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56 articles for “pipeline integrity”
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Ensuring Pipeline Longevity: Key Factors for Durability in the Oil and Gas Industry
Abstract: This article explores the durability of pipes in the oil and gas industry, focusing on critical aspects such as remaining life, anti-wax coatings, life extension strategies, and the implications of oil spills and leaks. Corrosion is identified as a significant threat to pipeline integrity, influenced by various corrosive substances. Standards like API 581 and API 571 help assess corrosion rates and remaining life of pipelines transporting different crude oils. Additionally, …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 19–24 Read article
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Innovative Biosensor Applications in Petroleum Industry for Enhanced Monitoring and Safety Measures
Abstract: The petroleum industry is fundamental to the global economy, providing the energy and raw materials that drive modern society. However, this industry faces a myriad of challenges, including ensuring the safety of operations, monitoring critical processes effectively, and minimizing environmental impacts. Traditional monitoring techniques, while valuable, often fall short in delivering real-time data and comprehensive insights into operational parameters. These limitations can result in delayed responses to potential hazards and …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–13 Read article
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Mechanically Operated Portable Hydrotesting Setup
Abstract: Hydrostatic testing is a crucial process in ensuring the integrity and safety of pressure vessels, pipelines, and various other industrial equipment. Traditional hydrostatic testing setups often require significant infrastructure and resources, limiting their accessibility and flexibility, especially in remote or constrained environments. This research paper presents the design, development, and implementation of a portable hydro testing setup tailored to address these challenges. The proposed setup offers a compact, versatile, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 21–27 Read article
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Study and analysis of the Double Data Rate SDRAM Controller for High-speed Interfacing with Processing Device
Abstract: A real-time embedded system must now manage many programs running concurrently. Increased Data Rate Because of its burst access, speed, and pipeline features, synchronous DRAM is a typical memory-building material. DDR transfers are performed using synchronous dynamic access memory. The memory controller must be set with a pipelined design for various applications and systems to perform effectively. The purpose of this study is to design a DRAM controller that will …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 8–13 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering
Abstract: Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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Design and Implementation of an IoT-based Traffic and Parking Management System Integrated with GIS for Urban Environments
Abstract: As urbanization accelerates, managing traffic flow and parking availability has become increasingly challenging. This article presents the design and implementation of an internet of things (IoT)-based traffic and parking management system integrated with geographic information systems (GIS) to address these challenges in urban environments. The proposed system utilizes a network of IoT sensors to monitor traffic flow, congestion levels, and parking space availability in real time. The data collected by …
Published in Trends in Transport Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 23–32 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Advances in Shell Programming: Techniques, Tools, and Emerging Trends
Abstract: Shell programming has undergone a significant transformation, shifting from simple command-line interactions to a mature, versatile scripting environment that supports modern computing needs. Over time, shells such as Bash, Zsh, and PowerShell have expanded far beyond basic task execution, evolving into powerful tools capable of handling complex automation workflows, system configuration tasks, and cross-platform orchestration. These environments now offer improved error handling, stronger security features, integrated performance-monitoring options, and more …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Optimizing DevOps Pipelines with Maven: Advanced Build Automation Techniques
Abstract: As modern software development continues to evolve, DevOps has become a fundamental methodology for integrating development and operations teams to enhance collaboration, reduce software delivery time, and improve overall product quality. Automating builds is a crucial aspect of any DevOps pipeline, as it helps maintain consistency and dependability throughout the different phases of the development process. Maven, a robust build automation tool commonly used in Java projects, is instrumental in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 06–11 Read article
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Enhanced Shell Script Optimization Techniques for Low-latency Automation in DevOps Environments
Abstract: Shell scripting remains a foundational component in system administration and DevOps automation, providing a straightforward yet powerful method for automating tasks, managing system configurations, and integrating seamlessly within continuous integration and continuous delivery (CI/CD) pipelines. These scripts serve as the backbone for many repetitive and complex tasks, enabling IT teams to execute workflows efficiently without manual intervention. As organizations continue to scale their infrastructure and adopt more complex architectures, the …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article