Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic حسب Saeed Al-Maroof, Rana

"…The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. …"
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Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning حسب Mohamed Elhadary (16329082)

"…With the significant advancements in machine learning (ML) and artificial intelligence (AI) in recent years, numerous models and algorithms have been proposed to support the diagnosis and classification of CLL. …"

Creating and detecting fake reviews of online products حسب Joni Salminen (7434770)

"…Using the better model, GPT-2, we create a dataset for a classification task of fake review detection. …"

HVAC system attack detection dataset حسب Mariam Elnour (14147790)

"…Given the limitations on accessing a real HVAC system for research purposes and the unavailability of public labeled datasets to investigate the cybersecurity of HVAC systems, this paper presents a dataset of a 12-zone HVAC system that was collected from a simulation model using the Transient System Simulation Tool (TRNSYS). …"

Machine Learning Techniques for Pharmaceutical Bioinformatics حسب SULTAN, AHMED ATTA AHMED

"…In this matrix, each drug is represented by a vector of attributes from all other drugs. A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. …"
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Behavior-Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter حسب Saleh Alhazbi (16869960)

"…Based on these features, we developed four classification models to identify political troll accounts, these models are based on decision tree, random forest, Adaboost, and gradient boost algorithms. …"

Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads حسب Yazdavar, Ameen H.

"…The intermittent natures of loads and renewable DGs are modelled probabilistically. The effectiveness of the proposed planning approach has been validated using the PG&E 69-bus system, and the followings are observed: 1) the significance of applying suitable fundamental-power-flow and harmonic-power-flow algorithms for isolated microgrids, and 2) the possibility of avoiding a severe voltage distortion by utilizing an appropriate planning method and only small increase in the cost.…"
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Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose حسب 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. …"

Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties حسب AbdulGhafour, Husaen

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Transformations for Variants of the Travelling Salesman Problem and Applications حسب Assaf, Mustafa Jamil

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ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks حسب Muhammad Asif Khan (7367468)

"…Recently, cognitive network architectures using sophisticated learning techniques are increasingly being applied to such problems. …"

Artificial Intelligence for Assessing the Correlation Between Sleep Apnoea and Comorbidities حسب Ramesh, Jayroop

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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach حسب Mohammad Taghi Dabiri (16904658)

"…We then formulate the problem for UAV trajectory to minimize the maximum outage probability (OP) of directional THz links. Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …"

A Machine Learning Approach to Predicting Diabetes Complications حسب Jian, Yazan Khaled

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Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters حسب Farhan, Abid

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging حسب Maricar, Mohammed Farook

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Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review حسب Hiba Alzoubi (18001609)

"…</p><h3>Objective</h3><p dir="ltr">This systematic review evaluates the performance of AI models in detecting and subtyping medulloblastomas using histopathological images. …"

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases حسب Muhammad Ali Muzammil (17910611)

"…To guarantee a safe and successful deployment in clinical practice, the use of AI in cardiology must be done with a thorough understanding of the algorithms and their limits. …"

Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review حسب Loay A. Salman (14150322)

"…All included studies were published between 2021 and 2022, with a total of nine different AI algorithms reported. Among these AI models, the accuracy of TKA femoral component sizing prediction ranged from 88.3 to 99.7% within a deviation of one size, while tibial component sizing exhibited an accuracy ranging from 90 to 99.9% ± 1 size.…"