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387 articles for “AI accuracy”
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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IoT and Sensor Technologies: Pioneering Smart Agriculture for a Sustainable Future
Abstract: Smart agriculture provides creative answers to important global problems including resource efficiency, environmental sustainability, and food security. It improves agricultural yields, reduces waste, and optimizes farming operations by combining technologies like IoT, AI, and big data. This strategy ensures dependable food supply for a growing population while minimizing environmental damage and promoting sustainable development. In addition to solving the problems facing agriculture now, smart agriculture opens the door to a …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 1–8 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Embarking on the Frontier: A Comprehensive Study of various traditional Technologies and creating awareness about latest technologies for Breast Cancer Screening amongst various Hospitals in India
Abstract: This extensive study explores the landscape of conventional technologies used in Indian hospitals for Breast Cancer Screening. The study comprehensively examines commonly used techniques, including Mammography, Ultrasound and Clinical Breast Examination in order to provide a holistic understanding of existing screening methods. The study also investigates how well-informed medical facilities are on the newest technology in breast cancer screening, including AI based methods.The acceptance rates and challenges involved with introducing …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 1, 2024 · pp. 80–86 Read article
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Optimization of Process Parameters for FDM Printed Tensile Test Specimens to Reduce Energy Consumption and CO2 Emission for Sustainable Manufacturing
Abstract: Three-Dimensional Printing (3D Printing) is one of the advanced manufacturing technologies which is being tremendously used in many fields because of its innovative applications. The concept of making a three-dimensional product by adding the material layer upon layer through Computer Aided Design (CAD) file data as input source is known as 3D Printing. Fused Deposition Modelling (FDM) is one of the leading technologies from all the available 3D Printing technologies, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 63–71 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Study on the Rocking Phenomenon of Parachute Rope
Abstract: With the constant development of computer technology and the development of numerical simulation techniques, the simulation of the dynamics of the parachute is becoming increasingly accurate. To eliminate the effects of large deformation of the grid in the conventional parachute simulation, we chose the parachute model using the smooth particle hydrodynamics method and performed a steady-state fluid-solid coupling numerical simulation, which is in good agreement with the calculated gas power …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–7 Read article
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Neuromorphic Spiking Neural Networks and Event-Driven Hardware: Architectures, Learning Paradigms, and Experimental Realizations
Abstract: With the current computational boom the research community is seeking for more sustainable energy efficient i.e. biologically inspired models of conventional Artificial Neural Networks (ANNs). Spiking Neural Networks (SNNs) known as the third generation of neural network models, provide a revolutionary approach by mimicking the asynchronized event-driven and temporally accurate signaling of the mammalian brain. Whereas conventional deep learning models operate with real-valued activations and dense matrix multiplications, SNNs use …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Design and Implementation of smart Grocery Packaging System
Abstract: The increasing demand for speed, accuracy, and cost efficiency in retail operations has accelerated the adoption of automation technologies in grocery packaging systems. Traditional grocery packaging methods rely heavily on manual labor, which often leads to errors in quantity measurement, inconsistent packaging quality, increased labor costs, and slower processing times. To address these challenges, this work presents the design and implementation of a smart automated grocery packaging system aimed specifically …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 46–52 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Wireless Sensor Network Localization Based on Static Anchor Node
Abstract: Anchor-based localization is a crucial challenge in wireless sensor networks (WSNs), aiming to determine the positions of all sensors by leveraging a limited number of anchor nodes whose locations are known. In this paper, we propose a novel algorithm for anchor-based localization in a static network, which improves the localization accuracy while reducing the computational complexity compared to existing methods. Our algorithm uses a range-based approach to estimate the distances …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 12–20 Read article
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Integration of Biosensors in Robotic Systems for Enhanced Environmental Monitoring
Abstract: Biosensors are analytical devices that use biological components, such as enzymes, antibodies, or nucleic acids, to detect specific chemical or biological substances. They have shown great potential in various fields, particularly in environmental monitoring, due to their sensitivity, specificity, and ability to provide real-time data. Integrating biosensors with robotic systems combines the strengths of both technologies, allowing for efficient data collection in remote, hard-to-reach, or hazardous environments. This integration enables …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 38–49 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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Container transportation in marine terminals and marine transportation infrastructure on the increase in export market share
Abstract: In order to achieve important policy goals like increasing global competitiveness, diversifying import sources, opening up new markets, and forging strategic partnerships, maritime transportation is essential. It also has a significant impact on reducing the economic vulnerability of nations that rely on the sale of gas and oil by carefully choosing its clients and growing the export of petroleum products, petrochemicals, and gas. This study develops a two-objective mathematical planning …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 36–42 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article