Category: Engineering

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  • Experimental verification of the six sectors neural DTC approach of squirrel cage induction motors

    Experimental verification of the six sectors neural DTC approach of squirrel cage induction motors

    Electrical machines are many and varied, and they can be divided according to the type of current into direct-current electric machines and alternating-current electric machines1. Nowadays, alternating current machines are the most widely used…

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  • Life cycle assessment based method for the environmental and mechanical evaluation of waste tire rubber concretes

    Life cycle assessment based method for the environmental and mechanical evaluation of waste tire rubber concretes

    Results of scoring

    The life cycle assessment (LCA) and estimation of environmental impact generation were conducted using SimaPro software54. Figure 4 shows the obtained environmental scores for different scenarios. A lower environmental score…

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  • Evolution of strain field and crack prediction in cemented paste backfill specimens based on digital image correlation and computer vision recognition model

    Evolution of strain field and crack prediction in cemented paste backfill specimens based on digital image correlation and computer vision recognition model

    Experimental findings

    UCS and slump tests were executed on CPB specimens derived from whole tailings, with slurry filling concentration and cement-to-tailings ratios serving as the principal variables. The experimental results are presented in…

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  • Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems

    Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems

    Evaluating the interpretability of ML models

    Although DTR, BRR, GBR, and ANN contribute to the explanatory power of the model, the interpretability of these models remains a significant concern in modeling. Machine learning models, in general, are…

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  • A novel method for estimating functional connectivity from EEG coherence potentials

    A novel method for estimating functional connectivity from EEG coherence potentials

    Ethical statement

    This study was approved by the Health Media IRB (USA, OHRP IRB #00001211) and Sigma-IRB (India) and this study is conducted in accordance with Title 45, the code of federal regulations, sub-part A of NIH (USA), and Indian…

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  • An optimized deep learning based hybrid model for prediction of daily average global solar irradiance using CNN SLSTM architecture

    An optimized deep learning based hybrid model for prediction of daily average global solar irradiance using CNN SLSTM architecture

    Data source and description

    The dataset collected from the Karur Solar Park was utilized in this study to predict the daily average global solar irradiation. It is situated at 122 m above sea level in Manjanaickenpatti, Karur, Tamil Nadu, India,…

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  • Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging

    Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging

    Artificial intelligence and machine learning have seen considerable progress in detecting and managing kidney stones in recent years. Deep learning has been proven invaluable in medical applications, as it can detect and localize kidney stones in…

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  • Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis

    Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis

  • Abrahamsen, B., van Staa, T., Ariely, R., Olson, M. & Cooper, C. Excess mortality following hip fracture: a systematic epidemiological review. Osteoporos. Int. 20, 1633–50. https://doi.org/10.1007/s00198-009-0920-3 (2009).

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  • Combining meta and ensemble learning to classify EEG for seizure detection

    Combining meta and ensemble learning to classify EEG for seizure detection

    Experimental datasets

    TUSZ dataset

    The Temple University Hospital (TUH)-EEG Corpus (TUEG) is publicly available from the Neural Engineering Data Consortium (NEDC) website (www.nedcdata.org). The TUEG Seizure Corpus (TUSZ) is a subset of the TUH…

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