Developing a UAE-Based Disputes Prediction Model using Machine Learning by Abu Laila, Ibrahim Wasef Subhi

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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. …”
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THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”

Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

“…The most common purposes of AI were the detection of disease and the evaluation of user performance. The size of the data set ranged from 36 to 795,600. The most common validation techniques used in the included studies were k-fold cross-validation and training-test split validation. …”

Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

“…The esc-edRVFL is identified as the best-performing algorithm through a comprehensive evaluation of 31 UCI datasets.…”

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

“…This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user’s eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. …”

Exploring new horizons in neuroscience disease detection through innovative visual signal analysis by Nisreen Said Amer (17984077)

“…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …”

From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”

Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…<p>Speech denoising (SD) covers the algorithms that remove the background noise from the target speech and thus improve its quality and intelligibility. …”

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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Secure and Anonymous Communications Over Delay Tolerant Networks by Spiridon Bakiras (16896408)

“…Instead, our work introduces a novel message forwarding algorithm that delivers messages, from source to destination, via a random walk process. …”

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”

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

“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…To investigate the practicality and effectiveness of SemIndex, we discuss its physical design within a standard commercial RDBMS allowing to create, store, and query its graph structure, thus enabling the system to easily scale up and handle large volumes of data. We have conducted a battery of experiments to test the performance of SemIndex, evaluating its construction time, storage size, query processing time, and result quality, in comparison with legacy inverted index. …”
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…In the final phase, the new dataset is trained using active learning concept, and the test data is generated using a random DNA sequence method. …”
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

“…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose by Atiq Ur Rehman (8843024)

“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”