Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks by Mohamed Amjath (17542512)

“…This study considers determining the optimal size of a homogeneous fleet of trucks to be outsourced (or subcontracted) from a third-party logistics provider to be used daily to cyclically transport different types of raw materials from designated storage yards to intermediate buffer locations to be fed as inputs to a production facility for processing. …”

Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining by Koen Schaaf (14778139)

“…Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. …”

Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

“…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. …”

On the exact recovery of the FFT of noisy signals using a non-subtractively dither-quantized input channel by Cheded, L.

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Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array by Amran Hossain (570706)

“…Later, a nine-antenna array-based microwave brain imaging (MBI) system is implemented and investigated by using phantom model. After that, the scattering parameters are collected, analyzed, and then processed by the Iteratively Corrected delay-multiply-and-sum algorithm to detect and reconstruct the brain tumor images. …”

Sentiment visualization of correlation of loneliness mapped through social intelligence analysis by Hurmat Ali Shah (18192889)

“…</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. By using natural language (NLP) processing, sentiment analysis, and topic modeling, we seek to understand prevalent sentiments and concerns. …”

An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models by K. Mukilan (22224793)

Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

“…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…<p dir="ltr">The present study evaluates the effect of co-digestion of agricultural solid wastes (ASWs), cow manure (CM), and the application of chemical pre-treatment with NaHCO₃ on the performance of anaerobic digestion (AD) process. An Artificial neural network (ANN) algorithm was developed to model and optimize the cumulative methane production (CMP) from ASWs, CM, and their mixture under mesophilic and thermophilic conditions. …”

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …”
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Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation by Attieh, Joseph

“…The latter is trained using the gradient descent algorithm allowing to iteratively update the term-category matrix until reaching convergence. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

“…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …”

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria by Nasser Yimen (16697129)

“…In the first step, the MATLAB environment was used to run simulations and optimize the system via the genetic algorithm. …”

Practical Multiple Node Failure Recovery in Distributed Storage Systems by Itani, M.

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

“…<p dir="ltr">Recently, electrochemical reduction of CO₂ into value-added fuels has been noticed as a promising process to decrease CO₂ emissions. The development of such technology is strongly depended upon tuning the surface properties of the applied electrocatalysts. …”