul

“…The implications of this research extend beyond the local setting, contributing valuable insights to the global discourse on climate change adaptation and urban resilience. By combining cutting-edge machine learning techniques with in-depth geographic analysis, this study offers a scalable and innovative model for flood hazard assessment and management, providing a critical tool for cities around the world facing similar challenges.…”
Get full text

A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

“…It also addresses the implementation of polynomial functions PTt in image and pattern detection, with emphasis on feature extraction and edge detection. The application of polynomials in imaging systems may improve recognizing object’s accuracy, curve fitting, and machine learning–based grouping, making them essential for computer vision modifications. …”
Get full text

Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms by Tuxiang Lin, Rongliang Lin

“…Future research will explore edge computing, multi-agent reinforcement learning, and real-time data integration to further enhance scalability and adaptability.…”
Get full text

An Evaluation of Image Slicing and YOLO Architectures for Object Detection in UAV Images by Muhammed Telçeken, Devrim Akgun, Sezgin Kacar

“…However, determining the proper dimensions to slice is essential for the integrity of the objects and their learning by the model. This study presents an evaluation of the image-slicing approach for alternative sizes of images to optimize efficiency. …”
Get full text

A utopic techno-teacher coupling: designing an ad hoc activity map towards transformative pedagogical prototypes for reading instruction by Adelina Asmawi, Md. Saiful Alam

“…Abstract In the evolving techno-educational landscape, it is crucial to reimagine transformative pedagogies based on techno-teacher collaboration to revolutionize teaching effectiveness and efficiency. Although the cutting-edge generative AI tool, Chat GPT, is speculated to be a revolutionary CALL (computer-assisted language learning) tool for teaching reading, how the synergy derived from coupling this modern digital tool and reading instructors may be exploited to reimagine a new reading pedagogy is still unexplored. …”
Get full text

Dense Sandstone Material Decomposition Based on Improved Convolutional Neural Network by Ran ZHANG, Huihua KONG, Jiaxin LI, Yijiao SONG

“…Hybrid loss supervised network learning is used to improve the decomposition accuracy of the network. …”
Get full text

Partial vs. Corona Discharges in XLPE-Covered Conductors: High-Resolution Antenna Dataset for ML Applications by Ondřej Kabot, Lukáš Klein, Zdeněk Slanina, Lukáš Prokop

“…Abstract Accurate differentiation between partial discharges (PD) and corona discharges in XLPE-covered conductors is crucial for power system diagnostics, yet remains limited by the lack of specialized, high-fidelity datasets for machine learning (ML) model development. This paper presents a high-resolution dataset (107 samples per 20 ms) acquired using a contactless dual-antenna system under controlled laboratory conditions simulating medium-voltage overhead distribution lines. …”
Get full text

Unleashing the Early Career Transition in Academic Medicine by David DH

“…Frontage Road, New Haven, CT, 06520, USA, Email daryn.david@yale.eduAbstract: In addition to advancing biomedical research and delivering cutting-edge clinical care, academic medical centers (AMCs) are tasked with training the next generation of physicians and scientists. …”
Get full text

Real-Time Landform Feature Detection and Segmentation Based on Heterogeneous MPSoCs for Lunar Robotic Exploration by Q. Fan, R. Duan, B. Wu, H. Zhou, S. Zhang, Y. Ma

“…FPGA-based MPSoCs are highly customizable and energy-efficient, making them advantageous for addressing the challenges of edge computing tasks in lunar robotic exploration. …”
Get full text

Salt and pepper denoising filters for digital images: A technical review by Kumar Abhishek, Kumar Sanjeev, Kar Asutosh

“…Up until now, researchers have presented several cutting-edge filters to overcome and lessen the impact of this noise. …”
Get full text

Advanced Battery Management for Electric Vehicles: Charge Monitoring and Fire Security by Romaisa Shamshad Khan, Abdul Aziz, Rehan Babar, Kashif Abbas, Nusri Elahi, Muhammad Abdullah Abdullah

“… A thorough study presented in this paper focuses on the design and development of a cutting-edge Battery Management System for Electric Vehicles (EV-BMS). …”
Get full text

Industry 5.0 in Smart Education: Concepts, Applications, Challenges, Opportunities, and Future Directions by Y. Supriya, Dasari Bhulakshmi, Sweta Bhattacharya, Thippa Reddy Gadekallu, Pratik Vyas, Rajesh Kaluri, S. Sumathy, Srinivas Koppu, David J. Brown, Mufti Mahmud

“…Industry 5.0 enables cooperation with such advanced technologies and the stakeholders in the education sector to ensure efficiency and effectiveness in the teaching-learning process. The present study provides an exhaustive review of the role of Industry 5.0 in smart education. …”
Get full text

BIBLIOMETRIC ANALYSIS OF MATHEMATICS EDUCATION APPLICATIONS INDEXED IN SCOPUS USING R STUDIO by Tanti Listiani, Melda Jaya Saragih

“…The significant rise in publications up to 2022 reflects a strong interest in educational technology for mathematics, while the decline in 2023 presents new opportunities for research in emerging innovations such as artificial intelligence and adaptive learning. …”
Get full text

Optimised RFO tuned RF-DETR model for precision urine microscopy for renal and systemic disease diagnosis by Neeraj Dahiya, Deo Prakash, Shakti Kundu, Shanu Rakesh Kuttan, Isha Suwalka, Manel Ayadi, Mitiku Dubale, Arshad Hashmi

“…Future work will focus on lightweight model variants, enhanced small-object detection, and domain adaptation using self-supervised and vision-language learning techniques.…”
Get full text

PEDOT:PSS-based bioelectronics for brain monitoring and modulation by Jing Li, Daize Mo, Jinyuan Hu, Shichao Wang, Jun Gong, Yujing Huang, Zheng Li, Zhen Yuan, Mengze Xu

Get full text

Real-Time Explainable Multiclass Object Detection for Quality Assessment in 2-Dimensional Radiography Images by Sadra Naddaf-Sh, M-Mahdi Naddaf-Sh, Hassan Zargarzadeh, Maxim Dalton, Soodabeh Ramezani, Gabriel Elpers, Vinay S. Baburao, Amir R. Kashani

“…In this work, a scalable, efficient, and real-time deep learning family of models for detection and classification of 10 various categories of weld characteristics on a real-world industrial dataset is presented. …”
Get full text

Carbon-Aware, Energy-Efficient, and SLA-Compliant Virtual Machine Placement in Cloud Data Centers Using Deep Q-Networks and Agglomerative Clustering by Maraga Alex, Sunday O. Ojo, Fred Mzee Awuor

“…The method combines a deep reinforcement learning model that learns optimum placement methods over time, carbon-aware data center profiling, and the hierarchical clustering of virtual machines (VMs) depending on resource constraints. …”
Get full text