Data redundancy management for leaf-edges in connected environments by Mansour, Elio

“…Although the sensed data could be useful for various applications (e.g., event detection in cities, energy management in commercial buildings), it first requires pre-processing to clean various inconsistencies (e.g., anomalies, redundancies, missing values). …”
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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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Communications in electronic textile systems by Nakad, Z.

“…This paper studies the communication requirements between the computing and sensing elements of an e-textile. This communication is studied through the construction of a prototype as well as through modeling and simulation. …”
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Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…For sentiment analysis, pre-processing is a crucial step in the data preparation process. …”
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A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

“…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”

Analysis of Multi-User-Based UAV System With Outdated CSI by Parvez Shaik (21633041)

“…Optimization of UAV location and altitude is performed through a limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm to attain minimum OP (MOP). Results illustrate optimal performance dependent on the channel correlation parameters, antenna elements, and fading conditions. …”

A PLC based power factor controller for a 3-phase induction motor by Al-Ali, A.R.

“…In addition to keep its voltage to frequency ratio constant in order to maintain a maximum torque over the whole control conditions. During the online process a set of capacitors sized in a binary ratio will be switched on or off with the help of zero voltage static switches according to a control strategy to obtain a pre-specified power factor. …”
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Connectionist technique estimates of hydrogen storage capacity on metal hydrides using hybrid GAPSO-LSSVM approach by Sina Maghsoudy (21393539)

“…So the HGAPSO-LSSVM model had the highest accuracy. In this model, the statistical factors of R², STD, MSE, RMSE, and MRE were 0.980, 0.043, 0.0020, 0.045, and 0.972%, respectively. …”

Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…Manually annotated data from a corpus collection was used to label the information for deep learning purposes. Pre-processing is a vital part of the data preparation process for cyberbullying detection. …”
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An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…Textual data contains much useless information that must be pre-processed. We clean the data, impute missing values, and eliminate the repeated columns. …”

Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. …”
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Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…We consider the various DTD operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes. Our approach is based on the concept of tree edit distance, as an effective and efficient means for comparing tree structures, XML documents and DTDs being modeled as ordered labeled trees. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO₃ on the performance of anaerobic digestion (AD) process. …”

Corona power loss computation in bundled bipolar conductors by Al-Hamouz, Z.M.

“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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A hybrid approach for XML similarity by Tekli, Joe

“…Our approach comprises of an original edit distance operation cost model, introducing semantic relatedness of XML element/attribute labels, in traditional edit distance computations. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ObjectiveThis study utilized various classical machine learning techniques, such as support vector machines, k-nearest neighbors, and random forests, in conjunction with a modified deep learning approach called DeepRaman. These algorithms were employed to distinguish and categorize bacterial endotoxins, following appropriate spectral pre-processing, which involved novel filtering techniques and advanced feature extraction methods. …”
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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.…”