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1595 articles for “individual”
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Smart and adaptive cutting-edge IoT based implementation for remote environments
Abstract: In remote, mountainous, or snow-covered regions, mobile networks and GPS signals usually become unreliable, which creates major challenges for search and rescue (SAR) operations. To overcome the issue, this paper presents a compact, low-power, voice-activated wearable device that integrates LoRa communication with a TinyML-based keyword detection system. The proposed device enables individuals to send signals in areas where GPS coverage is unavailable. Using the Received Signal Strength Indicator (RSSI), the …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 1–7 Read article
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Impact Of Nurse-Led Pain Management Protocol On Postoperative Recovery Outcome
Abstract: Postoperative pain remains a critical determinant of recovery outcomes, influencing patient satisfaction, complication rates, and overall healthcare utilization. Nurse-led pain management protocols have emerged as an evidence-based strategy to enhance postoperative care through continuous assessment, individualized interventions, and multidisciplinary collaboration. This article explores the impact of nurse-led pain management on postoperative recovery outcomes, including pain reduction, early mobilization, decreased hospital stay, and improved patient satisfaction. Evidence from recent studies demonstrates …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 2, 2026 Read article
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Uncontrolled Cell Growth and Human Health: A Comprehensive Exploration of Cancer
Abstract: Cancer is a diverse category of diseases defined by the uncontrolled proliferation and spread of aberrant cells. It remains the major cause of morbidity and mortality worldwide. This article presents an overview of the various forms of cancer, such as carcinomas, sarcomas, lymphomas, and leukaemia, emphasising their distinct causes, symptoms, and risks. Early detection and diagnosis are emphasized as key to enhancing treatment outcomes. The article further provides an in-depth …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 1–23 Read article
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Leveraging Arduino Nano for Developing a User-Friendly and Automated Medicine Dispensing System
Abstract: The goal of the "MED BUDDY" project is to address the urgent need for medication management, particularly for elderly individuals, those with chronic illnesses, and those who must adhere to a rigorous medication schedule. An Arduino Nano microcontroller powers the automated medication dispenser known as the MED BUDDY system. By dispensing the appropriate dosage of medication at the appropriate time, it lowers the possibility that users will forget or take …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 37–46 Read article
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A Comparative Study of the Optimum Health and Health-Related Physical Fitness Level of State Level Players Boys and Girls at MBSPSU, Patiala
Abstract: The study’s goal was to compare state-level player girls’ and boys’ optimal health and health-related physical fitness. Thirty individuals, including male and female state-level players from the Patiala district of Punjab, India, were chosen via purposeful random sampling. There were two distinct groups formed: There were fifteen participants in each group (15 females and 15 boys), with Group 1 being made up of girls and Group 2 being made up …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 22–27 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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Forecasting Climate-Driven Healthcare Demand in Agricultural Regions: A Multi-Modal AI Approach
Abstract: The rapidly increasing instability of world climatic regimes has made past meteorological thresholds irrelevant, especially in the agricultural areas where monetary stability and well-being of humans are closely intertwined with an environmental situation. The more the frequency of 1 in every 1000-year events, i.e., heatwaves and catastrophic flooding increase, the greater the rural healthcare systems are in crisis, i.e., unable to predict a surge in demand because of data scarcity, …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 28–38 Read article
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PREDICTIVE LEARNING POWERED BY AI AND SOPHISTICATED STUDENT ENGAGEMENT TECHNIQUES
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
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Vitamin D Mitigates Inflammation and Downregulates Importin α3 in Non-Alcoholic Fatty Liver Disease (NAFLD)
Abstract: Background: Pro-inflammatory cytokines, such as TNF-α, IL-1β, IL-6, and IL-8, seem to play a crucial role in the progression of NAFLD as they activate the transcription factor NF-кB. The activated NF-кBp50/RelA subunits are translocated to the nucleus by Importin α3 and Importin α4. Numerous studies have indicated a negative association between NAFLD and vitamin D levels. Low vitamin D levels have been correlated with histological severity, necro-inflammation, and fibrosis in …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 1–16 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Photonic Diagnostics: Harnessing Optical Sensing for Non-Invasive Assessment of Coronary Obstruction
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with coronary artery blockages primarily atherosclerosis representing a critical challenge. The gold standard for diagnosing coronary artery disease remains invasive coronary angiography, a procedure that, while precise, carries inherent patient risks, high costs, and logistical burdens. Optical sensors, leveraging the principles of light-tissue interaction, offer real-time, high-resolution insights into vascular health, paving the way for early detection of arterial stenoses …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 25–30 Read article
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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Low-Fat and Lactose-Free Dairy Products: Trends and Challenges
Abstract: Dairy products play a vital role in human nutrition, providing essential nutrients such as proteins, calcium, vitamins, and fats. However, increasing health concerns related to obesity, cardiovascular diseases, and lactose intolerance have significantly influenced consumer preferences worldwide. As a result, the demand for low-fat and lactose-free dairy products has grown rapidly in recent years, driven by the need for healthier and more digestible alternatives. Low-fat dairy products are developed by …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–29 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Ayurvedic Management of Vātadhika Vātarakta – A Case Series
Abstract: Vātarakta is a classical disorder described in Ayurveda that arises due to the simultaneous vitiation of Vāta and Rakta, resulting in a pathological condition characterized by mutual obstruction (Āvaraṇa) between these two factors. This complex interaction between Vāta and Rakta leads to a wide spectrum of clinical manifestations, making the condition challenging to diagnose and manage effectively. Among the four types of Vātarakta described in classical texts, Vātādhika Vātarakta predominantly …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Polymer-Mediated Electron Transfer in Eco-Friendly P3HT–rGO Nanocomposites for Optoelectronic Applications
Abstract: Conducting polymer–graphene hybrid nanocomposites have emerged as promising materials for next-generation optoelectronic applications owing to their solution processability, tunable interfacial properties, and mechanical flexibility. Recent studies have highlighted the importance of graphene–polymer hybrid systems in enhancing charge transport pathways, exciton dissociation efficiency, and interfacial stability in organic optoelectronic devices. Despite these advantages, a key challenge remains the efficient production of individual graphene sheets through the reduction of graphene oxide using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 413–423 Read article
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Circadian Regulation of Lipid Peroxidation in the Brain: Linking Ferroptosis to Neurodegenerative Vulnerability
Abstract: The human brain operates through highly coordinated physiological and biochemical processes that regulate cognition, behavior, and neural adaptability. Central to these processes are mechanisms governing brain function, neurophysiology, and neuroplasticity, which are increasingly recognized to be influenced by circadian rhythms. Recent advances in cognitive neuroscience, neuroimaging, and behavioral neuroscience have revealed that disruptions in circadian regulation can significantly impact oxidative balance within the brain, particularly through enhanced lipid peroxidation. Lipid …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 1–14 Read article
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Gold Nanoparticle Size, Biodistribution, and Toxicity: Insights from DualEnergy CT
Abstract: Dual-energy and spectral computed tomography (CT) have emerged as powerful platforms for noninvasive, quantitative mapping of nanoparticle biodistribution in vivo. By exploiting the energy-dependent attenuation profiles of high-atomic-number (high-Z) materials, these systems enable material decomposition and element-specific imaging, thereby distinguishing nanoparticle signals from those of soft tissues and conventional iodinated contrast agents. Photon-counting spectral CT further enhances this capability by binning individual photons into multiple energy channels, improving spatial resolution, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 · pp. 22–34 Read article
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Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article