Pre-production movie rating prediction using machine learning. (c2017) by Gerges, Firas Abdallah

“…In this work, we present several machine learning techniques (Support Vectors Machine, K-Nearest Neighbors, C5, Neural Networks and Case-Based Reasoning) along with a genetic algorithm to predict the success of a movie before its production using the IMDB rating as an indicator of the success. …”
Get full text
Get full text
Get full text

Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
Get full text
Get full text

Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…In this regard, our study aims to predict the permeability of molecules across the placental barrier. Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. …”

Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…</p><p><br></p><h3>Methods</h3><p dir="ltr">We developed an XGBoost-based machine learning model to predict pathogenicity of BRCA2 variants. …”

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

Get full text

FPGA-based Parallel Hardware Architecture for Real-time Object Classification by Qasaimeh, Murad Mohammad

Get full text

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”

Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…Furthermore, more advanced algorithms can be used such as Support Vector machine (SVM) and XGBoost.…”
Get full text

Hybrid deep learning based threat intelligence framework for Industrial IoT systems by Jahanzaib Malik (23718816)

Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

Get full text

Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

Get full text
Get full text

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …”

A parallel optimization algorithm for the maximum clique problem. (c2008) by Rizk, Mohamad A.

Get full text
Get full text

Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi (16888710)

“…Subsequently, state-of-the-art research that envisions the use of clustering-based machine learning and deep learning-based solutions for PGP is presented. …”

Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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

Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

Get full text

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)