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321 articles for “Scaling Model”
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Efficient Fault Detection in Power Transmission: A Review of Three-Phase Line Fault Detection with Hybrid Energy using MATLAB
Abstract: In urban regions, the density of power demand has significantly increased recently. Large-scale subterranean power cable installations are beginning to take the place of overhead transmission lines everywhere in the world because of environmental concerns in highly populated areas. The present project's primary objective is to use MATLAB to create a simulation model that includes 3ph symmetrical and unsymmetrical defects. Some have proven to be effective in detecting errors while …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 42–47 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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An empirical investigation using artificial neural networks to evaluate the manageability of object-oriented systems
Abstract: Software can be called quality software if it produces consistent outputs over multiple time of testing. There can be very much difficulties to modify and maintain the software with poor maintainability. For assessing the characteristics of object-oriented software, such as scale, inheritance, integrity, and coupling, numerous object-oriented metrics have been recommended. In this study, we explore object-oriented variables that have the potential to be significant antecedents of software maintenance. In …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 50–58 Read article
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Spectral Signatures to Achieve Accuracy
Abstract: AbstractSignature of spectrum is data convert appearances those to make for least accuracy variation by generalization and extension in place of expansion. Pixel form has subjected to change from multi-spectra issued to hyperspectral formation after issue of spectroscopic forms. Spectral signatures perform have scaled to measure from agronomy to metallurgical element detecting prosecution. Optimism appeared in species differentiation between coconut and palm oil plantation. Updating forms from spectroscopic hyper-spectra have …
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 3, 2019 · pp. 26–31 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Emerging Paradigms in Parallel Computing: Trends and Innovations
Abstract: Parallel computing is at an inflection point with revolutionary new paradigms and technologies. The goal of this paper is to survey the recent trend in parallel computing from architecture, programming model and applications. Mahajan cites a litany of architectural developments such as heterogeneous computing systems with integrated graphics processing unit/central processing unit ; the emerging promise from quantum and neuromorphic architectures (please see later); advances in packing transistors using novel …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 39–43 Read article
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Change Detection in Aerial Imagery
Abstract: The development of the Multi U-Net engineering marks an essential headway in geospatial question location inside ethereal symbolism investigation. The altered U-Net addresses the complexities of multi-class division in assorted geospatial settings. Leveraging the inalienable growing and contracting pathways inside U-Net plans, the Multi U-Net exceeds expectations in capturing complicated spatial data, in this manner setting up a vigorous establishment for exact division. The extend envelops an advanced picture handling …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 22–28 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and graphics processing unit (GPU)-based architectures without centralizing sensitive data. This work proposes a parallel adaptive federated learning (AFL) framework that integrates differential privacy and secure aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 09–16 Read article
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Data-Driven Design Framework for Biofunctional Polymer Composite Materials
Abstract: This paper introduces a knowledge-based design platform of biofunctional polymer composite substances through the combination of machine learning, materials informatics, and digital twins applications. The framework allows the effortless forecasting and maximization of mechanical, biological and degradation characteristics based on supervised, unsupervised and deep learning models. A materials database is accompanied by the AI algorithms to find the best material compositions and microstructure-property relationships. Experimental validation proves to be more …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Digital Enablers of Nanomedicine: Pharmaceutical Software Across the Lifecycle of Nanotechnology‑Based Drug Products
Abstract: Nanotechnology‑based drug products have rapidly evolved from laboratory concepts to clinically relevant therapies, yet their development is constrained by complex design variables, stringent quality requirements, and emerging regulatory expectations specific to nanomaterials. Pharmaceutical software now plays a central role in the nanomedicine lifecycle, enabling in silico design of nano‑carriers, simulation of nano–bio interactions, control of nanoscale quality attributes during manufacturing, and systematic tracking of safety signals in real‑world use. Integrated …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 11–16 Read article
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Micro Level Mobility Intervention in Urban Spatial Structure in Reducing GHG Emissions: A Case of The City of Lucknow, Prayagraj and Varanasi
Abstract: In contemporary times, the Greenhouse Effect has emerged as a paramount concern in urban areas. With India undergoing rapid urbanization, cities are witnessing soaring temperatures. Greenhouse gas emissions are one of the main causes of the Greenhouse Effect. India stands among the highest emitters of GHGs, primarily stemming from the energy sector, particularly in electricity generation. The period from 2005 to 2018 saw a noteworthy surge in India's emissions, largely …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 25–33 Read article
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An Experimental Study to Assess the Effectiveness of Valsalva Maneuver Prior to Intravenous Cannulation on Pain Perception among Patients Undergoing Venous Cannulation at HAHC Hospital in Delhi
Abstract: An experimental study was done to assess the effectiveness of valsalva maneuver prior to IV cannulation on pain perception among patients undergoing venous cannulation at HAHC hospital in Delhi. The objectives of the study were to assess the level of pain during IV cannulation among the experimental group, to assess the level of pain during IV cannulation among the control group, to compare the level of pain during IV cannulation …
Published in Research and Reviews : Journal of Surgery · Vol. 5, Issue 2, 2016 · pp. 1–6 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Modelling Electronic Diode Networks with PSPICE Simulation
Abstract: The dual of Thevenin, Norton equivalent circuit is used in place of any circuit/network of linear sources and immittances at at a given frequency. Both Thevenin with Norton theorem is useful for analyses and modification of circuits, to study /obtain network’s steady state response and initial condition. Methods to represent different circuits with Thevenin/Norton impedances connected at desired nodes are given using Spice/Pspice. The Thevenin/Norton impedances connected are of other …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 17–37 Read article
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Leveraging Deep Learning and Cloud Computing for Water Usage Optimization in Agriculture: A Study
Abstract: Water scarcity and inefficient irrigation practices are significant challenges in modern agriculture. This research investigates how deep learning and cloud computing can be combined to enhance water efficiency in agricultural practices. Leveraging advancements in deep learning and cloud computing, researchers have developed innovative solutions for optimizing water usage. This review examines the state-of-the-art methodologies, technologies, and applications in smart irrigation systems. It explores how deep learning models and cloud platforms …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 83–91 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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Study of a Western Disturbance of 2023 Using Satellite-Based Observation, Reanalysis Data, and Numerical Simulation
Abstract: Western Disturbances (WDs) are synoptic-scale, extratropical storm systems that influence winter precipitation across northwest India. This study focuses on a specific WD event that occurred from 24– 25 March 2023, affecting Jammu & Kashmir, Himachal Pradesh, Uttarakhand, and Punjab. The analysis integrates satellite observations, ERA-5 reanalysis data, and simulations from the Weather Research and Forecasting (WRF) model to evaluate the model's performance. The novelty of this study lies in its …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 16–38 Read article
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Integrating Plant Selection, Planting Design, and Landscape Construction for Sustainable Site Development
Abstract: This paper explores the interrelationship between plant selection, planting design, and landscape construction in achieving ecologically sustainable and aesthetically pleasing outdoor environments. Plant selection involves choosing species that are well adapted to site conditions, ecological functions, maintenance regimes, and visual preferences. Planting design refers to the arrangement, composition, and spatial organization of plant materials to meet functional, aesthetic, and environmental objectives. Landscape construction encompasses implementation—from site preparation and planting through …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article