Predicting COVID-19 cases using bidirectional LSTM on multivariate time series حسب 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. …"

Process Mining over Unordered Event Streams حسب Awad, Ahmed

"…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …"
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Anomaly Detection Based Framework for Profile Monitoring حسب Al-Rahim, Nour Al-Huda Z. Al-Abed

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A novel few shot learning derived architecture for long-term HbA1c prediction حسب Marwa Qaraqe (10135172)

"…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …"

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

"…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO₂ solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO₂ absorption capacity. …"

Active distribution network type identification method of high proportion new energy power system based on source-load matching حسب Qinlin, Shi

"…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …"
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test حسب Hasan T. Abbas (8115014)

"…We trained and validated the models using the OGTT and demographic data of 1,492 healthy individuals collected during the San Antonio Heart Study. …"

An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation حسب Abdul Rahman, Sawsan

"…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …"
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A survey and comparison of wormhole routing techniques in a meshnetworks حسب Al-Tawil, K.M.

"…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …"
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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks حسب Daou, Leonardo

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Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet حسب Vineet Dhanawat (22361395)

"…The model’s hyperparameters are optimized using an Enhanced Firefly Algorithm (EFA). …"

Generic metadata representation framework for social-based event detection, description, and linkage حسب Abebe, Minale A.

"…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …"
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Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review حسب Alaa Abd-alrazaq (17058018)

"…The most commonly used category of data for model development was physical activity data, followed by sleep data and heart rate data. …"

Novel RFID-Based Pose Estimation Using Single Stationary Antenna حسب Saab, Samer S.

"…Our scheme is based on power map matching algorithm that is capable in estimating the location and orientation of objects. …"
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Estimation of power grid topology parameters through pilot signals حسب Hargossian, H.

"…Pilot voltage stimulations are injected from distributed generators and the induced currents effects are measured at several nodes in the system. The measured data is evaluated through correlation, and a weighed least-square algorithm, applied to the network’s dynamic model, estimates those unknown parameters and provides an accurate snapshot of the power network topology. …"
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Investigation of Forming a Framework to shortlist contractors in the tendering phase حسب DABASH, MOHANNAD SALAH

"…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …"
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Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care حسب Regina Padmanabhan (14231606)

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

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

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Collaborative Caching for D2D Content Sharing in 5G حسب Abdelsalam, Ansam Elfadil Kamel

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Joint computing, communication and cost-aware task offloading in D2D-enabled Het-MEC حسب Abbas, Nadine

"…Furthermore, we propose a low-complexity algorithm that generates high performance results and can be applied for large-scale networks. …"
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