A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”

Big Data Energy Management, Analytics and Visualization for Residential Areas by Gupta, Ragini

“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…Data envelopment analysis (DEA) is a widely used benchmarking technique. …”
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A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities by Muhammad Mazhar Rathore (17051745)

Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

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

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles by 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. …”

Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by 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. …”

A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by 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 by Arshad, Muhammad Arbab

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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

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

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

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

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

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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices by 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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LaScaDa: A Novel Scalable Topology for Data Center Network by 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 by 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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