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processing algorithm » processing algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
pre processing » _ processing (Expand Search), image processing (Expand Search)
processing algorithm » processing algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
pre processing » _ processing (Expand Search), image processing (Expand Search)
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41
A PLC based power factor controller for a 3-phase induction motor
Published 2000“…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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42
Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…Finally a runlength plus a Huffman encoding are applied for binary coding of the quantized coefficients.…”
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43
Developing a Cooperative Behavior for Multi Agents System Application to Robot Soccer
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44
Multigrid solvers in reconfigurable hardware. (c2006)
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masterThesis -
45
Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…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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46
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. We clean the data, impute missing values, and eliminate the repeated columns. …”
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47
Downlink channel estimation for IMT-DS
Published 2001“…To obtain channel estimates during pilot symbols, we propose a chip level adaptive channel estimation which performs better than the conventional method. …”
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48
Measuring ripple effect for object-oriented programs. (c2004)
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49
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...
Published 2020“…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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50
Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone
Published 2021“…This risk is specifically eminent in monitoring data transmission traffic, espionage, troop movement, border surveillance, searching, and warfare battlefield phenomenon, etc. …”
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51
Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
Published 2020“…<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 NaHCO<sub>3</sub> on the performance of anaerobic digestion (AD) process. …”
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52
Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The performance level improvements are practically summarized in both the transmission and reception entities with the help of the proposed hybrid network architecture and the associated Dual Deep Network algorithm. …”
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53
DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…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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54
Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…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.…”
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55
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…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. …”
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56
Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. …”
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57
Oversampling techniques for imbalanced data in regression
Published 2024“…For image datasets, we employ Multi-Level Autoencoders, consisting of Convolutional and Fully Connected Autoencoders. …”
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58
Blockchain-Based Decentralized Architecture for Software Version Control
Published 2023“…The proof of authority (PoA) consensus algorithm will be used to approve the developer communicating modifications to the private blockchain network; the authority will only provide permission and will not be able to add, edit, or delete code files. …”
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59
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…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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60
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…<p dir="ltr">Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. …”