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Showing 1 - 20 results of 79 for search '(( elements data algorithm ) OR ((( current sampling algorithm ) OR ( event modeling algorithm ))))', query time: 0.13s Refine Results
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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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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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    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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    An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication by Syed Muhammad Amrr (16855557)

    Published 2019
    “…Aligned with these design objectives, a robust event-triggered attitude control algorithm is proposed to regulate the orientation of a flexible spacecraft subjected to parametric uncertainties, external disturbances, and vibrations due to flexible appendages. …”
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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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    Current trends and future orientation in diagnosing lung pathologies: A systematic survey by Noorizadeh, Mohammad

    Published 2025
    “…This study examined the current state-of-the-art methods and offers a comprehensive analysis of their advantages and disadvantages from an engineering perspective. …”
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    Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population by Amr M. Fahmi (21632909)

    Published 2024
    “…Each patient provided a saliva sample. DNA was extracted, purified and genotyped for <i>VKORC−1639 G>A, CYP2C9*2, CYP2C9*3 </i>and<i> CYP4F2*3</i>. …”
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    Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

    Published 2018
    “…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

    Published 2012
    “…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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