Intelligent Hybrid Feature Selection for Textual Sentiment Classification by Jawad Khan (6422669)

“…Researchers have also proposed feature extraction and selection techniques to reduce high dimensional feature space, but they fall short in extracting and selecting the most effective sentiment features for sentiment model learning. Effective feature extraction and selection are significant for the SA because they can boost the learning algorithm’s predictive performance while reducing the high-dimensional feature space. …”

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)

“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”

Automated skills assessment in open surgery: A scoping review by Hawa Hamza (17707224)

“…About 35 % utilized deep learning algorithms, specifically convolutional neural networks (CNN) (<i>n </i>= 14). …”

Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

Get full text

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

Exploring the System Dynamics of Covid-19 in Emergency Medical Services by Ali, Muhammad

“…Results show that the number of calls and number of missions dropped yet, the emergency response time was higher and more variable than in previous years. The predictive analysis yielded a model of response times for emergency missions through machine learning, specifically using a random forest algorithm. …”
Get full text
Get full text
Get full text

Connectionist technique estimates of hydrogen storage capacity on metal hydrides using hybrid GAPSO-LSSVM approach by Sina Maghsoudy (21393539)

“…Meanwhile, the estimation of hydrogen storage capacity will accelerate their development procedure. Machine learning algorithms can predict the correlation between the metal hydride chemical composition and its hydrogen storage capacity. …”

The Assessment and Allocation of Public Private Partnership Risks in the UAE by Shaban, Mazhd

Get full text

Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges by Sk Injamamul Islam (14111241)

“…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …”

LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…We applied the SHAP algorithm to demonstrate the importance of most dominating features that were leveraged in the model. …”

Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”

Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

Get full text

Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…With strong R-squared values and high predictive accuracy, the Random Forest machine learning model predicts exergy efficiency, freshwater production, unit specific product cost (USPC), net present value (NPV), and environmental impact. …”

Design and Analysis of Secure Digital Twin Architecture by Shaikh, Eman

Get full text

Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks by Jafari, Reza

Get full text

Investigation of Forming a Framework to shortlist contractors in the tendering phase by 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. …”
Get full text

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. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”