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147 articles for “Convergence”
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IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 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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Smart Ways to Manage Waste with AI and IOT: A Review
Abstract: Rapid urban growth and population have led to exponential growth in municipal solid waste over traditional inefficient waste management systems (collection / segregation / disposal). This paper reviews the convergence of Internet-of- Things (IoT) and artificial intelligence (AI), seen as two potential smart techniques to launch smarter waste management. The research reports important applications for AI and IoT in waste classification, waste collection optimization, waste-to-energy as well as smart bin …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 26–31 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Epigenetic Modifications in Health, Disease, and Precision Therapeutics (From Genome to Epigenome)
Abstract: Introduction: Epigenetic alterations play a crucial role in regulating gene expression in both normal physiological and disease states. These reversible modifications—such as DNA methylation, histone acetylation, phosphorylation, ubiquitination, and chromatin remodelling—are increasingly implicated in complex diseases including cancer and neurodegenerative disorders. Despite advances in standard therapeutic approaches, patient responses remain variable, largely due to genetic heterogeneity and epigenetic dysregulation. This highlights the need for incorporating epigenetic understanding into personalized medicine. …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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An Overview on MOSFET based Sensor Design
Abstract: In the past two decades the MOSFET has transformed from a simple switch in digital logic to an analog powerhouse that can be cofabricated with the sensing material on a single chip. MetalOxideSemiconductor FieldEffect Transistors (MOSFETs) have silently become the beating heart of modern sensor platforms, translating the faint whispers of physical, chemical, and biological phenomena into robust electrical signatures. This abstract surveys the latest advances that have turned the …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 20–26 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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LQR-Based Optimal Control of Inverted Pendulum System with State Estimation and Stability Analysis
Abstract: The inverted pendulum on a cart is a canonical benchmark problem in control systems engineering, capturing the essential challenges of stabilizing an inherently unstable, underactuated, and nonlinear plant. Classical Proportional-Integral-Derivative (PID) controllers, while widely employed in industrial practice, exhibit fundamental performance limitations when applied to such systems, primarily due to their inability to account for multivariable coupling, process noise, and the absence of a systematic optimization framework. This paper presents …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 31–43 Read article
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Biophilic Design as a Bridge Between Applied Vastu and Contemporary Interior Design Practice in Urban Indian Residences
Abstract: The growing disconnect between urban Indian residents and the natural environment has prompted renewed interest in design strategies that restore human–nature connections within indoor spaces. This paper investigates the conceptual and practical convergence between biophilic design—a framework grounded in the innate human affinity for nature—and Vastu, the ancient Indian architectural science that prescribes spatial harmony through alignment with natural forces. Drawing on a qualitative review of existing literature, established biophilic …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 52–61 Read article
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Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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Nano-Chemical Revolution in Vaccinology: A Study
Abstract: The development of traditional vaccines, reliant on attenuated pathogens or purified proteins, has historically been limited by slow development timelines, poor stability, and low immunogenicity requiring potent, often non-specific, adjuvants. This synthesis argues that the convergence of nano-material science and meticulous chemical engineering represents the next major paradigm shift in preventative medicine. Nano-materials, particularly Lipid Nanoparticles (LNPs) and various polymeric or inorganic scaffolds, have transitioned from theoretical constructs to essential …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 1, 2026 Read article
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Neural Implants & Brain–Computer Interfaces: Enhancing Human Intelligence or Violating Free Will?
Abstract: The integration of neural implants with artificial intelligence creates opportunities to develop new implants and enhance current nanotechnologies. Although these advances hold significant potential for restoring neurological functions, they also introduce important ethical concerns. The rapid advancements in neural implants and brain–computer interfaces [BCIs] are revolutionizing human cognition, enabling enhanced intelligence, communication, and even thought-driven control of external devices. Although these technologies offer great promise in enhancing human abilities, they …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 13–18 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Technology with a Human Face: Reimagining Progress through Universal Ethical Principles
Abstract: Technological progression is mostly considered as a tool of human evolution. In this digital era, however, quick novelty has revealed complex ethical gaps in the modelling and implement of technology. Technologies namely artificial intelligence, algorithmic systems, and digital surveillance progressively effect social life, economic activity, and political decision-making. While these technologies provide proficiency and progress, they also advance moral concerns connected to discretion, disparity, liability, and human dignity. The technique …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 30–36 Read article