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895 articles for “Accuracy”
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IoT and Node MCU based Smart Logistics
Abstract: Logistics plays a key role in global economies, encompassing the planning, implementation, and control of goods movement. Traditional logistics systems often suffer from inefficiencies, such as manual tracking, delays, and lack of real-time visibility, leading to increased costs and environmental waste. The advent of IoT has revolutionized this sector by enabling interconnected devices to gather and argument data seamlessly. At the heart of many IoT applications is Node MCU. It …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 38–50 Read article
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Polymer-Integrated Smart Biomedical Waste Management System Using AI and Sensor-Based Segregation
Abstract: Biomedical waste, which comes from healthcare facilities like hospitals, clinics, and labs, includes both infectious and non-infectious materials. This can range from sharps and pathological waste to pharmaceutical leftovers and general medical trash. If this waste isn't handled, sorted, and disposed of properly, it can pose serious contamination risks, leading to infections, workplace hazards, environmental damage, and public health emergencies. Traditional biomedical waste management often relies on manual sorting, which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 172–184 Read article
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Generic Virtual Mouse
Abstract: The mouse and keyboard have been replaced by new input mechanisms brought about by the quick development of Human-Computer Interaction (HCI). Using computer vision and deep learning techniques, this study explores the possibility of replacing actual mouse inputs in a computer system with hand gestures. We created a virtual mouse system that uses a normal webcam to record hand motions. Computer vision algorithms then process these gestures to handle mouse …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Handwritten Sanskrit Word Recognition: A Deep Learning Approach Using AlexNet
Abstract: Handwritten Sanskrit word recognition poses significant challenges due to the intricate structure of the script and the considerable variations in handwriting across individuals. To address these challenges, this research introduces a novel methodology employing transfer learning with the AlexNet convolutional neural network. The study utilized two distinct datasets: a specifically curated Sanskrit word image dataset containing 2616 samples, alongside a broader Devanagari character dataset used for validation purposes. The established …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Advanced Functional Polymers and Their Synergistic Role in Smart Composite Materials for Sustainable Industrial Applications
Abstract: Advanced functional polymers have revolutionized composite materials, offering enhanced properties such as self-healing, electrical conductivity, environmental adaptability, and high mechanical strength. These innovations are reshaping industries by enabling smarter, more efficient, and sustainable solutions. Functional polymers play a pivotal role in producing high-performance composite materials to meet the growing demands of sustainable industrial applications. Significant improvements in material properties mechanical strength, durability, thermal stability, and recyclability are achieved through the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 12–27 Read article
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Investigative Study of Adaptive Fault Tolerance in Optical Networks
Abstract: Optical networks have become the backbone of modern telecommunications infrastructure, enabling high-speed data transmission across global networks. However, these networks face significant reliability challenges due to component failures, signal degradation, and environmental factors. This investigative study examines adaptive fault tolerance mechanisms in optical networks, focusing on emerging technologies and methodologies that enhance network resilience. The research analyzes various fault detection techniques, including machine learning-based approaches, self-healing protocols, and dynamic reconfiguration …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 24–30 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Exploring Spirituality and Cognitive Styles as a Predictor of Suicidal Ideation in Urban Population
Abstract: Suicidal ideation, or the thought of suicide, is a complicated and multi-dimensional issue of public health that effects individuals globally at a individual level, in families and in society at large. It is one of the main causes of death in the world. Beliefs, practices and experiences pertaining to the transcendence, sacred or divine, are all included in the broad category of spirituality. In cognitive psychology, the term "cognitive style" …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
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Adoption of Artificial Intelligence in Periodontal Diagnostics: Awareness, Confidence, and Barriers Among Dental Practitioners in India
Abstract: AI has emerged as a transformative tool in healthcare, including periodontics, where it aids in diagnosing periodontal diseases, assessing bone loss, and predicting disease progression. Despite its potential, the adoption of AI in dentistry, particularly in India, remains limited. This study aimed to evaluate the awareness, confidence, and willingness of dental practitioners to adopt AI-based tools in periodontal diagnostics. A cross-sectional survey was conducted among 106 dental practitioners, including general …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 27–38 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Simulation and Experimental Analysis of Heat Treatment for Steel Tie Rods: A Review
Abstract: The study is related to the actual heat treatment and simulation of the physical deformation of the steel tie rod and compares the observations for process optimization. The general methodology is to go for either traditional or induction hardening after getting the chemical composition of the material, followed by tempering, which is a key technique for improving the mechanical properties of materials, strength, hardness, etc., and to release stresses. This …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 43–51 Read article
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Enhancing Glaucoma Diagnosis with Deep Learning: A Study Using ResNet-50 and DenseNet-121
Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, mainly resulting from progressive optic nerve damage, often related to elevated intraocular pressure. Early detection is essential to prevent vision loss, but traditional diagnostic methods rely on specialized equipment and trained professionals, making large-scale screening difficult. This study uses a publicly available fundus imaging dataset to explore the effectiveness of deep learning models for glaucoma detection. These datasets provide medical images, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 9–18 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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Smart Bionic Hand: Combining Hardware and AI For Adaptive Prosthetic Functionality
Abstract: This research paper presents the development and integration of a bionic arm that leverages both hardware components and artificial intelligence (AI) models for enhanced functionality and user interaction. The hardware design includes key components such as servo motors, an Arduino UNO microcontroller, electromyography (EMG) sensors, and a lithium-ion battery. The EMG sensors detect muscle signals, which serve as inputs for controlling the arm's movements, while the servo motors are responsible …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Cervical Leiomyomas: Age associated insights from 3 Year prospective study from Tertiary Care Hospital
Abstract: Cervical leiomyomas are rare benign smooth muscle tumours of cervix, often presenting diagnostic challenges due to their uncommon occurrence and overlapping features with other cervical pathologies. This is a 3-year prospective study involving a total of 460 female subjects who were diagnosed with various gynecologic complications, with a particular focus on cervical leiomyomas. The study aims to provide a comprehensive age-wise distribution of cervical leiomyomas, emphasizing the incidence and prevalence …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article