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816 articles for “machining time”
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Radio in the Age of AI
Abstract: Artificial intelligence (AI) is changing the traditional world of radio broadcasting very quickly. It is changing the way material is made, curated, shared, and listened to. This article talks about how AI technologies like machine learning, natural language processing, and automated voice synthesis can be used in radio production and operations. It looks at how AI-powered solutions may make listening more personalised, give real-time audience statistics, automatically generate news, and …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Determination of Well Loss and Aquifer Loss of New Construction Deep Water Well at Artesian Aquifer in Khulna City, Bangladesh
Abstract: This work studied the performance of water well installed as artesian aquifer in South Western Region of Bangladesh. The main activities were known to the properties of aquifer condition on that area. Well performance was also measured after development of water well. The well performance and aquifer performance were justified by Rorabaugh’s graphical methods. The total depth of drilling was 305 m from the ground level. Drilling was completed by …
Published in Recent Trends in Civil Engineering & Technology · Vol. 3, Issue 1, 2013 · pp. 8–13 Read article
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Drug Discovery and Design: Focus on computational approaches used in the discovery and design of new drugs
Abstract: Computational approaches have revolutionized the field of drug discovery and design, offering efficient and cost-effective strategies for identifying and developing new therapeutics. This review article explores the application of computational methods in drug discovery, with a focus on virtual screening techniques, molecular docking, molecular dynamics simulations, and quantitative structure-activity relationship (QSAR) models. Virtual screening plays a crucial role in narrowing down large chemical libraries by utilizing ligand-based and structure-based approaches. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 1, 2023 · pp. 26–30 Read article
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Examining the Crowd in Real-time with Deep Learning
Abstract: In this research, a model is proposed that can be used to estimate crowd density in a specific region and to establish social distances in accordance with predetermined rules. This is accomplished utilizing a multi-source model-based approach. In a small public gathering where hand counting is impossible, this technique conducts a survey. To do this, input video frames are extracted, each frame is processed, and then passed to the model …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 41–45 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Performance Analysis And Battery Management System Optimization In Electric Vehicles
Abstract: The rapid electrification of the automotive industry has led to an increased need for battery management systems that are not only efficient and safe but also intelligent. BMS is the device that guarantees the best use of the battery, prolongs its life, and allows its safe operation even under different environmental and load conditions. Through the synthesis of literature and industry practices, this paper acts as a tribute to the …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 Read article
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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Deploying Optimal Number of Sensors and Damage Detection in Structural Health Monitoring Using SEM-GA Method
Abstract: Detecting damages is the most important criterion in any engineering creation—be it a machine or a building. Among the engineering creation, civil engineering structures need a continuous monitoring to check their operations, performance and the health status of the structures. Damage detection cannot be done manually every time. Automated systems have to be developed in order to monitor the health of the structure periodically. Hence, structural health monitoring (SHM) aims …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 28–35 Read article
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Artificial Intelligence for Polymer and Nanocomposite Materials: Performance Prediction, Manufacturing Optimization, and Future Perspectives
Abstract: The exceptional mechanical properties, design flexibility, and lightweight nature of polymer composite and nanocomposite materials make them indispensable in a wide range of applications, including aerospace, automotive, construction, biomedical, and energy sectors. The optimization of the strength, durability, and manufacturing efficiency of polymer composite and nanocomposite materials is highly challenging because their performance depends on matrix composition, reinforcement type, fiber or nanoparticle distribution, interfacial interactions, processing conditions, and environmental factors. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
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Real Time Automobile - Caused Air Pollution Monitoring System
Abstract: The system proposed in this paper aims to be a novel approach for real-time detection and quantification of vehicular emissions, integrated into smart city infrastructures. The structured workflow enhances accuracy and efficiency. The license plate is captured by OCR, while the ground clearance is simultaneously measured, allowing the thermal camera to dynamically adjust its position to align with the tailpipe level. The emission data is collected and transmitted to a …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 49–55 Read article
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Parametric Study of Fused Deposition Modelling Process During Fabrication of Acrylonitrile Butadiene Styrene (ABS) Based Injection Molding Die
Abstract: The purpose of this study is to dictate an optimum process parameter during the fabrication of additively manufactured acrylonitrile butadiene styrene (ABS) based injection mold using fused deposition modelling methodology based additive manufacturing process and to assess the quality of the infection mold by analyzing the surface roughness of the injection mold, and the time taken in the manufacturing of the mold. The ABS PRO+ filament is used in manufacturing …
Published in Journal of Polymer & Composites · Vol. 10, Issue 1, 2022 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Smart Glasses Using Ultrasonic Sensor and AI for Blind Person
Abstract: Smart glasses has received considerable attention recently from people around the world. This research paper introduces a pioneering project, 'Smart Glasses Using AI and Ultrasonic Sensor,' aimed at revolutionizing the assistive technology landscape for visually impaired individuals. The project seamlessly integrates advanced hardware, including Raspberry Pi and Node MCU, with an array of sensors and state-of-the-art machine learning techniques, notably the YOLOv5 model. This paper presents a new paradigm in …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 1–9 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Sky Scanners: Using satellite remote sensing to figure out what Earth is like
Abstract: Satellite remote sensing has changed the way we look at, study, and learn about the Earth changing systems. Orbiting sensors take data from many different spectral bands, giving us constant, large-scale information about land, oceans, and the atmosphere. This study discusses the fundamental concepts of satellite remote sensing, including the various types of sensors, methods for data acquisition, and techniques for interpreting images. It talks about important uses like monitoring …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 22–33 Read article
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A Core Loss Model Based on Finite Element Method for Switched Reluctance Generator Considering Different Control Modes
Abstract: In the present paper, core loss modeling of switched reluctance generator (SRG) is proposed for the first time. Using ANSYS finite element (FE) package, 2D FE transient analysis of SRG is carried out and the stator pole flux waveform is predicted. To determine the flux waveforms in the different parts of the machine, an introduced mathematical flux model is considered and its algorithm is implemented in ANSYS Parametric Design Language …
Published in Trends in Electrical Engineering · Vol. 4, Issue 2, 2014 · pp. 26–33 Read article
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Uncovering the Elusive Threat: An Investigative Study on Polymorphic Viruses
Abstract: In the intricate landscape of cybersecurity, polymorphic viruses have prominently emerged, distinguishing themselves through their unique ability to continually modify their code, rendering them stealthy and challenging to detect. This comprehensive study embarks on a journey through the complex world of these viruses. It commences with a historical lens, meticulously tracing their roots, their initial manifestations, and the progressive sophistication of their code-altering techniques. The research then pivots to a …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 10–21 Read article