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). …”

Artificial intelligence in respiratory care by Manjush Karthika (18384907)

Boosting the visibility of services in microservice architecture by Ahmet Vedat Tokmak (17773479)

“…Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…”

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. …”

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”

A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”

Optimizing ADWIN for Steady Streams by Moharram, Hassan

“…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …”
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IoT-Based Sustainable Parking Lot by Binmahfooz, Abdullah

“…Moreover, a carbon emissions sensor at the gate is used to detect the generated emission rates by vehicles entering the parking lot. Furthermore, deep learning neural network was used to predict the congestion of the parking lot at any day or time. …”
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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. …”

DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

“…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”

Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine by Naila, Rabbani

“…Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. …”
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Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis by Jithin Kalathikudiyil Sreedharan (18268894)

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control by Mahmoud Dahmani (18810247)

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

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Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. This model can be used in a clinical setting as a decision support system or for public health awareness as an informal risk prediction system. …”
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The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

“…<p dir="ltr">Imbalanced datasets affect the performance of machine learning algorithms adversely. To cope with this problem, several resampling methods have been developed recently. …”

Social Network Analysis for Precise Friend Suggestion for Twitter by Associating Multiple Networks Using ML by Dharmendra Kumar Singh Singh (19517710)

“…<p dir="ltr">The main aim in this paper is to create a friend suggestion algorithm that can be used to recommend new friends to a user on Twitter when their existing friends and other details are given. …”

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.…”