Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Therefore, this study investigates the effect of optimization algorithms on the prediction accuracy of the multilayer perceptron neural networks (MLPNNs). …”

MSLP: mRNA subcellular localization predictor based on machine learning techniques by Saleh Musleh (15279190)

“…</p><h3>Methods</h3><p dir="ltr">In this article, we propose MSLP, a machine learning-based method to predict the subcellular localization of mRNA. We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.…”

Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

“…The novel LSTM time series algorithm proved to work best for demand forecasting. …”
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An integrated partitioning and synthesis system for dynamically reconfigurable Multi-FPGA architectures by Ouaiss, Iyad

“…The SPARCS system accepts design specifications at the behavior level, in the form of task graphs. The system contains a temporal partitioning tool to temporally divide and schedule the tasks on the reconfigurable architecture, a spatial partitioning tool to map the tasks to individual FPGAs, and a high-level synthesis tool to synthesize efficient register-transfer level designs for each set of tasks destined to be downloaded on each FPGA. …”
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Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

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Multi-Model Investigation and Adaptive Estimation of the Acoustic Release of a Model Drug From Liposomes by Wadi, Ali

“…Finally, the proposed algorithm is not computationally demanding and is capable of online estimation tasks.…”
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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection by Sui Paul Ang (18460605)

“…This paper proposes a novel neural architecture search (NAS) algorithm, named MSD-NAS, to automate this laborious task. …”

Sentiment analysis for Arabizi in social media. (c2015) by Tobaili, Taha

“…We took the initiative to make use of this abundance of data by analyzing it and predicting sentiment. Applying the same sentiment analysis techniques that are used on English for Arabic is not a simple task due to their semantic and structural differences, and because Arabic is a rich morphological language. …”
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DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

“…<p>Training a deep neural network on a large dataset to convergence is a time-demanding task. This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”

A new method for broad‐scale modeling and projection of plant assemblages under climatic, biotic, and environmental cofiltering by Alessandro Ferrarini (3951098)

“…To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. …”

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. …”

Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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Next-generation energy systems for sustainable smart cities: Roles of transfer learning by Yassine Himeur (14158821)

“…However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. …”

Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”

Process Mining over Unordered Event Streams by Awad, Ahmed

“…While such online algorithms have been proposed for several process mining tasks, from discovery through confor mance checking to time prediction, they all assume that an event stream is ordered, meaning that the order of event generation coincides with their arrival at the analysis engine. …”
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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. …”

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. …”

An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation by Abdul Rahman, Sawsan

“…The concept of crowdsensing implies the reliance on the crowd to perform sensing tasks and collect data about a phenomena of interest. …”
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Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. …”

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …”