Towards dental diagnostic systems: Synergizing wavelet transform with generative adversarial networks for enhanced image data fusion

Computers in Biology and Medicine, Год журнала: 2024, Номер 182, С. 109241 - 109241

Опубликована: Окт. 2, 2024

Язык: Английский

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Environmental engineering solutions for efficient soil classification in southern Syria: a clustering-correlation extreme learning approach

International Journal of Environmental Science and Technology, Год журнала: 2024, Номер unknown

Опубликована: Июнь 14, 2024

Язык: Английский

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Evaluating the performance of spherical, hemispherical, and tubular solar stills with various configurations - A detailed review

Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy, Год журнала: 2024, Номер 238(7), С. 1261 - 1296

Опубликована: Июль 22, 2024

Solving global water shortages has become an urgent challenge, hindering sustainable development. Therefore, comparing different solar still designs from application and economic perspectives is necessary. Solar distillation considered a major innovation in the alternative energy sector for purifying brackish or brine into clean water. Despite extensive literature on improved stills, determining most efficient residential industrial applications remains difficult. This review compares productivity of spherical, hemispherical, tubular designs. The aim to study factors that influence efficiency each type analyze recent research results obtained under conditions. show innovations design can take many forms improve productivity. For example, adding parabolic mirrors increase stills by 35 70%. Likewise, innovative such as rotating spheres changing bowl shapes significantly increased spherical hemispherical stills. retrofitting with vacuum generation technology yields 50 In addition, using nanomaterials, especially nanophase change materials (NPCM), 116.5%, producing 7.62 kg/m 2 per day. NPCM-equipped model was option among three

Язык: Английский

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Leak detection and localization in water distribution systems using advanced feature analysis and an Artificial Neural Network

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100685 - 100685

Опубликована: Авг. 3, 2024

This study capitalizes on a dataset, originally including 280 sensory measurements from laboratory-scale water distribution system, to advance the concept of leakage diagnosis and localization. The test rig are formulated in two configurations, namely looped branched layouts. paper processed time-domain data accelerometers dynamic pressure sensors into advanced statistical features of: Autocorrelation Coefficient (Au-C), Signal Energy (Sig-E), detect localize leakage. By Employment these features, research developed an expert system Artificial Neural Network (ANN) model designed with optimal parameters, neurons, hidden layers classify presence pinpoint location leaks within rig. effectiveness current approach is quantitatively evaluated using F1-scores accuracy metrics. A robust capability for both detecting localizing under varying conditions was established highest F1-score 86.5 % 86.2 %, respectively. findings underscore potential integrating Intelligence (AI) enhancing reliability dependability management systems. contributes broader application AI managing resources infrastructure resilience its support improve whereabouts.

Язык: Английский

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Optimizing water resources for sustainable desalination: The integration of expert systems and solar energy in experimental applications

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100683 - 100683

Опубликована: Авг. 3, 2024

The integration of renewable energy sources with multi-energy systems present challenges and opportunities to enhance sustainability. Among these, solar stills have emerged as a solution for water desalination. With the advent expert system technologies, avenues are opened improving operational efficiency distillers. This paper presents an innovative approach utilizing correlation analysis, ReliefF feature selection, k-Nearest Neighbor (kNN) algorithm forecasting cumulative distillate output double slope still. analysis is based on 6-cases-based dataset, which includes variations in relative different operational-environmental conditions. Key features that significantly impact overall performance were identified manage distiller productivity. findings reveal maximum was 1610 ML/m2.day due incorporating reflective materials phase change (PCM) enhancing distillation rates. kNN model evaluated its R2, RMSE, CVRMSE, best models achieving scores 0.995, 0.0033, 0.1666, respectively. These metrics underscore effectiveness proposed machine learning predicting output, thereby enabling informed management processes. Combining technologies computational intelligence holds significant promise sustainable environmental management, study presented.

Язык: Английский

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A Data Fusion Analysis and Random Forest Learning for Enhanced Control and Failure Diagnosis in Rotating Machinery

Journal of Failure Analysis and Prevention, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 15, 2024

Язык: Английский

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A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks

Open Engineering, Год журнала: 2024, Номер 14(1)

Опубликована: Янв. 1, 2024

Abstract Breast cancer is globally known to be a major health concern that necessitates advancements in detection and classification methods. This study introduces machine learning-based approach for breast diagnosis using benign malignant mammograms of cancer. A two-hidden-layer artificial neural network (ANN) model was designed categorize from mammographic images. Prior analysis, the images were subjected sophisticated data augmentation process leveraged denoising, contrast enhancement, application generative adversarial (GAN). multi-enhancement preprocessing enriched quality transformed them into format more amenable analysis by vectorizing pixel data. The methodology involved rigorous training ANN on input images, resulting significant improvement model’s ability classify accurately. Experimental results demonstrate notable enhancement performance, with an increase accuracy ranging 22.5 42.5% compared traditional scans. final achieved impressive rate unity, which considered all stages image processing, including normal, contrast-enhanced, denoised, GAN-enhanced outcomes this research underlined effectiveness medical imaging. Future innovations diagnostics are elaborated potential improve early patient outcomes. robust offered contribution biotechnological fields interest.

Язык: Английский

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Improving the Performance of Spherical Stills with Circular Absorber Surface, Wicks, Tracking System, and Back Reflector. A Practical Study

Опубликована: Янв. 1, 2025

Язык: Английский

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Zinc manganese oxide spinel phase nanomaterial layered on solar stills applications: An analytical study for improved performance compared with machine learning methods

Journal of Water Process Engineering, Год журнала: 2025, Номер 71, С. 107363 - 107363

Опубликована: Фев. 26, 2025

Язык: Английский

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Comparative CFD case study on forced convection: Analysis of constant vs variable air properties in channel flow

Open Engineering, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

Abstract In this study, a steady-state forced convection heat transfer (HT) of air flow in two-dimensional channel with circular cross-section is numerically investigated. The analysis considers two sources at uniform temperatures along the lower surface mini-channel, upper remaining adiabatic to facilitate energy exchange. are placed distances L 1 = 3.5 m and 2 1.5 on bottom surface. finite element method used solve momentum-energy equations using Computational fluid dynamics (CFD) software, under constant variable properties. HT rates computed for Reynolds numbers (Re ≤ 2,000) Prandtl number (Pr 0.713). study evaluates effects number, thermo-physical properties, thermal boundary conditions hydrodynamic behavior. Results show that changes Nusselt significantly influenced by Re source configuration, rate increases highlighting notable differences centerline temperature, velocity, conductive flux wall maximum difference 14% T 20°C. Pressure also decreases increasing shows good agreement between CFD results empirical Shah equation.

Язык: Английский

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