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51 articles for “big data processing”
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Unveiling Library Usage Patterns: A Python-based Descriptive Analysis of Big Data in Librarianship
Abstract: This study analyses circulation data from Vivekananda Library, Maharshi Dayanand University, Rohtak, Haryana, India, for the academic year 2022-23. The analysis is conducted using descriptive statistics and Python programming to understand library resource utilisation patterns, temporal trends, and user behaviour. The findings reveal distinct usage patterns across the four quarters, with variations in the number and types of transactions. Temporal trends show fluctuations in library usage based on academic calendars …
Published in Journal of Advancements in Library Sciences · Vol. 11, Issue 1, 2024 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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AI-Driven Product Management Assistants: Co-Pilot or Competitor for the Future PM?
Abstract: The emergence of Artificial Intelligence has led to a big transformation in the field of product management. When AI first came into picture, it was limited to the routine tasks but now AI assistants are able to handle a lot of decision making and streamline the execution process involved in product management. A major question with this emerging technology: can these assistants now or in future handle the work of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 58–63 Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Study on Cloud Computing’s Deployment Models
Abstract: Cloud computing represents a significant technological advancement in the information technology industry. It is one of the fastest-growing technologies, where computing resources are managed and allocated across the globe via the internet. Today, cloud computing is a key topic in many computer science curricula due to its extensive impact on various computing domains, particularly big data, which would be impossible without cloud computing. Cloud computing is an internet-based technology that …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 26–33 Read article
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A Novel Secure Cloud Storage Solution: Combining AES-OTP, RSA, and Time-Limited Access Control with Adaptive Key Management
Abstract: The reliance of cloud computing on the data processing and storage structure creates serious security risks. Ensuring availability, security, and integrity of data in cloud settings becomes a challenge for both the individual and the enterprise. This paper will, therefore, introduce a novel Hybrid Cryptographic Framework that combines RSA, One-Time Pad (OTP), and AES as a means of enhancing data security in cloud storage. It employs RSA for secure key …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 11–20 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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A Dynamic Text Compression Model for Big Data Applications Using Hadoop
Abstract: In today’s data-driven era, efficiently handling vast amounts of information has become increasingly important. Data compression plays a vital role in this regard — it is essentially a method of encoding information in such a way that significantly reduces the number of bits required to store or transmit a file. By shrinking data to its most compact form, compression techniques help save storage space, reduce bandwidth consumption, and improve the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 2, 2026 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article