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83 results for “Computational Efficiency”
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Research ArticleOpen accessPhrase in the titleA Comparative Computational Efficiency Analysis of LSB and Hybrid Steganographic MethodsDivya Sharma, Chander PrabhaElectronic Medical Images (EMI) are of various types such as X-rays, CT scans, MRIs, etc. EMIs are generally large, but they vary in dimensions and sizes based on the body part to which they belong. Not much research has been done to secure EMIs due to their varied and large sizes, while ensuring their accessibility for real-time transmission. Where access … …Journal of Computer Science, Vol. 21, Issue 10 · 28 Nov 2025 · 2,458 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImpact of the Edges of a Backside Diffusive Reflector on the External Quantum Efficiency of Luminescent Solar Concentrators: Experimental and Computational ApproachMauro Pravettoni, Cristina S. Polo Lòpez, Robert P. KennyLuminescent Solar Concentrators (LSCs) have been proposed in the 1970s as cheap planar concentrators for residential applications and nowadays represent a novel idea with excellent perspectives for building integration photovoltaics. The interest in LSCs has increased in the last years, due to improved stability of luminescent dyes, the introduction of quantum dots and nanorods and the overall reported increase in … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 1 · 18 Jan 2016 · 8,364 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 383 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEffect of Size of Heated Obstruction within Room on Three Dimensional Air Flow CharacteristicsAbduljabbar Muttair Ahmed, Mukhtar Ahmad, Abdur RahimProblem statement: This study reported a numerical investigation of three-dimensional turbulent buoyant recirculating flow within a room with heated obstruction. Approach: The study involved the solution of partial differential equations for the conservation of mass, momentum, energy, concentration, turbulent energy and its dissipation rate. These equations were solved together with algebraic expressions for the turbulent viscosity and the heat diffusivity, … …American Journal of Engineering and Applied Sciences, Vol. 3, Issue 2 · 30 Jun 2010 · 6,934 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessIn the abstractLightweight Deep Learning Model for TFT-LCD Pixel Defect Detection Using MobileNetV2J. Sheikshabjan, K. Dhanakodi, A.T. Rajamanickam et al.The proposed methodology aims to achieve high classification accuracy while maintaining computational efficiency and minimizing inference latency, making it highly suitable for real-time industrial inspection scenarios. This study evaluated five traditional transfer learning models (VGG16, ResNet50, MobileNetV2, Xception, and InceptionV3) for comparison in pixel defect detection. MobileNetV2-based implementation demonstrated a competitive average test accuracy of 0.9916, outperforming several baselines while … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 673 accessesView PDFCite
Research ArticleOpen accessIn the abstractCascaded MNetV3UNet: A Lightweight Two-Stage Architecture for High-Precision Brain Tumor Segmentation in MRIMayuri Popat, Sanskruti PatelPrecise brain tumor segmentation is an essential but quite challenging process in MRI images because of their irregular shapes, heterogeneous appearance, and low contrast with surrounding tissues. While U-Net-based architectures have achieved significant success, their high computational complexity limits deployment on resource-constrained systems. In this study, a Novel two-stage cascaded architecture, MNetV3UNet, is introduced, which employs the light-weight MobileNetV3-Large as … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment and Validation of a 2D Finite Element Model for Air Pollution Dispersion (SUITE-2D)Youssef Ismail HafezThis paper presents the development and validation of SUITE-2D (Solving Unsteady Incompressible Transport Equation in Two Dimensions), a two-dimensional finite element model for solving the advection-diffusion transport equation with decay and source terms. The model provides an efficient and accurate approach for simulating pollutant dispersion in environmental systems. The finite element formulation uses the standard Galerkin method, with numerical integration … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 22 Dec 2025 · 3,127 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite