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.…”

Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

“…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”

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

“…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …”
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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…This paper presents a machine learning approach for Android malware detection. In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

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. …”

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT by Arumugam K (18456690)

“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”

Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

“…The time efficiency of both proposed algorithms renders them well-suited for deployment in IoT ecosystems. …”

Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

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Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning by Md Nazmul Islam Shuzan (21842426)

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

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Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

“…A pattern recognition model is applied to a revealed preference (RP) survey obtained from the Ministry of Transportation and Communication (MoTC) in Qatar for the travel diary for blue-collar workers. Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”

Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels by Bernard J. Jansen (7434779)

“…<p dir="ltr">Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. …”

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review by Mohamed Massaoudi (16888710)

“…These technologies include federated learning, deep transfer learning, incremental learning, and big data DL. …”

Human digital thought clones: the <i>Holy Grail</i> of artificial intelligence for big data by Jon Truby (14153022)

The Use of Microwave Tomography in Bone Healing Monitoring by Alkhodari, Mohanad Ahmed

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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)