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674 articles for “pattern”
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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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An Overview on Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial intelligence techniques with core operating system services is ushering in a new class of platforms—Intelligent Operating Systems (Intelligent OS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Currents, Waves, and Whirls: An Academic Exploration of Fluid Mechanics
Abstract: Fluid mechanics investigates the behavior of liquids and gases in motion and at rest, revealing the principles that control natural occurrences and engineering systems alike. This article gives an easy review of essential concepts such as fluid characteristics, pressure, flow patterns, and the contrast between laminar and turbulent flow. It explores how fundamental rules, including conservation of mass and energy, impact the transport of fluids across varied settings. Through real-world …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 8–13 Read article
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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Digital Payments as a Driver of Sustainable Consumption: A Consumer-Based Study of Perceived Challenges and Opportunities in FinTech Ecosystems
Abstract: The Digital Payment Systems evolved remarkably fast, and so, have transformed the way in which the consumer makes purchases for products and services as well as the way in which they function economically, i.e., how they consume things. Beyond convenience and efficiency, digital payments are increasingly viewed as a potential driver of sustainable consumption by reducing cash dependency, improving transaction transparency, and supporting responsible spending practices. This study examines digital …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 1–12 Read article
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Impact of Mould Material on Microstructure and Mechanical Properties of Aluminium Castings: A Comparative Study with Aluminium Matrix Composites
Abstract: Casting has a wide industrial usage because it allows manufacturing complicated forms even at a comparatively low cost. Issues like transfer of heat through the interface of the mould and the metals, the rate of solidification, and the characteristics of the mould material have a powerful impact on the quality of cast products. This study measures the influence of various mould substances on the mechanical characteristics of aluminium castings. Sand, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 9–18 Read article
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Association Between Smartphone Addiction and Functional Exercise Capacity in College Students
Abstract: Smartphone addiction has become increasingly prevalent among college students and is associated with various negative physical and psychological outcomes. Functional exercise capacity, a key indicator of physical fitness and health, may be adversely affected by excessive smartphone use due to sedentary behavior and reduced physical activity. This article examines the association between smartphone addiction and functional exercise capacity in college students by analysing behavioral, psychological, physiological, and methodological perspectives. Evidence …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 4, Issue 1, 2026 Read article
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Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article
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Automating time based Household electricity Bill Calculations for Efficient Budgeting
Abstract: Recurrent household expenses must be precisely, in time, and openly tracked to make efficient household budgeting. Conventional monthly billing performance tends to delay the financial information, which results in the inefficient cash flow management and inability to modify short-term expenditure patterns. The proposed research is a system to automatize the calculation of household bills per week in order to deliver more frequent and practical insights into the household spending habits. …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 1–16 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Influence of Infill Density on Structural Performance of FDM-Processed PET-G Polymer: Experimental Validation through Quadcopter Flight Testing
Abstract: Polyethylene terephthalate glycol-modified (PET-G) is an amorphous thermoplastic copolymer increasingly adopted in structural applications through fused deposition modeling (FDM). However, the correlation between FDM processing parameters, especially infill density, and mechanical performance of PET-G parts remains inadequately characterized under real-life loading conditions. This study investigates how infill density (10% and 30%, grid pattern) influences the structural integrity of FDM-processed PET-G components, validated experimentally through quadcopter airframe fabrication and flight testing. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 644–656 Read article
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Myco-Engineering Systems: Harnessing Fungal Networks for Carbon Sequestration and Sustainable Ecosystem Restoration
Abstract: Fungal organisms play a foundational role in global ecosystem stability, particularly through their contributions to nutrient cycling, soil regeneration, and carbon sequestration. Recent scientific advances have highlighted the potential of fungal mycelial networks as natural bioengineered systems capable of supporting sustainable environmental restoration. This paper introduces the concept of Myco-Engineering Systems, an interdisciplinary framework that integrates fungal biology, environmental science, and artificial intelligence (AI) to enhance carbon capture and ecosystem …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article
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Consumer Misuse of Cosmeceuticals and Its Role in Adverse Skin Reactions
Abstract: Cosmeceuticals represent a rapidly expanding category of products positioned between cosmetics and pharmaceuticals, offering both aesthetic and therapeutic benefits. However, their widespread availability, aggressive marketing, and perception as inherently safe have contributed to increasing instances of consumer misuse. Misuse includes over-application, inappropriate combinations, prolonged unsupervised use, and use of high-potency active ingredients without dermatological guidance. Such practices have been strongly associated with a broad spectrum of adverse cutaneous reactions ranging …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 2, 2026 · pp. 1–16 Read article
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Genomic Characterization of Emerging Arboviruses in Rural India
Abstract: Arboviruses (arthropod-borne viruses) represent a rapidly evolving group of pathogens responsible for significant morbidity and mortality, particularly in tropical and subtropical regions. Rural India, characterized by dense vector populations, changing ecological patterns, and limited healthcare infrastructure, has become a hotspot for the emergence and re-emergence of arboviral diseases such as dengue, chikungunya, Japanese encephalitis, and more recently, Zika virus infections. Advances in genomic technologies, including next-generation sequencing (NGS), metagenomics, and …
Published in International Journal of Pathogens · Vol. 3, Issue 2, 2026 · pp. 1–8 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 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
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article