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123 articles for “big data”
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Supply Chain Optimization Using Big Data
Abstract: In the references to add productivity and short the appendences, and increase customer value, supply chain optimization is a very crucial part of contemporary business operations. Supply chain management has been transformed by the emergence of big data, which can provide analysis and insight from many different sources of information. This content explores the importance of using big data analytics to improve the delivery process. Thanks to the evolution of …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 19–25 Read article
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Decoding Big Data: A Practical Comparison Between Hadoop and Spark
Abstract: This paper conducts a comprehensive comparison of Apache Hadoop and Apache Spark, two essential frameworks in the big data era. The rapid expansion of data possesses challenges in terms of volume, variety, and velocity, which necessitate advanced processing solutions. Hadoop, utilizing its MapReduce paradigm, provides scalable and fault-tolerant storage, whereas Spark, built upon Hadoop, introduces in-memory processing to increase speed and flexibility. This study includes a detailed examination of their …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 15–23 Read article
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Smart Soil Health Monitoring: Leveraging Sensors and Big Data to Optimize Crop Growth
Abstract: The increasing demand for sustainable farming practices has necessitated the development of innovative technologies that improve crop productivity while reducing environmental harm. This study investigates the combination of internet of things (IoT) sensors and big data analytics for real-time soil health monitoring, with the aim of maximizing crop yield and efficient resource management. This allows for informed decision-making in key agricultural practices, such as fertilization, irrigation, and crop rotation, based …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 36–43 Read article
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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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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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AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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Smart Infrastructure Systems: A New Era in Civil Engineering and Infrastructure Management
Abstract: Civil engineering has experienced a significant technological shift due to the adoption of smart infrastructure systems. The integration of the Internet of Things (IoT), artificial intelligence (AI), and big data analytics has facilitated real-time monitoring, predictive maintenance, and improved infrastructure management. These advancements have transformed the planning, design, and operation of roads, bridges, water systems, and buildings. By employing smart sensors and AI-driven algorithms, engineers can now optimize the entire …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 38–43 Read article
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Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 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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Research Challenges in the Era of AI and Digitization for Sustainable Supply Chains
Abstract: Two main topics have an impact on the adoption of sustainability as a worldwide business mandate. The first is admitting that global supply networks have an impact on sustainability and that "greening" the chain as a whole is necessary. Technology, encompassing "big data," artificial intelligence (AI), and digitization, is the second. These ideas are now widely accepted. These innovations are transforming how firms design and manage their supply chains, which …
Published in Journal of Production Research & Management · Vol. 14, Issue 1, 2024 · pp. 1–10 Read article
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Advancements in Smart Manufacturing: A Review of Industry 4.0 Technologies and Integration Strategies
Abstract: A new era of production known as “Smart Manufacturing,” which is primarily motivated by the ideas of Industry 4.0, has been brought about by the quick development of digital technologies. The goal of this technology revolution is to develop intelligent, adaptive, and networked production systems that react instantly to shifting supply, demand, and operating circumstances. The Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), cyber-physical systems (CPS), big …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 31–36 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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Study of the Trends and Customer Buying Behaviour in The Automobile (Car) Industry
Abstract: This study examines car buying behavior in India, one of the largest automotive markets globally, contributing significantly to the Gross Domestic Product (GDP). Understanding how consumers decide on car purchases is essential for manufacturers and marketers. The research involved a comprehensive methodology, including a literature review, questionnaire design, survey distribution, and data analysis, to gain insights into Indian car buyers' preferences and trends. The findings reveal that young adults, primarily …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 9–18 Read article
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Digital Transformation in Public Transport Management
Abstract: The digital transformation of public transport systems has emerged as a critical driver for improving urban mobility and addressing the growing challenges of congestion, inefficiency, and environmental sustainability. Public transport management systems are advancing through the integration of cutting-edge technologies like cloud computing, artificial intelligence (AI), big data analytics, and the Internet of Things (IoT). These innovations enhance efficiency, intelligence, and user experience, making transportation more seamless and responsive to …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 17–21 Read article
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Advances in Data Security in Cryptography
Abstract: In the ultra-modern period, evaluation of networking and wireless networks within information and communication technology has brought many changes to deal with this technology using internet, growing strongly over the past several decades, data security has come a main concern for anyone connected to the web. Data security ensures that our data can only be accessed by authorized recipients and prevents any unauthorized access or alteration of the data. We …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 1–7 Read article
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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 Read article
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The AI Revolution: Transforming Business Decision-Making
Abstract: Industries undergo a transformation thanks to artificial intelligence, which makes machines capable of activities that previously required human intelligence. This interdisciplinary field of computer science models human thought processes, impacting sectors from autonomous vehicles to creative AI tools. Integrating AI into business operations transforms decision-making and enhances corporate performance. AI-driven methodologies analyze vast datasets to provide valuable insights and facilitate decisions beyond human capability. Predictive modeling anticipates consumer behavior, market …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 25–32 Read article