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89 articles for “Bio-detection applications”
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The Future is Smelling: Exploring the Potential of e-Nose
Abstract: The human sense of smell, a complex and often underestimated faculty, allows us to perceive the world through volatile organic compounds (VOCs). This ability to detect and differentiate between aromas, flavors, and even potential hazards has inspired the development of the electronic nose, or e-nose. More than just a novelty, e-noses are rapidly becoming sophisticated analytical tools with applications that span across numerous industries. By mimicking the biological processes of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 15–25 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 Read article
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Advancement and Limitations of Raman Spectroscopy: A Review
Abstract: The present review provided an overview of advances and limitations in Raman spectroscopy— a powerful analytical tool widely used across scientific disciplines. Instrumental advances, including the development of lasers, detectors, and optics, have increased the scope of Raman spectroscopy. These advances have expanded its applications in fields such as information science and biology. The integration of Raman spectroscopy with additional technologies such as microscopy and artificial intelligence further expands analytical …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 85–97 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Role of Solid-State Materials in Development of devices for Internet of Medical Things
Abstract: The Internet of Medical Things (IoMT) represents a transformative paradigm in healthcare delivery, integrating connected medical devices, sensors, and wearable technologies to enable real-time patient monitoring and personalized treatment. Solid-state materials form the foundational infrastructure of IoMT systems, encompassing semiconductors, energy storage materials, sensing materials, and flexible electronics. This article explores the critical role of advanced solid-state materials in enabling miniaturization, energy efficiency, biocompatibility, and enhanced sensing capabilities essential for …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 11–18 Read article
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Nanotechnology in Context of Environment and Industrial Development: A Review
Abstract: Climate change and sustainable development with context to environment has been one of the main concerns and challenges of 21st century. Industrialization and development go hand in hand, so we need to devise green synthetic routes so that our environment stays protected. In the past two decades, there has been significant advancement in the field of nanotechnology. Many cost-effective methods have been devised for large-scale production. Significant improvements have been …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Advanced Fiber-Reinforced Polymer Composites: Processing, Nano-Modified Adhesive Technologies, Interfacial Engineering, Durability, and Structural Applications—A Comprehensive Review
Abstract: Fiber reinforced polymer (FRP) composites are considered to be one of the most universal categories of advanced engineering materials owing to their unique properties such as outstanding strength-to-weight ratio, corrosion resistance, fatigue durability, and wide opportunities for design. Innovations in the fields of fiber reinforcement, polymer matrix system, composite manufacturing technologies, and nano-modified adhesives technology have greatly extended the range of applications of this type of materials in aerospace, automotive, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 980–990 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Remote Monitoring Sensor Systems and Applications in Health Informatics: Fostering Shell Programming
Abstract: The fascination of sensor systems has been promising for health informatics as their direct initiative for real-time information by observing its accuracy that was required at the time for data collection, monitoring and analysis to improve patient well-being and health system administering. By integrating these systems with wearable devices, biomedical sensors, and other IoT-enabled technologies, patients can experience continuous health tracking, early disease detection, and remote patient monitoring. For example, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 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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Recent Advancements and Comprehensive Review on Hyphenated Techniques
Abstract: Hyphenated techniques represent a powerful class of analytical methods that combine two or more established techniques – typically a separation method with a spectroscopic detection technique – to achieve enhanced analytical performance. First introduced by Hirschfeld in 1980, the term “hyphenation” refers to the online coupling of such methods, enabling more precise, sensitive, and comprehensive analysis of complex samples. These techniques exploit the strengths of individual methods while overcoming their …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 37–50 Read article
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Smart Attendance System Using Face Recognition with OpenCV
Abstract: In the past, the conventional method of recording student attendance relied heavily on teachers manually marking entries in a physical register. While simple, this approach is not only time-consuming but also highly vulnerable to errors such as accidental omissions, incorrect entries, or even malpractice in the form of proxy attendance. Moreover, traditional registers lack real-time accessibility, making it difficult to analyze or monitor data instantly. To address these limitations, modern …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 30–39 Read article
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AI-Enhanced Interpretation of Cardiac Troponins: Toward Predictive Precision in Myocardial Injury
Abstract: Background: Cardiac troponins (cTn) represent the gold standard biomarkers for myocardial injury detection, yet their interpretation remains challenging due to various confounding factors and clinical contexts. Artificial intelligence (AI) technologies provide remarkable possibilities to improve the interpretation of troponin levels by utilizing pattern recognition, predictive modeling, and clinical decision-making support. Objective: This review examines the current state and future potential of AI-enhanced cardiac troponin interpretation, focusing on machine learning applications, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–9 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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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article