Innovative mobile E-healthcare systems by Haraty, Ramzi A.

“…Caching is one of the key methods in distributed computing environments to improve the performance of data retrieval. To find which item in the cache can be evicted and replaced, cache replacement algorithms are used. …”
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Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

“…The XGboost algorithm is suggested from 10-fold cross-validation on 6 candidate models. …”

Indoor Localization Schemes for Mobile Robots by Al-Jarrah, Islam Mohammad-Amin

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

“…The automatic processing and management of XML-based data are ever more popular research issues due to the increasing abundant use of XML, especially on the Web. …”
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Here, the Quantized Identical Data Imputation (QIDI) mechanism is implemented at first for data preprocessing and normalization. …”

Predicting COVID-19 cases using bidirectional LSTM on multivariate time series by Ahmed Ben Said (14158926)

“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.…”

Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”

CEAP by Abdel Wahab, Omar

“…To reduce the overhead of the proposed detection model and make it feasible for the resource-constrained nodes, we reduce the size of the training dataset by (1) restricting the data collection, storage, and analysis to concern only a set of specialized nodes (i.e., Multi-Point Relays) that are responsible for forwarding packets on behalf of their clusters; and (2) migrating only few tuples (i.e., support vectors) from one detection iteration to another. …”
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Automated skills assessment in open surgery: A scoping review by Hawa Hamza (17707224)

“…We highlight the progress in automated skills assessment during open surgery with advancements in sensor technology, and AI algorithms with high prediction accuracies. Further developments in data acquisition and processing methods are essential to facilitate clinical implementation of such technologies.…”

Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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Optimizing ADWIN for Steady Streams by Moharram, Hassan

“…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…Pre-processing is a vital part of the data preparation process for cyberbullying detection. …”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”

Evacuation of a highly congested urban city by El Khoury, John

“…As the evacuation route planning is computationally challenging, an evacuation scheduling algorithm was adopted to expedite the solution process. …”
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Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…For sentiment analysis, pre-processing is a crucial step in the data preparation process. …”
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Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…Existing methods are either applicable only to data with limited observation errors, work only for partially shuffled data, sensitive to initialization, and/or work only with small dimensions. …”
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