Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers by Hamidreza Besharatifard (16904823)

A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants by Khan, T.

“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
Get full text
Get full text

A Comprehensive Review of Digital Twin Technology in Building Energy Consumption Forecasting by Maissa Boukaf (22282279)

“…The digitalization of building energy forecasting systems, enhanced by Energy Digital Twin technology alongside IoT devices and advanced data-driven algorithms, offers substantial improvements in energy management and optimization, servicing, maintenance, and energy-efficient design. …”

A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…Several machine learning techniques can be used for text classification, but we have focused only on the recent trend of neural network algorithms. …”
Get full text
Get full text

Minimizing using BBO and DFO methods by El Zeghondy, Jean

“…The goal of this thesis is to develop two MATLAB codes for the numerical algorithm of [1]. To solve nonlinear differential equations we use Runge-Kutta method of fourth order, and for the minimization part, we use two different methods, namely Nelder-Mead and Model Based Descent methods. …”
Get full text
Get full text
Get full text

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

Get full text

Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
Get full text

Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
Get full text
Get full text
Get full text
Get full text

Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

Get full text

On the use of L/sub 2/ gap metric for identifying Hammersteim models by Al-Amer, S.H.

Get full text
Get full text

Stacking-based ensemble learning for remaining useful life estimation by Begum Ay Ture (17773170)

“…In this study, predictive models that estimate the remaining useful life of turbofan engines have been developed using deep learning algorithms on NASA’s turbofan engine degradation simulation dataset. …”

Internal Model Control Structure Using Adaptive Inverse Control Strategy by Shafiq, M.Riyaz

“…In this paper, we propose a new adaptive IMC scheme based on adaptive finite impulse response filters, which can be designed for both minimum and non-minimum phase systems in the same fashion. The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. …”
Get full text
Get full text

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm by Ali S. Alghamdi (17541711)

“…In this study, the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method (TPEM). …”

On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis by Md. Shafayet Hossain (16888833)

Sentiment visualization of correlation of loneliness mapped through social intelligence analysis by Hurmat Ali Shah (18192889)

“…By using natural language (NLP) processing, sentiment analysis, and topic modeling, we seek to understand prevalent sentiments and concerns. …”

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm by Abdelbasset Krama (16870008)

“…This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. …”

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”

Identification of physically based models of residential air-conditioners for direct load control management by El-Ferik, S.

“…In this work, we address the problem of identifying the parameters of an aggregated elemental model representing a housing unit with an A/C system. …”
Get full text
Get full text

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.…”