Knee Osteoarthritis Detection and Classification Using Autoencoders and Extreme Learning Machines by Jarrar Amjad, Muhammad Zaheer Sajid, Ammar Amjad, Muhammad Fareed Hamid, Ayman Youssef, Muhammad Irfan Sharif

“…To test the generalizability of the Knee-DNS system, we utilized the Butterfly iQ+ IoT device for image acquisition and Google Colab’s cloud computing services for data processing. Conclusions: This work represents a pioneering application of autoencoder-based deep learning models in the domain of KOA classification, achieving remarkable accuracy and robustness.…”
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Grid Integration of PV Systems With Advanced Control and Machine Learning Strategies by Venkata Reddy Kota, Bapayya Naidu Kommula, Asif Afzal, Mohammad Asif, Liew Tze Hui

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EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

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A Cloud-Based Optimized Ensemble Model for Risk Prediction of Diabetic Progression—An Azure Machine Learning Perspective by V. K. Daliya, T. K. Ramesh

“…The experiment is performed and implemented in Microsoft’s Azure cloud, using Azure Machine Learning service, that leverages the advantages of cloud computing with respect to scalability, security and its potential integration possibilities into IoT-based smart healthcare systems.This aspect highlights its versatility and impact with respect to remote monitoring of patients as well. …”
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Geo-Intelligence for Resilient Land-use Planning by John Kiema

“…The methodology leverages open-source satellite data and cloud computing to map land potential zones, utilizing 50 years of historical data (1990-2040) to forecast future scenarios. …”
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Region search based on hybrid convolutional neural network in optical remote sensing images by Shoulin Yin, Ye Zhang, Shahid Karim

“…To overcome the above difficulty region search task, we propose an accurate and fast region search in optical remote sensing images under cloud computing environment, which is based on hybrid convolutional neural network. …”
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Changes of Water Turbidity in Liangzi Lake Based on Multi-temporal Remote Sensing by DENG Shi-quan, TIAN Zhi-han, BAI Ting, XIE Shan, LI Wen-kai, GU Huan-huan

“…Taking Liangzi Lake as the research object, this paper utilized Aqua MODIS remote sensing data from 2003 to 2021 on the Google Earth Engine (GEE) remote sensing cloud computing platform to invert the water turbidity of the Liangzi lake and analyze its spatiotemporal variation characteristics. …”
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Advancements in artificial intelligence and machine learning for poultry farming: Applications, challenges, and future prospects by Muhammad Halim Natsir, Wayan Firdaus Mahmudy, Mochamad Tono, Yuli Frita Nuningtyas

“…Edge-AI solutions further reduce latency and dependence on cloud computing, making on-site monitoring feasible in low-connectivity environments. …”
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High-Resolution Global Land Cover Maps and Their Assessment Strategies by Qiongjie Xu, Vasil Yordanov, Lorenzo Bruzzone, Maria Antonia Brovelli

“…., neural networks and transformers), and their direct application on powerful cloud-computing platforms. A comprehensive analysis of the temporal dimension of land cover products, where available, is conducted, highlighting a shift from decadal intervals to production intervals of less than a month. …”
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A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

“…With the rapid development and application of container cloud computing-related technologies, more and more applications are being deployed to container cloud clusters. …”
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RETRACTED: Assisting Smart Construction With Reliable Edge Computing Technology by Qiang Yue, Song Mu, Longguan Zhang, Zhun Wang, Zhun Wang, Zhonghua Zhang, Xing Zhang, Yongge Wang, Yongge Wang, Zhuang Miao, Zhuang Miao

“…However, as the amount of big data generated grows, processing and analytical issues arise. Cloud computing technologies are now being used to solve processing and analytical challenges. …”
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UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

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DimAug-TimesFM: Dimension Augmentation for Long-Term Cloud Demand Forecasting in Few-Shot Scenarios by Xiaoyi Yang, Qiming Zheng, Xiaoyu Zhu, Mianzhang Luo, Zheng Hou, Jiatai Zhang, Yuqing Lan

“…Accurate long-term cloud demand forecasting is critical for optimizing resource procurement and cost management in cloud computing, yet it remains challenging due to dynamic demand trends, limited historical data, and the poor generalization of existing models in few-shot scenarios. …”
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Energy-Aware Task Allocation for Multi-Cloud Networks by Sambit Kumar Mishra, Sonali Mishra, Ahmed Alsayat, N Z Jhanjhi, Mamoona Humayun, Kshira Sagar Sahoo, Ashish Kr. Luhach

“…In recent years, the growth rate of Cloud computing technology is increasing exponentially, mainly for its extraordinary services with expanding computation power, the possibility of massive storage, and all other services with the maintained quality of services (QoSs). …”
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Active Privacy-Preserving, Distributed Edge–Cloud Orchestration–Empowered Smart Residential Mains Energy Disaggregation in Horizontal Federated Learning by Yu-Hsiu Lin, Yung-Yao Chen, Shih-Hao Wei

“…In the proposed framework, edge computing that collaborates with the cloud to form edge–cloud computing can serve as converged computing from which load data gathered by distributed on-site edge devices for online load monitoring/smart energy disaggregation are globally consolidated through an artificial intelligence (AI) model in the cloud (cloud AI) and which the model that realizes global knowledge modeling is then deployed for global AI deployment at the edge (edge AI) via global knowledge sharing. …”
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Enhanced priority based task scheduling with integrated fault tolerance in distributed systems by Sheikh Umar Mushtaq, Sophiya Sheikh, Sheikh Mohammad Idrees

“…Fault tolerance in task scheduling is a fundamental challenge in cloud computing, particularly in dynamic environments where failures can disrupt task execution and degrade performance. …”
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Non-Invasive Glucose Monitoring Using Optical Sensors and Machine Learning: A Predictive Model for Nutritional and Health Assessment by Heru Agus Santoso, Nur Setiawati Dewi, Susilo, Arga Dwi Pambudi, Hanif Pandu Suhito, Iman Dehzangi

“…The IoT-based architecture enables seamless integration with cloud computing platforms, allowing remote access and scalability for large-scale population-level screening and monitoring. …”
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Paracetamol and dexketoprofen as the basis of multimodal anesthesia in secondary surgical treatment of head and neck blast injuries by D.O. Dziuba, D.O. Petyak, O.F. Melnyk, O.V. Reshetnyk, T.M. Ryzhenko, I.A. Chaikovsky

“…Clinical, laboratory, and instrumental methods were used, including assessment of psychoemotional state based on analysis of subtle changes on the electrocardiogram, namely heart rate variability, using cloud computing and artificial intelligence. Results. …”
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Global renewable energy transition: A multidisciplinary analysis of emerging computing technologies, socio-economic impacts, and policy imperatives by Herman Zahid, Adil Zulfiqar, Muhammad Adnan, Muhammad Sajid Iqbal, Anwar Shah, Salah Eldeen Gasim Mohamed

“…The technologies involved in achieving 100% seamless integration of renewable energy in the paradigm of smart grid and super smart grid include cyber-physical systems, Internet of things, metaverse, cloud computing and big data along with the other tools. …”
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A Robust Game Approach for On Spot Price Cloud Markets in Microservice-Based Applications by Hamta Sedghani, Mauro Passacantando, Riccardo Lancellotti, Mina Zolfy Lighvan, Danilo Ardagna

“…The evolution and widespread adoption of virtualization, service-oriented architectures, autonomic computing, and utility computing have converged, giving rise to Cloud Computing, which enables the on-demand delivery of software, hardware, and data as services. …”
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