Use of Data Mining Techniques to Detect Fraud in Procurement Sector حسب AL HAMMADI, SUMAYYA ABDULLA

"…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …"
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Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

"…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …"

An efficient approach for textual data classification using deep learning حسب Abdullah Alqahtani (7128143)

"…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …"

VEGAWES: variational segmentation on whole exome sequencing for copy number detection حسب Samreen Anjum (19651882)

"…In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. …"

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory حسب Wehbi, Osama

"…Based on our simulation findings, our strategy surpasses the VanillaF selection approach in terms of maximizing both the revenues of the client devices and accuracy of the global federated learning model.…"
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Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles حسب Zainab Akhtar (15192184)

"…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …"

I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams حسب Raun, Kristo

"…This paper introduces a new approximate algorithm – I Will Survive (IWS). The algorithm utilizes the trie data structure to improve the calculation speed, while remaining memory-efficient. …"
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring حسب Sakib Mahmud (15302404)

"…Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …"

Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy حسب Raad, M.W.

"…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Center for Applied Physical Sciences (CAPS). …"
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data حسب Arshad, Muhammad Arbab

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Advancing Data Center Networks: A Focus on Energy and Cost Efficiency حسب Zina Chkirbene (16869987)

"…<p dir="ltr">Data centers serve as the backbone for cloud computing, enterprise services, and infrastructure-based offerings. …"

Education Data Mining to Predict Student Exam Grades in Vocational Institutes حسب Saleh, Ashjan Ahmad

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Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining حسب Alqaryouti, Omar

"…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …"
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study حسب Ayman Hassan (14426412)

"…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…"

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model حسب Ramesh Sundar (19326046)

"…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …"

UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices حسب Samir, Moataz

"…Then, we develop an effective sub-optimal algorithm based on successive convex approximation in order to obtain results for larger network scenarios. …"
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An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication حسب Syed Muhammad Amrr (16855557)

"…Moreover, the numerical comparative analysis shows that the proposed approach performs better than periodically sampled data technique and sliding mode-based event-triggered technique.…"

LaScaDa: A Novel Scalable Topology for Data Center Network حسب Zina Chkirbene (16869987)

"…<p dir="ltr">The growth of cloud-based services is mainly supported by the core networking infrastructures of large-scale data centers, while the scalability of these services is influenced by the performance and dependability characteristics of data centers. …"

Heat rate curve approximation for power plants without data measuring devices حسب Poullikkas, Andreas

"…In this work, a numerical method, based on the one-dimensional finite difference technique, is proposed for the approximation of the heat rate curve, which can be applied for power plants in which no data acquisition is available. …"
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Artificial intelligence models for predicting the mode of delivery in maternal care حسب Rawan AlSaad (14159019)

"…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …"