Showing 21 - 40 results of 62 for search '(((( implement box algorithm ) OR ( elements control algorithm ))) OR ( level finding algorithm ))', query time: 0.12s Refine Results
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    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

    Published 2023
    “…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
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    Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

    Published 2006
    “…Adaptive tracking of nonlinear dynamic plants is an essential element of many control applications. The main difficulty felt in establishing the tracking of nonlinear dynamic plants is the computational complexity in controller design. …”
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    article
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    On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

    Published 2023
    “…However, considering the OSW, which has not been addressed in the project scheduling problems, requires the construction site to have a space capacity constraint while considering the workshop size, availability level, and other project-related constraints. In the present work, by considering the OSWs, a real construction project scheduling problem is studied as a Multi-Mode On-Site Workshop Investment Problem with Tardiness (MOSWIPT) while finding the installation/dismantling time of the OSWs. …”
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    Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

    Published 2023
    “…The marginal error of only 0.72% in the hybrid approach showcases its high precision and reliability in determining the optimal levels of machining parameters. These findings underscore the potential of the Taguchi optimization method, ANFIS, and GA in achieving superior results in the tensile testing of materials, particularly in cases where multiple parameters are involved. …”
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    Timing influenced general-cell genetic floorplanner by Sait, Sadiq M.

    Published 2020
    “…The second phase of floorplanner allows modification to the aspect ratios of individual modules to further reduce the area of the overall bounding box. The first phase is implemented using genetic algorithm while in the second phase we adopt a constraint graph based approach. …”
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    article
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    A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions by Chakarajamula Hussaian Basha (21633167)

    Published 2024
    “…The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. …”
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    Regression testing web services-based applications by Tarhini, Abbas

    Published 2006
    “…In this paper, we present a safe regression testing algorithm that selects an adequate number of non-redundant test sequences aiming to find modification-related errors. …”
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    Semantics-based approach for detecting flaws, conflicts and redundancies in XACML policies by Jebbaoui, Hussein

    Published 2015
    “…XACML (eXtensible Access Control Markup Language) policies, which are widely adopted for defining and controlling dynamic access among Web/cloud services, are becoming more complex in order to handle the significant growth in communication and cooperation between individuals and composed services. …”
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    article
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    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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