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194 articles for “conventional frame”
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Holographic Beam Switching and Intelligent Routing for Terahertz Space-Air-Ground Integrated Networks
Abstract: The rapid evolution of sixth-generation (6G) and beyond communication technologies necessitates highly adaptive, ultra-high-capacity, and low-latency networking frameworks capable of supporting global connectivity across terrestrial and non-terrestrial domains. This study proposes a novel holographic beam switching and intelligent routing framework for terahertz (THz) Space-Air-Ground Integrated Networks (SAGINs). The proposed architecture leverages holographic beamforming techniques to dynamically manipulate electromagnetic wavefronts, enabling precise beam steering, reduced interference, and enhanced spectral efficiency in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Performance Improvement of Standalone Solar PV Pumping System Using Supercapacitor
Abstract: Two of the most pressing issues when it comes to rural communities of arid and semi-arid regions are water shortage and unstable grid electricity. Standalone solar photovoltaic (PV) pumping systems have been introduced as a clean, low maintenance alternative to diesel powered pumps, but their performance is limited by intermittent nature of sunlight and limited energy buffering capacity of conventional batteries. The paper is an investigation into the incorporation of …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT
Abstract: The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 18–31 Read article
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Polymer Chemistry in Shoulder Orthotics
Abstract: The design of effective shoulder orthotic devices has increasingly made use of polymeric materials because of their versatility, durability, and biocompatibility. This review illustrates polymer chemistry role in constructing an orthotic device for shoulder subluxation, which is a commonly occurring post stroke or injury condition. Proprietary design elements such as polypropylene are rigid yet moldable which help in anatomical formulating for joint stabilization. On the other hand, rubber elastomers, medicinal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 21–28 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 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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Analysis of Friction Stir Welding Utilizing ANSYS: A Study Based on Simulation
Abstract: Friction Stir Welding (FSW) represents a sophisticated solid-state welding methodology that has attracted considerable scholarly attention due to its efficacy in amalgamating high-strength, lightweight substrates including aluminium, magnesium, and titanium alloys. FSW enables the fabrication of defect free products with a substantial amount of mechanical and wear properties. The process is highly sensitive to various parameters that significantly influence the quality and strength of the final product. Studies have shown …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 62–77 Read article
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Thermodynamic Optimization and Exergy-Based Performance Analysis of Hybrid Thermal Management Systems for Electric Vehicles
Abstract: The transition toward sustainable transportation has brought electric vehicles (EVs) to the forefront of modern engineering innovation. Despite their environmental benefits and improved energy efficiency, EVs face major thermal challenges that affect performance, safety, and durability. Efficient thermal management of batteries, power electronics, and electric drive systems is vital to ensure reliability under diverse operating conditions. This study presents a detailed thermodynamic optimization and exergy-based performance analysis of hybrid thermal …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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Lysogenic Phage Cocktails with Embedded Fluorophores for Field Wound Diagnostics.
Abstract: Rapid and accurate detection of wound infections in field settings remains a critical challenge in emergency and military medicine. Conventional microbiological diagnostics are time- consuming and laboratory-dependent. Bacteriophages, particularly lysogenic phages, offer high specificity toward bacterial hosts and can be engineered as diagnostic tools. A translational framework was developed for lysogenic bacteriophage cocktails embedded with fluorophore reporters for rapid, point-of-care wound diagnostics. Mechanisms of phage infection, lysogenic integration, and fluorophore …
Published in International Journal of Virus Studies · Vol. 3, Issue 2, 2026 Read article
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Structure-Property Correlation in PTT/PP Blends with Improved Mechanical Performance
Abstract: The present work investigates a series of poly (trimethylene terephthalate) (PTT)/polypropylene (PP) blends prepared with varying PP concentrations in order to improve the overall performance of PTT, particularly with respect to mechanical properties and processability. PTT is a promising engineering thermoplastic owing to its balanced stiffness, resilience, and chemical resistance; however, its relatively high cost and processing limitations often restrict its wider application. In this context, blending with PP offers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 90–98 Read article
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Integrative Therapeutics for Antimicrobial Resistance and Autoimmune Disease: Evidence and Pathways
Abstract: Background: Antimicrobial resistance (AMR) is accelerating globally, while autoimmune diseases and adverse drug reactions (ADRs) continue to rise. Ayurveda offers immunomodulatory, antimicrobial, and detoxification‑oriented interventions that may complement biomedical strategies. Objective: To propose a hypothesis‑driven integrative model combining Ayurvedic phytotherapy, panchakarma detoxification, and personalized dosha‑based care with evidence‑based medical management to mitigate AMR emergence, modulate autoimmunity, and reduce ADR incidence. Methods: A synthesis of mechanistic literature on Ayurvedic herbs with …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 · pp. 25–30 Read article
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Simulation and Analysis of Battery Pack Using the Multi Scale Multi-Domain Battery Model
Abstract: The creation of sophisticated simulation models has been made necessary by the need for reliable and effective battery packs in energy storage systems and electric vehicles. This study focuses on the simulation and analysis of battery packs using a multi-scale multi-domain battery model. The model enables a thorough knowledge of battery pack behavior across a range of operating situations by integrating the electricity, thermal, and mechanical domains. Multi-scale modeling bridges …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 31–46 Read article
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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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The Role of Mathematical Reasoning in Legal Analysis: Bridging Two Disciplines
Abstract: This research paper explores the integration of mathematical reasoning into legal analysis, emphasizing the inherent similarities between the two disciplines. Both fields rely on logical structures, such as deductive reasoning, inductive reasoning, and other formal methods of thought. By examining these parallels, the paper reveals the nascent but growing interaction between mathematics and law, uncovering how the organizational schemes that underpin mathematical principles can enhance legal argumentation, decision-making, and analysis. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article