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1433 articles for “DEE”
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 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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Performance and Analysis of 6T, 8T & 10T SRAM Cell in 28nm Technology
Abstract: Technology scaling into deep sub-micron regimes has significantly increased the design challenges of Static Random Access Memory (SRAM), particularly at the 28 nm technology node. As transistor dimensions shrink, SRAM cells become more vulnerable to stability degradation, leakage current, process variations, and reduced noise margins, which adversely affect overall memory performance and reliability. The conventional 6T SRAM cell remains widely used due to its compact structure and high storage density; …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 12–18 Read article
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Nanotechnology-Based Cosmeceuticals for Anti-Aging and Skin Regeneration
Abstract: Nanotechnology has transformed the cosmetic industry of the cosmeceuticals by allowing the production of sophisticated delivery systems that improve the stability, penetration, bioavailability, and therapeutic efficacy of active ingredients in cosmetics. The present review identifies the value of nanotechnology-based cosmeceuticals in anti-aging and skin regeneration, with special focus on the recent developments in nanocarrier technologies and their use in dermatology. Many nanocarriers have exhibited great potentials in enhancing delivery of …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 2, 2026 · pp. 33–45 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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A Qualitative Comparative Study of Storytelling Through the Thematic Apperception Test Among Two Young Adults with a History of Substance Abuse in a Selected De-Addiction Centre in Delhi, India
Abstract: Introduction: Substance use can deeply affect an individual’s personality, relationships, and psychological functioning. The thematic apperception test (TAT), a projective psychological tool, helps uncover unconscious thoughts and emotions through storytelling. Objective: (i) To explore and compare the underlying personality dynamics of two young adult males with a history of substance use through TAT card analysis. Method: A qualitative comparative case study design was used. Ten standard TAT cards were presented …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 1–4 Read article
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Valorization of Shrimp Processing Waste by Green Methodology and its Application in Chitosan-PEG Composite Film
Abstract: Shrimp processing waste is mostly unidentified marine by product, presents considerable environmental pollution which also offers a rich but not fully exploited sources of biopolymers. The current work presents a sustainable method to convert shrimp processing waste into chitosan a biopolymer by green methodology. Isolation of chitin to chitosan from shrimp processing waste was carried through four green methodology steps i. Demineralization using citric acid ii. Deproteinization using papain iii. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1154–1162 Read article
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A Review of Modifications of Cement Slurry Formulations for Carbon Dioxide Storage
Abstract: Climate action, which includes activities aimed at mitigating climate change or reducing its adverse impacts, is the thirteenth goal of the 2030 SDGs (Sustainable Development Goals). Tthe successful commercial deployment of CCS technology would heavily rely on the integrity of the cement sheath used to complete the wellbores at the CO₂ storage sites. It has been established that the cement sheath made from conventional ordinary Portland cement (OPC) is not …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 1–21 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 · pp. 22–36 Read article
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Bridging Traditional Ayurvedic Pedagogy and Competency-Based Education: A Contemporary Perspective
Abstract: Mentoring plays a pivotal part in education. It has deep roots in both the traditional practitioner- Shishya Parampara of Ayurveda and ultramodern faculty- grounded medical education. The National Medical Commission and the National Commission for Indian System of Medicine have stated that structured mentorship programs are essential to guide scholars from newcomers to interpreters. This composition looks at how these traditions connect. It explains the purpose and limits of mentoring. …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 15, Issue 2, 2026 Read article
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TELEVISION MEDIA AND ROUTINE LIFE OF RURAL SOCIETY IN PUNJAB: A SOCIOLOGICAL INSIGHT
Abstract: The present study deals with the interface of the modern technologies especially the information and communication technologies that have greatly influenced the societies especially the rural society in Punjab. In this, we have delved deeper to understand the idea that how television has influenced the daily routine life of the rural people in Punjab and how under the influence of the content shown over the screen leads them to draw …
Published in Recent Trends in Social Studies · Vol. 3, Issue 2, 2026 · pp. 18–25 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence
Abstract: Plant health assessment is crucial for agricultural production and food security, as plant diseases significantly affect crop yields and quality. This paper reviews the applications of polymers and composite materials in the evaluation of plant health, focusing on both natural and artificial polymers, carbon materials, and polymeric–nanoparticle composite materials. Various types of sensing principles, such as colorimetry, fluorimetry, surface plasmon resonance (SPR), surface enhanced Raman scattering (SERS), and interferometry, are …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1135–1144 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Analyzing Thermal Expansion in Polymer Composites Through Heat Transfer Simulations
Abstract: Although lightweight and strong, polymer composites require careful handling in environments where temperatures shift. Their usefulness in fields like aviation, vehicle manufacturing, and electronic devices comes from customizable heat behavior alongside favorable mechanical traits. Yet variation in size due to heating or cooling remains a concern hard to dismiss. As conditions change, expansion occurs - sometimes enough to disrupt fit, alignment, or function within complex systems. This response to warmth …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1098–1108 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Managed Pressure Drilling for Improved Well Control: A Cross-Case Comparative Study (2015–2025)
Abstract: Managed Pressure Drilling (MPD) has matured over the past decade from a specialist technique applied to challenging wells into a mainstream drilling capability spanning ultra-HPHT exploration, deepwater development, unconventional tight-gas multi-well campaigns, and naturally fractured sour-gas reservoirs. Despite this maturation, the operational question of which MPD variant should be applied to a given well has been addressed in the literature case-by-case rather than through structured comparative synthesis. This paper presents …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 07–12 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 Read article