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1946 articles for “Friday AI-2.0” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 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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AI and Human Intelligence: Exploring Impacts on Human Activities
Abstract: Artificial intelligence (AI) has become the important force that is shaping human activities across different domains. This article delves into the complex relationship between AI and human intelligence, scrutinizing its interplay, and also examining the consequential impacts on diversified human activities. Through the extensive literature review, this paper also investigates the current landscape of AI technologies and their implications, which showcases the multifaceted roles AI plays in augmenting, challenging, and …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 45–49 Read article
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Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials
Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Implementation of Energy-efficient Axial Fans for Air Handling Unit Using AI Model
Abstract: This research explores the integration of energy-efficient axial fans in Air Handling Units (AHUs) within a large automotive manufacturing facility to enhance HVAC (heating, ventilation, and air conditioning) performance and reduce energy consumption. Standard AHUs in the facility’s clean rooms and other spaces utilize traditional blower fans, which primarily rely on static pressure, limiting their efficiency. By replacing these with electronically commutated (EC) axial flow fans, which leverage both static …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 3, 2024 · pp. 28–34 Read article
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Ramifications of Artificial Intelligence and Cyber Security
Abstract: Artificial intelligence (AI) has pros and cons for cyber security: AI can improve network security, anti-malware, and fraud detection. AI can simulate cyberattacks, automate responses, and analyse enormous databases. AI-powered phishing and deepfakes are cyber risks. AI can potentially be attacked and become a liability for corporations. AI has transformed cyber security, bringing both new opportunities and challenges. AI-powered tools discover abnormalities faster, automate threat responses, and improve threat detection …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 40–45 Read article
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Role of Generative AI for Advanced Shell Language Design
Abstract: This study explores the emerging field of applying Artificial Intelligence (AI), specifically generative AI, to enhance shell scripting, a crucial skill for system administration and automation. While the formal design of entirely new shell languages using AI remains a long-term prospect, the current focus is on augmenting how existing shell languages are used for improving the scripting experience. This involves leveraging AI for tasks like automated script generation, intelligent code …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 22–27 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Understanding Airborne Pathogens: Pathways, Risks, and Control Strategies
Abstract: Airborne transmission is the transfer of germs through the air, mostly by respiratory droplets and aerosols that come out when you cough, sneeze, talk, or breathe. These particles can stay in the air for a long time and move a long way, especially in small or poorly ventilated places. Mycobacterium tuberculosis, measles virus, varicella-zoster virus (chickenpox), influenza virus, and more recently, SARS-CoV-2 are all infections that can be spread through …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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AI-Enabled Recycling of Thermoplastic Polymer Waste in Hospitals: A Circular Economy Pathway Toward Green Hospital Certification
Abstract: This review research explores the latest role of AI in improving thermoplastic waste management for hospitals in terms of segregation accuracy, operational efficiency, and circular economy outcomes. Seventy-five relevant studies were analysed, and it was reported that AI-based systems, especially CNNs, YOLO models, and sensor-fusion approaches, achieved high accuracy in the identification and sorting of medical plastics, often above 90%. Early evidence also reveals improvements in the reduction of contaminants, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 170–182 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Asymmetrical Light Propagation in 2D Photonic Crystal Structure
Abstract: In this work, using Plane Wave Expansion (PWE) and two-dimensional Finite Difference Time Domain (2D-FDTD) methods, we design a structure that shows the high asymmetry in propagation of light. Structure is based on two-dimensional Photonic Crystal (2D-PC) consisting of square lattice (39 X 39) of infinitely long circular rods of refractive index 2.9 in the background of refractive index 1. Radius of rods is 0.15a, where a is the lattice …
Published in Journal of Polymer & Composites · Vol. 11, Issue 7, 2023 · pp. 69–74 Read article
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Innovations in Civil Engineering: Advancing Infrastructure through AI Technology
Abstract: A comprehensive exploration of the intersection of civil engineering and artificial intelligence (AI) technology, highlighting the transformative impact of AI on infrastructure development, management, and sustainability. The journal encompasses a wide array of research articles, case studies, and reviews that demonstrate the integration of AI into various facets of civil engineering, including but not limited to smart infrastructure, predictive maintenance, structural analysis, and urban planning. By showcasing cutting-edge applications and …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations
Abstract: Dynamic and unpredictable characteristics of environmental processes create challenges in their management and regulation. Artificial intelligence (AI) offers a powerful solution for addressing these complexities.AI tools have become more and more popular across a range of fields and research domains due to their efficient development and rapid growth. We analyse key trends in AI applications, including predictive analytics for climate modelling, automated monitoring of biodiversity, and smart resource management. The …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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AI-Driven Exam Evaluation Systems: Challenges, Innovations, and Future Directions
Abstract: A proposed AI system is used to grade exams automatically. It addresses inefficiencies in human assessment. A GPT model trained on graded replies is used for evaluation, and TrOCR is used for precise handwritten text recognition. Efficiency and less bias are provided by this method, although there are still issues. More work is needed to assess open-ended questions and make sure they are understandable. To automate many aspects of exam …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 7–13 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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AI-Based Sentiment Analysis of Public Perception Under Bangabandhu Sheikh Mujibur Rahman
Abstract: Sheikh Mujibur Rahman, known as Bangabandhu, played a pivotal role in Bangladesh’s post-liberation period (1971–1975). Understanding public sentiment during his leadership is crucial for historical analysis. This study employs Artificial Intelligence (AI)-based Sentiment Analysis to examine public perception through archived newspapers, parliamentary speeches, and historical records. Using Natural Language Processing (NLP) techniques, including sentiment classification and opinion mining, we analyze textual data to assess the prevailing public mood during his …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 21–29 Read article