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95 articles for “Pipelines”
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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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Blockchain Enabled IoT System for Tamper Proof Monitoring of Polymer Composite Manufacturing Quality
Abstract: Ensuring real-time process compliance in resin-based polymer composite manufacturing remains a persistent challenge due to non-linear material behaviors, unpredictable curing dynamics, and fragmented sensor data pipelines. Traditional centralized monitoring architectures struggle to guarantee data integrity, auditability, and adaptive response under high-frequency environmental fluctuations. Most existing frameworks fall short in unifying trust, traceability, and time-critical decision-making particularly during critical cure-phase deviations due to limited integration of blockchain with intelligent sensor systems. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 126–145 Read article
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IoT-Enabled Flexible Polymer Sensors for On-Body Health Monitoring and Real-Time Data Transmission
Abstract: Wearable health monitoring systems have grown increasingly vital in shifting care beyond clinical settings, yet many existing technologies remain hamstrung by rigid substrates and unreliable data streaming, impeding continuous and comfortable physiological assessment. Despite advances in flexible materials, most current sensor platforms suffer from limited mechanical endurance, signal instability under dynamic conditions, or an inability to sustain real-time wireless transmission. This work addresses those deficiencies by introducing a fully integrated, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 188–200 Read article
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RTL-to-GDSII Flow Optimization for Low-Power 32-bit RISC-V Processor
Abstract: This paper presents the implementation and optimization of a 32-bit RISC-V processor, transitioning from Register Transfer Level (RTL) design to final GDSII using Synopsys Fusion Compiler over 32nm technology node. The processor architecture is based on the RV32I base instruction set and incorporates a 5-stage pipeline to achieve a balanced trade-off between performance and design complexity. The design methodology involved RTL synthesis, gate-level netlist generation, and successive physical design stages …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 1–10 Read article
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Prediction of Depth-Induced Stress Distribution and Maintenance Cost Implications for Submerged Structural Components
Abstract: This study investigates the influence of water depth on stress distribution and structural integrity of submerged mechanical components . Structural models fabricated from mild steel, stainless steel, carbon steel, and copper alloy were examined under hydrostatic loading corresponding to water depths between 30 cm and 150 cm. Results indicate that normal and shear stresses increased proportionally with depth due to intensified hydrostatic pressure. Mild steel exhibited the highest stress concentrations, …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 29–35 Read article
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Regression Analysis of Topological Indices and Physicochemical Properties of Polymer-Based Anticancer Drugs
Abstract: The research analyzed the quantitative correlation between topological indices and the physicochemical properties of selected anticancer compounds using regression analysis. Various topological descriptors—such as the First Zagreb Index, Second Zagreb Index, and Forgotten Index were calculated and regressed against key molecular features, including polar surface area, melting point, and molar refractivity. The regression analysis revealed linear correlations between these topological indices and the properties of anticancer drugs, with particularly strong …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 255–267 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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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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Machine Learning-Driven Polymer Composite Smart Skin for Integrated Sensing in Soft Robotic Systems
Abstract: Soft robotics has grown rapidly, but its progress is still constrained by the limitations of current sensing skins. Most polymer-based sensors provide either flexibility or sensitivity, yet they struggle to deliver real-time communication and adaptive intelligence when deployed in complex robotic environments. This disconnect between material performance and system-level responsiveness forms a critical bottleneck for practical deployment. Existing approaches often treat tactile sensing and wireless communication as separate problems. As …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 121–136 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 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
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Hierarchical Computational Modeling of Physical Structure Across Quark, Nuclear, and Atomic Scales
Abstract: We present a modular, multi-scale computational framework that integrates physical modeling and visualization across quark, nuclear, and atomic scales within a unified pipeline. Developed to address the traditional fragmentation between sub-nucleonic, nuclear, and electronic representations, the system provides a continuous data flow and visualization bridge spanning from femtometers to ångströms. The framework consists of three primary modules: a particle-level module illustrating nucleons as confined quark-triplets with effective flux-tube geometries; a …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 Read article
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The Dual Crisis: Antibiotic Resistance and the Discovery Void – A Review of Novel Therapeutic Strategies and Non-Traditional Approaches
Abstract: The global rise of antimicrobial resistance (AMR) has emerged as one of the most critical public health challenges of the 21st century, threatening to undermine decades of therapeutic success and rendering conventional antibiotic regimens increasingly ineffective. Parallel to the escalating resistance rates is a profound “discovery void,” characterised by a steep decline in the development of new antibiotic classes since the late 20th century. Together, these two interconnected crises create …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 47–65 Read article
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An Efficient Vision-Based Algorithm for Hand Pose Estimation and Cursor Control
Abstract: Conventional input devices like the keyboard and mouse are no longer necessary because gestures are becoming more popular as the most natural way to interact with computers. This project has demonstrated a novel real-time system that lets users control their computer cursors using simple hand gestures. The system facilitates an easy operation for us in terms of the use of a cursor by using techniques and hand mark detections. The …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 24–35 Read article
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Polymer Composite Nodes for Smart IoT Environmental Monitoring: Applying ML-Calibrated RF Sensors for Exceptionally Low-Power, Flexible, and Dependable Performance
Abstract: The quick usage of the Internet of Things (IoT) for monitoring the environment needs sensor platforms that are accurate, responsive, adaptable, energy-efficient, and able to work in many different conditions. This work presents polymer composite nodes equipped with machine learning (ML)-calibrated radio-frequency (RF) sensors that adhere to stringent criteria. Sensor substrates built of flexible polymer matrices with conductive fillers are strong, light, and flexible enough to fit on surfaces that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1205–1221 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Plant-Derived Antimicrobials as Next-Generation Solutions to Multidrug Resistance
Abstract: The steady rise of multidrug-resistant (MDR) pathogens is reshaping how clinicians, researchers, and policymakers think about infection control. When bacteria acquire the ability to survive exposure to three or more antibiotic classes at once—whether through efflux pumps, enzyme-mediated drug destruction, target modifications, or reduced membrane permeability—treatment options narrow dramatically, hospital stays lengthen, and mortality climbs. Conventional pharmaceutical pipelines have struggled to keep pace with this biological arms race, pushing the …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 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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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article