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129 articles for “healthcare experience”
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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An Evaluation of the Impact of a Nurse-Led Program on Knowledge and Practices Related to Needle Stick Injury Prevention Among 2nd Year B.Sc. Nursing Students at the College of Nursing, PT. B.D. Sharma PGIMS, Rohtak
Abstract: Healthcare workers and nursing students frequently face accidental occupational exposures while caring for patients, with needle stick injuries being the most common form of exposure in healthcare settings. These injuries pose a significant risk of infections. This study aimed to evaluate the awareness and practices related to the prevention of needle stick injuries among second-year B.Sc. Nursing students, assess the effectiveness of a nurse-led intervention in enhancing their knowledge and …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 28–66 Read article
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The Future of Computing: Exploring the Impact of 3D Technology
Abstract: In the evolving landscape of computing, the integration of three-dimensional (3D) technology has revolutionized various industries, from entertainment to healthcare. “Computers in the 3-D World” explores the transformative impact of 3D computing, focusing on how advances in hardware and software are enabling new forms of interaction, visualization, and simulation. The study explores the key technologies behind this transformation, including virtual reality (VR), augmented reality (AR), 3D modeling, and 3D printing. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 01–19 Read article
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Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems
Abstract: The integration of Artificial Intelligence (AI) in nursing education offers significant potential to enhance learning experiences by personalizing education, improving knowledge retention, and developing clinical competencies. This study evaluates the effectiveness of AI-driven adaptive learning systems compared to traditional lecture-based teaching methods in nursing education. A mixed-methods approach was used, with 200 nursing students participating in a quasi-experimental design. The intervention group (100 students) used AI-powered adaptive learning platforms for …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 2, 2025 · pp. 29–34 Read article
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Exploring Robotic Arm Fabrication: An In-depth Review of Current Trends
Abstract: Robotic arms have emerged as indispensable tools across a myriad of industries, revolutionizing manufacturing processes, medical procedures, and even everyday tasks. This comprehensive review explores the recent advancements in robotic arm technology, focusing on key developments in design, control, sensing, and applications. The review begins by examining the evolution of robotic arm design, highlighting innovations in materials, actuators, and kinematic configurations that have enhanced the performance, versatility, and dexterity of …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 3, 2024 · pp. 28–41 Read article
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A Descriptive study to assess the prevalence of Nomophobia among Nursing students in Chirayu College of Nursing Bhopal (MP).
Abstract: Nomophobia, defined as the fear or anxiety of being without access to a mobile phone, has emerged as a growing behavioral concern in the digital age, particularly among young adults. Nursing students are especially vulnerable due to their extensive reliance on smartphones for academic, clinical, and social purposes. The present descriptive study was conducted to assess the prevalence of nomophobia among nursing students at Chirayu College of Nursing, Bhopal (Madhya …
Published in Journal of Nursing Science & Practice · Vol. 16, Issue 1, 2026 · pp. 36–41 Read article
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Exploring Phytomedicine: Innovations, Efficacy and Future Directions
Abstract: The use of plant-derived substances for therapeutic purposes has long been a cornerstone of traditional medicine systems worldwide. With increasing interest in natural remedies, the field of phytomedicine is experiencing a revival, marked by innovations in research, formulation, and application. This review article explores recent advancements in phytomedicine, highlighting novel extraction technologies, and the efficacy of plant-based treatments in clinical settings. The review also addresses the challenges faced in phytomedicine …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 2, 2025 · pp. 32–50 Read article
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Barg-e-Tulsi (Ocimum sanctum Linn.) in Unani Medicine: Bridging Classical Therapeutics with Contemporary Pharmacological Evidence
Abstract: In the Unani System of Medicine (USM), Barg-e-Tulsi (Ocimum sanctum Linn.), commonly known as Tulsi or Holy Basil, is a highly valued medicinal herb that has been extensively used for centuries in the prevention and treatment of various ailments. It occupies an important place in traditional Unani therapeutics due to its broad spectrum of medicinal properties and its effectiveness in managing respiratory, gastrointestinal, neurological, and infectious disorders. Classical Unani scholars …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 2, 2026 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Unresolved and misdiagnosed of floating sensation in young man
Abstract: Persistent Postural-Perceptual Dizziness (PPPD) stands out as a prevalent peripheral vestibular disorder, earning its recognition in the International Classification of Vestibular Disorders in 2017. Characterized by chronicity, this condition manifests symptoms persisting for more than three months, encompassing a disconcerting array such as a floating sensation, unsteadiness, and dizziness. Notably, individuals afflicted with PPPD often report symptom exacerbation following prolonged standing, self-initiated motion, or exposure to dynamic visual stimuli. This …
Published in International Journal of Brain Sciences · Vol. 1, Issue 1, 2024 · pp. 1–4 Read article
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Unravelling the Impact of AI: Insights into Pattern Recognition and Image Processing
Abstract: Apart from its academic origins, the evolution of Artificial Intelligence (AI) has emerged as a notable influence in shaping our daily experiences. Artificial intelligence, which focuses on domains such as image processing and pattern recognition, encompasses a vast array of topics, including its complex applications, obstacles, and societal repercussions. Machine Learning, Natural Language Processing, Computer Vision, Robotics, Expert Systems, Knowledge Representation, and AI Ethics are among the domains in which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 1–7 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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Design Principles and Applications of Virtual Telepresence Robots: A Comprehensive Review
Abstract: The primary objective of this project is to develop an advanced virtual telepresence robot system that facilitates remote communication and collaboration in various environments. Through the integration of cutting-edge robotics, sensing, and communication technologies, our virtual telepresence robot enables real-time interaction between users located at different physical locations. This technology combines wireless connectivity, robotics, and user interfaces to provide people with an immersive experience. This study explores the development, functionality, …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 11–18 Read article
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Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT
Abstract: The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 18–31 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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SIBR/Aloe barbadenis Mill.: A Review on Medicinal Utility from the Perspective of Unani Medicine
Abstract: Aloe barbadensis Mill., known as Sibr in Unani medicine, is a time-honored medicinal plant belonging to the family Liliaceae. Revered across cultures and healing systems, it has been extensively described in Unani literature under various names such as Elwa, Musabbar, and Ghikwar. This review aims to comprehensively explore the medicinal utility of Sibr from an Unani perspective while integrating evidence from modern pharmacognosy, phytochemistry, and pharmacology. Traditionally, the dried juice …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 22–29 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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5G and up to 6G
Abstract: The 5th generation of mobile networks is called 5G, and the next generation, 6G is expected to arrive soon. With the promise of faster speeds, less latency, and increased connectivity, 5G technology has revolutionized mobile communications. However, the 6G vision is already taking shape as the need for high-performance networks keeps increasing. By offering ultra-high-speed communication, smooth artificial intelligence (AI) integration, extensive Internet of Things (IoT) connectivity, and support for …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 01–06 Read article
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Exploring Artificial Intelligence in the Finance Sector
Abstract: Artificial intelligence (AI), machine learning (ML), and progressive algorithms illustrate a substantial technological leap with wide applications across sectors like automobiles, healthcare, gaming, finance, entertainment, and more. The foremost objective of AI is to produce intelligent, independent systems capable of self-sustaining decision-making. This study delivers a concise summary of AI, concentrating on its transformative influence on finance, especially within banking, asset firms, derivatives markets, and insurance enterprises. It summarizes the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 16–23 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article