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203 articles for “deployment models”
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A Five-Layer Architectural Framework for Sustainable and Scalable AI Systems
Abstract: Artificial Intelligence (AI) is not only about algorithms. AI works like a full “stack” of layers, from electricity to real-world user applications. In this paper, we explain a simple and student-friendly Five- Layer Architecture of AI: (1) Energy, (2) Chips, (3) Infrastructure, (4) Models, and (5) Applications. Each layer supports the next layer, like a cake with multiple layers. If any layer is weak, AI systems become slow, costly, or …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Process Mapping and Bottleneck Analysis of the Wellness Provider Deployment Cycle
Abstract: This Study focuses on understanding how a wellness service provider company currently manages the process of assigning wellness professionals—such as fitness trainers, doctors, and mental health experts—to corporate clients, and where delays tend to occur within that process. As the organization follows an aggregator-based service model, it works with a wide network of freelance professionals spread across multiple cities. While this approach allows flexibility and rapid expansion, it also makes …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 26–32 Read article
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Simulation of Different Propagation Models for WiMAX channel under Different Environments
Abstract: Today the Worldwide Interoperability of Microwave Access (WiMAX) technology is gaining popularity and gaining increasing acceptance as a Broadband Wireless Access (BWA) system. It is a IEEE 802.16 standard wireless communication technology that provides high speed data over a wide area. It is a point-to-point technology for using a multi-point wireless network. It has potential success in its line of sight (LOS) and non-linear (NLOS) operating conditions under the frequency …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 2, 2021 · pp. 35–45 Read article
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Study Of Uber-Related Data Using Machine Learning
Abstract: This paper describes the operation of the machine learning algorithm used in the Uber database, which contains data generated by the Uber Movement for a few locations in Hyderabad and the big apple City. Uber is known as a peer-to-peer program. This program connects you to the nearest drivers available to take you to your destination. This database includes Uber capture data with information such as time, ride date additional …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 1–6 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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A Technical Blueprint for AI-Driven Localization in 6G Mobile Networks
Abstract: The advent of sixth-generation (6G) wireless systems promises unprecedented spatial resolution, ultra-low-latency, and pervasive connectivity, turning mobile localization from a peripheral service into a core enabler of immersive extended reality (XR), autonomous logistics, and digital twins. Yet, the sheer scale of dense terahertz (THz) deployments, the stochastic nature of reconfigurable intelligent surfaces (RIS), and the dynamic interference landscape render traditional model-based positioning techniques inadequate. This work investigates how artificial intelligence …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 26–34 Read article
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Life Cycle Assessment (LCA): A Tool for Sustainable Development and Environmental Management of Products
Abstract: Life cycle assessment (LCA) is a crucial technique for clearly understanding how much room there is for product improvement in a given good or service. Because of its high cost and application in eco-design, supply chain management, green buying, sustainable investing, and other relevant activities, manual data engineering and analysis processes. Traditional LCA methodologies and technology may need more scalability regarding substantial product portfolios and expanding reporting requirements. The Sustainability …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 2, 2023 · pp. 16–25 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Study of 5G Technology and its impacts - Review
Abstract: Digitization is an ongoing revolution in the manufacturing industry. 5G technology is expected to play an important role in providing connectivity. Digitized factories place high demands on technical availability and therefore also on maintenance performance. However, it is difficult to incentivize senior decision makers to invest in maintenance, as impacts are often delayed and difficult to verify upstream. To quantify long-term effects, discrete event simulation (DES) has been identified as …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 3, 2021 · pp. 40–50 Read article
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Scaling Cost Model for the Economics of Concentrated Solar Power Plants
Abstract: Concentrated Solar Power (CSP) is a renewable energy technology that can provide clean and reliable energy to regions with adequate environmental resources. Especially for the regions around the Mediterranean Sea, where solar radiation is significant, this technology seems to have great potential to meet the medium and long-term targets for emission-free energy production, once cost-related issues have been resolved. Factors such as the capacity of the plant, the efficiency of …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 2, Issue 1-3, 2012 · pp. 74–87 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques
Abstract: This paper explores the current cybersecurity landscape surrounding Unmanned Aerial Systems (UAS), commonly known as drones. With rapid growth in commercial and recreational drone use, the risk of cyber-attacks has also increased. This study highlights real-world vulnerabilities such as GPS spoofing, Wi-Fi hijacking, and firmware exploitation. It also suggests practical mitigation techniques, including encryption, real-time anomaly detection using machine learning, and secure communication protocols. The goal is to support researchers, …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 1–8 Read article
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Paradigm of Artificial Intelligence in Business Management
Abstract: Artificial intelligence stands out as a prominent trend in today's technological landscape, enabling machines to engage in human-like thinking, learning from experiences, adapting to new inputs, and making decisions. This capability facilitates rapid and error-free results, akin to human rational decision-making. In the contemporary business landscape, which is often regarded as a cornerstone for national development, artificial intelligence plays a pivotal role. Businesses, ranging from small-scale enterprises to medium-sized ones …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 26–30 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Serverless Computing in Personal Internet of Things (PIoT): Current Trends & Future Perspectives
Abstract: Serverless computing has played a great role in the deployment of the various services and applications including the Personal Internet of Things (PIoT). It illustrates the transformation of cloud programming models, their platforms, and the hiding of inessential details. It is proof of capability and immense endorsement of cloud technologies. In the following study, we analyze the concept of Serverless Computing in the Personal Internet of Things (PIoT), the current …
Published in Current Trends in Information Technology · Vol. 11, Issue 2, 2021 · pp. 1–7 Read article
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A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article