Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. …”

Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
Get full text
Get full text

Design and development of an embedded controller for roboticmanipulator by Bakhashwain, J.M.

“…Mohseni's Proposed Algorithm, MPA, has been incorporated into the embedded controller to reduce the computational efforts and to obtain a close-to-optimal control law. …”
Get full text
Get full text

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…After selecting the most appropriate lattice map (32 × 32) in 750,000 iterations using SOMs, the data points below the dark blue region are mapped onto the data frame to get the videos. …”

Corrosion Monitoring Technologies for Reinforced Concrete Structures: A Review by SHEHADEH, KHADIJA

“…Irrespective of the adopted processes for corrosion monitoring, it was concluded that none of these methods represent an optimum solution by itself, where employing a combination of multiple systems is one way of optimizing its results. New technology, algorithms, data processing, and AI are new approaches to improving corrosion monitoring processes. …”
Get full text

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

“…We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. …”
Get full text
Get full text
Get full text
Get full text

FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…The results of the conducted experiments indicate that random forest outperforms other algorithms achieving a maximum accuracy of 98.5% and an F-score of 0.932. …”
Get full text

Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…Nonetheless, several operations based on the structure of XML data have not yet received strong attention. Among these is the process of matching XML documents with XML grammars, useful in various applications such as documents classification, retrieval and selective dissemination of information. …”
Get full text
Get full text
Get full text
Get full text

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…Finally, the algorithm is employed in a CO₂ capture case study to generate and select the best-performing novel ILs, which exhibit behavior consistent with established ILs in the literature.…”

Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing by Zabin, Asem Ahmad

Get full text

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…Statistical analysis showed that the selected features for liquids' and pipe's properties using the BGWOPSO algorithm were adequate to attain superior performance for both models. …”

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…Due to the complexity of Arabic poetry such as the excessive use of metaphors, figurative language, unlimited imagination, and the diversity of styles from one poet to another and from one poem to another, we tackle these challenges by careful employment of preprocessing steps, feature engineering and selection. We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …”
Get full text

Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
Get full text

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

“…Artificial intelligence (AI), with its ability to process vast amounts of data and detect intricate patterns, offers a solution to the limitations of traditional mammography, including missed diagnoses and false positives. …”

Inertial Navigation system of In-pipe Inspection Robot by Al-Masri, Wasim

Get full text

A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…Four online databases, including Web of Science, Scopus, Google Scholar, and Science Direct, were used to screen articles. Study selection, quality assessment, and data extraction were performed independently by four authors. …”

Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries by Assayed, Suha Khalil

Get full text
Get full text

Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19 by Hibah Shaath (5599658)

“…Herein, we employed iterative clustering and guide-gene selection 2 (ICGS2) as well as uniform manifold approximation and projection (UMAP) dimensionality reduction computational algorithms to decipher the complex immune and cellular composition of BAL, using publicly available datasets from a total of 68,873 single cells derived from two healthy subjects, three patients with mild COVID-19, and five patients with severe COVID-19. …”

Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

“…Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. To address this research gap, we collect a total of 197,566 comments from four platforms: YouTube, Reddit, Wikipedia, and Twitter, with 80% of the comments labeled as non-hateful and the remaining 20% labeled as hateful. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
Get full text
Get full text
Get full text