A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…The proposed technique involved two major steps: feature selection and fault classification. Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”

DNA Base-Calling Techniques by Odeh, Fadi

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Advancing Interpretability in Sequential Models Through Generative AI Rationalization Using GPT-4 by Mohammed Rasol Al Saidat

“…In this study, we investigate the role of Generative Pre-trained Transformer 4 (GPT-4) in enhancing interpretability of sequential predictions in Natural Language Processing (NLP). …”
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Lung nodule classification utilizing support vector machines by Mousa, W.A.H.

“…We intend to automate the pre-processing detection process to further enhance the overall classification.…”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. …”

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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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. …”

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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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. …”

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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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. …”

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.…”

Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…We searched Embase, PubMed, Scopus, and Google Scholar to retrieve relevant studies. After pre-processing and screening, we extracted data from 34 studies that fulfilled the inclusion criteria. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…<p dir="ltr">Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”

The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. …”
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