Semantic based navigation and lane keeping by Abdeen, Abdallah Adel

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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”

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

“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group by Iqtadar Hussain (14147850)

“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S₈ semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by Zhitao Xu (2426023)

“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”

On sensor selection in mobile devices based on energy, application accuracy, and context metrics by Taleb, Sireen

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

“…With all the preventive methods, malicious users still find new methods that overcome the system security, and access and modify the sensitive information. To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
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Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights by Malekloo, Arman

“…Connecting the ubiquitous sensing and big data processing of critical information in infrastructures through the IoT paradigm is the future of SHM systems. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints by Mohammed Al Disi (16855407)

Exploring the Impact of Explainable Artificial Intelligence on Decision-making in Healthcare by MOHAMMAD, AHMAD HASAN

“…The study analyses the benefits and limitations of applying XAI in healthcare decision-making processes through an exhaustive analysis of current literature and empirical data. …”
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Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies.…”
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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)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. The ANN reliability is directly related to the success of the training process. …”

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”