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Showing 1 - 20 results of 91 for search '(( element study algorithm ) OR ((( element method algorithm ) OR ( event modeling algorithm ))))', query time: 0.15s Refine Results
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    Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study by Alkhodari, Mohanad Ahmed

    Published 2021
    “…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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    A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

    Published 2025
    “…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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    Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

    Published 2024
    “…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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    Process Mining over Unordered Event Streams by Awad, Ahmed

    Published 2020
    “…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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    I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams by Raun, Kristo

    Published 2023
    “…Finally, the algorithm is stress tested for performance using a simulation of high-traffic event streams.…”
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    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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    Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

    Published 2021
    “…Conformance checking compares a process model and recorded executions of a process, i.e., a log of traces. …”
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    Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers by Hamidreza Besharatifard (16904823)

    Published 2022
    “…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”
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    Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

    Published 1993
    “…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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    Generic metadata representation framework for social-based event detection, description, and linkage by Abebe, Minale A.

    Published 2020
    “…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …”
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    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Therefore, in this paper we propose the usage of historical charging data in conjunction with weather, traffic, and events data to predict EV session duration and energy consumption using popular machine learning algorithms including random forest, SVM, XGBoost and deep neural networks. …”
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