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445 articles for “Machine tools”
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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Contribution Of Indian Historical Technology To Development The AI
Abstract: The Indus Valley Civilization (3300–1300 BCE) was among the first in the world to develop advanced metallurgy. They created bronze tools, copper vessels, and intricate metal ornaments. A testament to ancient Indian metallurgy, this rust-resistant iron pillar, built during the Gupta Empire, still stands without significant corrosion, demonstrating an advanced understanding of material science. The study examines key texts and technologies, including Panini’s Ashtadhyayi (a formal system of grammar resembling …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 Read article
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A Critical Review of the CBDRM Project in District Charsadda
Abstract: Pakistan, being a least developed and economically sluggish country, cannot widely support and implement the community projects for its nation. Community development projects in Pakistan mostly rely on foreign aids. The agenda behind this support to the least developed countries is to facilitate them in achieving the millennium development goals. The charter of United Nations also encourages the promotion of social progress and better standards of life by the employment …
Published in Journal of Industrial Safety Engineering · Vol. 3, Issue 2, 2016 · pp. 19–22 Read article
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Google Play Store Analysis
Abstract: Google play store consists of millions of applications and several thousand apps are added on the play store every day. The competition is so fierce that it is really difficult for the developers to find out whether the app that is the product of his hard work is going to be successful or not. The main goal of the study is to create a tool that helps developers and organizations …
Published in Journal of Open Source Developments Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
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The Role of Automation in Modern Healthcare: Innovations and Impact.
Abstract: Automation technology encompasses a broad array of systems and tools designed to perform tasks with minimal human intervention, thereby increasing efficiency, reducing errors, and enhancing productivity. This study explores the core components of automation technology, including sensors, actuators, controllers, and software, and examines their applications across various industries. In manufacturing, automation leads to significant improvements in production speed and precision. In healthcare, it enhances patient care and operational efficiency. In …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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Artificial Intelligence in Trigonometry: Innovations, Applications, and Future Prospects
Abstract: Artificial Intelligence (AI) has transformed numerous scientific fields, yet its integration with classical mathematics such as trigonometry is still emerging. This paper explores how AI enhances trigonometric problem solving, learning, and real-world applications. We analyse AI-driven tools for teaching trigonometry, AI in geometric and spatial reasoning, usage in robotics and computer vision, and future directions for research. Key challenges, methodologies, and case studies are discussed to provide a comprehensive overview …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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Editorial: Advancements in Movement Analysis for Understanding Neurological Disorders
Abstract: Neurological disorders pose a significant challenge, demanding innovative approaches for accurate diagnosis, effective treatment, and deeper understanding. Movement analysis emerges as a powerful tool, offering a quantitative window into the complexities of motor function. This editorial delves into the transformative impact of movement analysis on neurological research and clinical practice. Traditional diagnostic methods, reliant on subjective observations, often miss subtle motor impairments, particularly in early disease stages. Movement analysis tackles …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 28–32 Read article
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Adventure Masterclass Travel App: Enhancing Experiences and Connectivity
Abstract: In an era where travel enthusiasts seek unique and exhilarating experiences, adventure tourism has emerged as a burgeoning sector in the global travel industry. This project aims to develop a mobile application tailored specifically for adventure travelers, catering to their diverse needs and preferences while ensuring seamless planning and execution of their expeditions. The proposed adventure travel application will integrate a plethora of features designed to enhance the overall travel …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 3, 2024 · pp. 1–10 Read article
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A Comprehensive Guide to Application Development Using Flutter
Abstract: Developers are forced to either write the same application many times for other operating systems or use a similar but inferior solution that compromises native performance and accuracy in favor of portability. Flutter is a toolkit developed by Google that helps programmers create apps that look and feel great on different devices like phones, tablets, and computers. What is special about Flutter is that one can write code once and …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 35–41 Read article
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Emerging Role of Drone Technologies in Environmental Research: Trends, Applications, and Future Directions
Abstract: Unmanned aerial vehicles (UAVs), commonly called drones, have rapidly transformed environmental research and management over the past decade. Their flexibility, improving sensor payloads, and ability to collect high-resolution spatial and temporal data make them powerful tools across disciplines — from biodiversity monitoring and precision agriculture to water quality assessment and disaster response. UAVs bridge the gap between ground-based surveys and satellite remote sensing by offering near-real-time, fine-scale data acquisition that …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 34–42 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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AbhiGyam: A Machine Learning Model-driven Research Platform for Assessing Accessibility Infrastructure in Indian Cities
Abstract: This work presents AbhiGyam, a machine learning-driven research platform designed to streamline and automate the assessment of accessibility infrastructure in Indian cities. AbhiGyam leverages the Google Maps API to transmit street view images to the backend, where computer vision techniques are implemented using OpenAI's CLIP (Contrastive Language-Image Pre-training) model to identify objects such as ramps, sidewalks, crosswalks, and parking spaces. The accuracy of the model is validated using labeled data …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 84–91 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Linear Programming for Profit Optimization in Small-Scale Manufacturing: A Python-Based Simplex and Machine Learning Approach
Abstract: Profit maximization under resource constraints is a classic challenge. Small manufacturers face tight margins and scarce capital every day. This paper tackles that problem using four Python-based methods. The case study is Bintang Bakery in Bandar Lampung, Indonesia. The bakery makes three bread types and faces 18 resource constraints. Data comes from Anggoro et al. Methods tested include LP revised simplex, Differential Evolution, PSO, and ANN Surrogate. General-purpose scipy minimizers …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 01–11 Read article