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. …”

Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …”

Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…Techniques for natural language processing may be used to text data to extract useful features like sentiment, emotion, and subjectivity. …”
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Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

“…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”

Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”

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. …”

Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration by Al-Yamani, A.

“…Using SAS, this paper also presents systematic scan reconfiguration, a test data compression algorithm that is applied to achieve 10times to 40 times compression ratios without requiring any information from the automatic-test-pattern-generation tool about the unspecified bits. …”
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Data Redundancy Management in Connected Environments by Mansour, Elio

“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by D., Sathish Kumar

“…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems.…”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by M. Premkumar (12757280)

“…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. …”

Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

“…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”

Assessment of four dose calculation algorithms using IAEA-TECDOC-1583 with medium dependency correction factor (K_med) application by Aram Rostami (22045274)

“…<h3>Purpose</h3><p dir="ltr">This study discusses the measurement of dose in clinical commissioning tests described in IAEA-TECDOC-1583. It explores the application of Monte Carlo (MC) modelled medium dependency correction factors (K_med) for accurate dose measurement in bone and lung materials using the CIRS phantom. …”

An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…The work presented in thesis add to the existing literature in a proposing the use of a genetic algorithm uncertain approach to resource- scheduling in projects. …”
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Methods for system-on-chip test design, scheduling and optimization. (c2006) by Farah, Rana

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Secure Storage of Crypto Wallet Seed Phrase Using ECC and Splitting Technique by Syeda Tayyaba Bukhari (21842078)

Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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