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A bibliometric analysis: AI-driven data placement optimization in cloud replication environments
Published 2024“…Data placement strategy using artificial intelligence (AI) in cloud replication environments has garnered significant attention in recent years. …”
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A Survey on Information-Centric Networking with Cloud Internet of Things and Artificial Intelligence
Published 2022“…We initially rate the configuration of ICN with cloud or edge IoT and AI (ICN-CIoT-AI) in this study so that readers may learn about the latest trends and merging of ICN-CIoT-AI. …”
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Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases
Published 2022“…Latency in real-time processing is influenced by many factors such as artificial intelligence (AI) computing algorithm, device processing capabilities, the frameworks, and also the distance from the cloud infrastructure. …”
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Artificial Intelligence in accounting / Akma Hidayu Dol @ Abdul Wahid and Rafizan Abdul Razak
Published 2025“…Furthermore, AI algorithms can reconcile transactions and identify discrepancies. …”
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
Published 2022“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Feature-based face recognition system using utilized artificial neural network
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Intelligent DNA signature detection for internet worms
Published 2011“…Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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Crop yield prediction in agriculture: a comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability
Published 2024“…This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. …”
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Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development
Published 2023“…To demonstrate the practicality of using artificial intelligence (AI) to address these problems, the genetic algorithm is applied to genetic engineering (genetic mutation) of cowpea in a crop improvement program to generate useful bioinformatic information for further improvement of the crop. …”
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A Modular Intelligent Control Framework for Scalable Biohydrogen Production in Microbial Electrolysis Cells
Published 2025“…This review traces the evolution of five control paradigms, including voltage/proportional-integral-derivative (PID), model-based, adaptive, fuzzy logic, and artificial-intelligence (AI) systems, as well as hybrid intelligent controllers, and benchmarks each against scalability, dynamic responsiveness, and energy-recovery performance. …”
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Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph
Published 2023“…Corina delivering her speech titled "AI and SDGs: Resource-Based View Perspective." In the speech introduction, various definitions of Artificial Intelligence (AI) were provided. …”
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An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction
Published 2023“…In this study, an intelligent hybrid model using CNN and RNN for crop yield prediction is proposed. …”
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Final Year Project Report / IMRAD -
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Development Of An Intelligent Water Blending System For Irrigation Of Crops With Various Salinity Tolerance And Aquaculture
Published 2008“…The application of Artificial Intelligence (AI) systems in decision-making and intelligent control systems has recently gained attention of researchers. …”
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Implementing server-side federated learning in an edge-cloud framework for precision aquaculture
Published 2025“…Precision aquaculture involves the use of smart technologies such as sensors, cloud computing, and artificial intelligence to monitor and manage fish farming environments. …”
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A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients
Published 2024“…The other way around, AI is a limb of Computer Science dedicated to developing systems that do what a human does intelligently. …”
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How Can Aerial Imagery and Vegetation Indices Algorithms Monitor the Geotagged Crop?
Published 2024journal::journal article
