Digital Image Watermarking Using Balanced Multiwavelets حسب Ghouti, L.

"…In this paper, a robust watermarking algorithm using balanced multiwavelet transform is proposed. …"
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Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier حسب Yassine Himeur (14158821)

"…An accuracy of up to 99.65% and 98.51% has been achieved on GREEND and UK-DALE data sets, respectively. While an accuracy of more than 96% has been attained on both WHITED and PLAID data sets. …"

Anonymizing multimedia documents حسب Haraty, Ramzi

"…A set of experiments are elaborated to demonstrate the efficiency of our technique.…"
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Structural similarity evaluation between XML documents and DTDs حسب Tekli, J.

"…It is of polynomial complexity, in comparison with existing exponential algorithms. Classification experiments, conducted on large sets of real and synthetic XML documents, underline our approach effectiveness, as well as its applicability to large XML repositories and databases. © Springer-Verlag Berlin Heidelberg 2007.…"
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test حسب Hasan T. Abbas (8115014)

"…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…<p dir="ltr">Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. …"

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges حسب Muhammad Mohsin Khan (22303366)

"…Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …"

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review حسب Alaa Abd-alrazaq (17058018)

"…The most frequently used data set from open sources was Depresjon. The most commonly used algorithm was random forest, followed by support vector machine.…"

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images حسب Rehan Raza (17019105)

"…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …"

A Biologicaly Inspired Decision Model for Multivariable Genetic- Fuzzy-AHP System حسب Kouatli, Issam

"…This paper describes a hybridized intelligent algorithm as a tuning mechanism for one type of Genetic Fuzzy system termed the Genetic Fuzzimetric Technique (GFT). …"
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Inferential sensing techniques in industrial applications حسب Shakil,, Muhammad

"…Different types of dynamical neural networks are combined according to system operation and emission behavior. Real data from a boiler plant is used to develop the model. …"
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

"…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …"
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Investigation of Forming a Framework to shortlist contractors in the tendering phase حسب DABASH, MOHANNAD SALAH

"…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …"
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Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care حسب Regina Padmanabhan (14231606)

"…Other highlights are (1) a novel set of easily available features for the prediction of the aforementioned clinical complications and (2) the use of data augmentation methods and model-scoring-based hyperparameter tuning to address the problem of class disproportionality, a common challenge in medical datasets and often the reason behind poor event prediction rate of various predictive models reported so far. …"

Uplink Noma in UAV-Assisted IoT Networks حسب Mrad, Ali

"…This technology proves important in scenarios with time-sensitive services when data has to be collected before a set deadline, otherwise, it is rendered useless, as well as, in scenarios with limited resources and large number of users. …"
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Indoor Localization Schemes for Mobile Robots حسب Al-Jarrah, Islam Mohammad-Amin

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Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

"…The proposed model is thoroughly assessed through an empirical study using a real data set from Australia. The simulation results confirm the performance superiority of the proposed model over the existing forecasting models with the lowest average root mean square error and mean absolute percentage error of 3.88kW and 2.30%, respectively.…"

Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers حسب Ali Sharida (17947847)

"…The DT is trained offline using a set of experimental data and updated online to get the maximum possible accuracy. …"

Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review حسب Alaa Abd-alrazaq (17058018)

"…The most common purposes of AI were the detection of disease and the evaluation of user performance. The size of the data set ranged from 36 to 795,600. The most common validation techniques used in the included studies were k-fold cross-validation and training-test split validation. …"

MoveSchedule حسب Zouein, Pierette

"…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …"
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