StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…The proposed StackDPPred method improves the overall accuracy by 13.41% and 7.62% compared to existing DPs predictors iDPF-PseRAAC and iDEF-PseRAAC, respectively on validation test. Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”

Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

“…The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For image datasets, we employ Multi-Level Autoencoders, consisting of Convolutional and Fully Connected Autoencoders. …”

Blockchain-Based Decentralized Architecture for Software Version Control by Muhammad Hammad (17541570)

“…The proof of authority (PoA) consensus algorithm will be used to approve the developer communicating modifications to the private blockchain network; the authority will only provide permission and will not be able to add, edit, or delete code files. …”

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology by Ajay Vikram Singh (204056)

“…As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. …”

Synthesis with VHDL. (c2001) by Halawi, Hatem

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

“…PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. …”

An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…Several metaheuristics, such as the Genghis Khan Shark Optimizer Algorithm (GKSO), can assist in optimizing the FS issue. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”

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

“…To accomplish such a feat, four user-specific methods were developed, implemented, and tested; all of which were based on a benchmark database created by the authors. …”

UML-based regression testing for OO software by Mansour, Nashat

“…For the second phase, we present algorithms for detecting system level changes in the interaction overview diagram. …”
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The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis by Ghada Al-Hussain (18295426)

“…Both methods have limited standardized tests, which are affected by the clinician’s experience and subjective judgment. …”

A novel design technique for generating building form by KAYED, MAYS N. A.

“…The theoretical framework of the technique was successfully tested out and validated by implementing it over serious of examples that are categorized into three groups: examples directed to test out the proposed variables in each process, examples directed to validate the ability of whole technique to generate forms for a hypothetical project requirements and examples of scripting the mechanisms using the algorithmic editor interface and the visual programming language Grasshopper incorporated with Rhinoceros 3D software."…”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. This model can be used in a clinical setting as a decision support system or for public health awareness as an informal risk prediction system. …”
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Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

“…The results suggest that the proposed algorithm, the optimal Kalman filter, performs better than the other two in all tests performed.…”
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Scheduling and allocation in high-level synthesis using stochastic techniques by Sait, Sadiq M.

“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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Parametric Design Optimization in Sustainable Urban Design: In Hot Climate by Musleh, Mousa A. M.

“…The application of suggested methodologies on real life case put it under test to evaluate its viability, precise of prediction and the outcome benefits to the practical current urban design processes. …”
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Extreme Early Image Recognition Using Event-Based Vision by Abubakar Abubakar (18278998)

“…<p dir="ltr">While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. …”

Modeling and Bias-Robust Estimation of the Acoustic Release of Chemotherapeutics from Liposomes by Wadi, Ali

“…The noise structure affecting the process dynamics and the measurement process is then identified in terms of the statistical covariance of the measured quantities. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. …”
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