Quantifying day-to-day variations in 4DCBCT-based PCA motion models by Dhou, Salam

“…Motion models are built by 1) applying deformable image registration (DIR) on each 4DCBCT image with respect to a reference image from that day, resulting in a set of displacement vector fields (DVFs), and 2) applying principal component analysis (PCA) on the DVFs to obtain principal components representing a motion model. …”
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Telescopic Vector Composition and Polar Accumulated Motion Residuals for Feature Extraction in Arabic Sign Language Recognition by Shanableh, Tamer

“…In the second approach, motion is represented through motion residuals. The residuals are then thresholded and transformed into the frequency domain. …”
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Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study by Dhou, Salam

“…A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from four-dimensional cone-beam CT (4D-CBCT) images was developed. 4D-CBCT images acquired immediately prior to treatment have the potential to accurately represent patient anatomy and respiration during treatment. …”
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Developing Privacy Frameworks for Motion Sensor Data in Next-Generation Wearable Devices by Ahmed, Ragad Moustafa

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Spatio-Temporal Feature-Extraction Techniques for Isolated Gesture Recognition in Arabic Sign Language by Shanableh, Tamer

“…The prediction errors are thresholded and accumulated into one image that represents the motion of the sequence. The motion representation is then followed by spatial-domain feature extractions. …”
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Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images by Shanableh, Tamer

“…This results in a single image representation per sign language word referred to as a motion image. CNN transfer learning is used to convert each of these motion images into a feature vector which is used for either model generation or sign language recognition. …”
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The Design and Simulation of a Fuzzy Logic-Controlled Upper-body Exoskeleton for Lower-Limb Paraplegics Using Swing Through Gait Ambulation by Jad, Eid

“…The controller is designed to recreate the STG using a rigid body dynamics model with a fuzzy logic controller guiding the motion of the shoulders and elbows. …”
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Fluoroscopic 3D Images Generation Using A GAN Method by Alshrbaji, Mohammad Nabeel Mohammad

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Multichannel image identification and restoration using continuousspatial domain modeling by Al-Suwailem, U.A.

“…Using the maximum likelihood estimation (ML) approach, the image is represented as an autoregressive (AR) model and blur is described as a continuous spatial domain model. …”
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Modeling of oblique penetration into geologic targets using cavity expansion penetrator loading with target free-surface effects by Tabbara, Mazen R.

“…A procedure has been developed to represent the loading on a penetrator and its motion during oblique penetration into geologic media. …”
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GIS-BIM Based Regional Seismic Risk Assessment for Dubai, UAE by Maky, Ahmed Mansour

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Computational Fluid Dynamics Simulation of Gas–Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models by Ramin Khezri (12506474)

“…The turbulent model of RNG k-Ɛ was found to best represent the actual process. …”

Computational Fluid Dynamics Simulation of Gas–Solid Hydrodynamics in a Bubbling Fluidized-Bed Reactor: Effects of Air Distributor, Viscous and Drag Models by Ramin Khezri (12506474)

“…The turbulent model of RNG k-Ɛ was found to best represent the actual process. …”

Exploring the potential of onboard energy scavenging subsystems for generating valuable data by Raziq Yaqub (16488878)

“…This gathered data is seamlessly synchronized with GPS coordinates and timestamps, meticulously organized within a system architecture, and harnessed through meticulously crafted Python code. The wealth of data that we obtain from an onboard energy scavenging subsystem holds significant potential. …”

Multidimensional Risk-Based Real Options Valuation for Low-Carbon Cogeneration Pathways by Houd Al-Obaidli (19365520)

“…The trend and volatilities in the major principal component scores (the combined price risk indicator) were modelled using the geometric Brownian motion stochastic process, whose parameters were determined and then used to perform time-series simulation and generate multiple realisations of the principal component. …”

RDFFrames: knowledge graph access for machine learning tools by Aisha Mohamed (5152970)

“…<p>Knowledge graphs represented as RDF datasets are integral to many machine learning applications. …”

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

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Multi-IsnadSet MIS for Sahih Muslim Hadith with chain of narrators, based on multiple ISNAD by Aziz Mehmood Farooqi (20748788)

“…In this paper, four different tools were designed and constructed for modeling and analyzing narrative network such as python library (NetworkX), powerful graph database Neo4j and two different network analysis tools named Gephi and CytoScape. …”

Closed-form Exact and Asymptotic Expressions for the Symbol Error Rate and Channel Capacity of the H-function Fading Channel by Alhennawi, Husam R.

“…The derived exact expressions are given in terms of the univariate and multivariate Fox H functions for which we provide a portable and efficient Python code. Since the Fox's H-function fading channel represents the most generalized fading model ever presented in the literature, the derived expressions subsume most of those previously presented for all the known simple and composite fading models. …”
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COLOR IMAGE IDENTIFICATION AND RESTORATION by Al-Suwailem, Dr. Umar A.

“…In this paper we present a novel identification technique for multichannel image processing using the maximum likelihood estimation (ML) approach. The image is represented as an autoregressive (AR) model and blur is described as a continuous spatial domain model, to overcome some major limitations encountered in other ML methods. …”
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