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845 articles for “base frame”
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Traffic Sign Detection and Recognition Using Deep learning based- Convolutional Neural Network Algorithm
Abstract: The concept of Deep Convolutional Neural Organizations (CNNs) is a quickly arising new zone for Automatic traffic sign detection and recognition among the few master frameworks, such as independent driving and driver assistance. Here, in this paper, for traffic sign detection, we have utilized another methodology that uses a newly developed identification calculation and an RGB-based tone thresholding procedure. Results of the proposed identification and acknowledgement approaches are assessed on …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 1, 2021 · pp. 24–29 Read article
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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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Performance Evaluation of 5G transmission system and Simulation Modeling
Abstract: Orthogonal multiple access (OFDMA) is a very important technology for the fifth generation (5G) wireless communication networks to provide the need of the flexible demands of users on lower latency rate, high level of reliability, good amount of connectivity, large fairness, and high data throughput. The key idea behind MIMO based 5G networks are to provide multiple users in common resource block. The MIMO OFDM principle is the main framework …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 21–32 Read article
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Evaluating the Role of Integrated Digital Tools in Enhancing Workforce Productivity in SMEs: A Case Study of the WorkWiz Management System
Abstract: This article investigates the potential impact of integrated digital management tools on workforce productivity in Small and Medium Enterprises (SMEs). While digital transformation is widely recognized as a key driver of productivity, SMEs face unique implementation challenges including resource constraints, workforce technical capabilities, and cultural adaptation. We examine how unified digital tools could affect individual and organizational productivity across attendance management, inventory control, communication, and administrative functions through a simulation …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 16–27 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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Paper Battery for Portable Electronics: A Review
Abstract: This paper depicts about paper battery. A paper battery is an adaptable, ultrathin vitality stockpiling and generation gadget framed by consolidating Carbon Nanotubes with a customary sheet of cellulose based paper. A paper battery can work both as a high vitality battery and super capacitor. The battery produces power similarly as the traditional lithium-particle batteries however every one of the segments has been consolidated into a light weight adaptable sheet …
Published in Journal of Power Electronics and Power Systems · Vol. 7, Issue 2, 2017 · pp. 28–32 Read article
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Developing a Model in Matlab/Simulink Environment for Induction Motor Considering Core Loss and Stray Load Loss
Abstract: This paper focuses on a Matlab/Simulink model of a squirrel-cage induction motor with consideration of core loss and stray load loss. This model is based on some mathematical expressions and also described through an equivalent circuit including core loss and stray load loss. The model of induction motor has been developed based on the state space equations in a synchronously rotating reference frame, where core loss and stray load losses …
Published in Trends in Electrical Engineering · Vol. 4, Issue 2, 2014 · pp. 1–12 Read article
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PV-Syst based Performance Forecasting of Grid Connected Solar PV System in Indian Scenario
Abstract: The presentation and economy of a solar photovoltaic framework relies upon area and geographic parameters. Anticipating energy productivity is significant for effective arranging and assessment rates. The proposed examination investigates the exhibition assessment of three interconnected geologically associated photovoltaic solar frameworks. In Jaipur, Kolkata and Chennai have been trying a 1 MW solar PV framework for a year. Recreations were performed utilizing PV Syst (a product device created by the …
Published in Trends in Electrical Engineering · Vol. 10, Issue 2, 2020 · pp. 33–39 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Machine Learning–Assisted Design of High-Performance Biomedical Polymer Composites
Abstract: The high-performance biomedical polymer composite design needs to represent a trade-off between the strength, biocompatibility, and degradation that cannot be accomplished using conventional design methods. The study aims to develop a predictive and optimization framework of composite properties with the help of machine learning. The methods include ANN, SVM, Random Forest, and Gradient Boosting with experiment and simulation data. The results of Gradient Boosting show that the accuracy is 95.9 …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Representation-Theoretic Symmetry Reduction and Fuzzy-Grey Optimization of Modular Vibration Systems
Abstract: This paper presents a representation-theoretic framework for symmetry-aware vibration control in modular structural systems. Exploiting cyclic symmetry, the mass, damping, and stiffness operators are block-diagonalised into irreducible representations, reducing the full structural dynamics to a collection of lower-dimensional modal subsystems. This decomposition provides both computational efficiency and a rigorous mathematical description of symmetry-preserving dynamic behaviour. To account for imperfections arising in practical implementations, near-symmetry defects in stiffness and damping are …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 22–30 Read article
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Immune Dysregulation and Cytokine Circuitry in Genital Endometriosis: Mechanistic Insights and Next-Generation Immunotherapeutic Strategies
Abstract: Genital endometriosis is increasingly recognized as an immune-mediated inflammatory disorder driven by complex interactions between dysregulated immune cells, cytokine hubs, and microbiome-derived modulators. This review introduces a novel “immune–cytokine circuitry” framework that unifies innate and adaptive immune abnormalities with key cytokine loops sustaining chronic inflammation, angiogenesis, neuroinflammation, and immune tolerance. Within this circuitry, macrophage polarization, dendritic cell immaturity, NK-cell anergy, Treg expansion, Th17 amplification, and B-cell–mediated autoimmunity converge to establish …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 06–16 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Fault Detection Attainment for Embedded Cores based on Software Test Routines
Abstract: The test circuitry is designed in built-in-self-test (BIST) technique involves a system that applies the test signals and observes the corresponding system response. In this technique, the framework is embedded directly into the system hardware. The testing process performs efficiently, fastly and more economically than using an external test setup. Self-testing of embedded processors based on the test routines is an emerging method, since it employs a test resource partitioning …
Published in Journal of VLSI Design Tools and Technology · Vol. 8, Issue 1, 2018 · pp. 1–6 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article
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Application of MCDM Techniques for Selection of Battery for Electric Vehicle
Abstract: An electric vehicle (EV) operates using an electric motor, which differs from traditional vehicles powered by internal combustion enginesElectric motors are used to power EVs rather than gasoline and gasses. These motors are powered by fuel cells, solar panels, or battery packs that recharge. As a result, EVs are increasingly considered as potential replacements for conventional automobiles, aiming to combat issues such as pollution, global warming, and resource depletion. Electric …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 33–40 Read article
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Shell Programming with Sensor Systems and Applications for Human Cognition
Abstract: Shell programming provides a flexible interface to sensor systems, enabling robust scripting for real-time data acquisition and processing, as well as integration with perception components. Such sensors have human analogs—tactile, physiological, and behavioral—and are increasingly embedded within health, mobile, and smart environments to capture fine-grained details of human cognition. Using shell scripts, the system can automatically collect sensor data, fuse multimodal data, and perform adaptive behavioral monitoring, allowing researchers and …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 41–45 Read article
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**Innovation and Quality Assurance in School Management: A Research Study on Indian Schools in the Context of NEP 2020**
Abstract: The quality of school education is strongly influenced by the efficiency and vision of school management practices. In today’s rapidly changing educational landscape, schools are expected to perform responsibilities that extend beyond routine administration. They must ensure academic excellence, learner well-being, value- based education, inclusion, transparency, and accountability to parents and society. However, many schools still function through traditional management patterns that focus mainly on record-keeping, examination routines, and compliance …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 · pp. 29–36 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