Accurate multiple network alignment through context-sensitive random walk by Hyundoo Jeong (3840013)

“…In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. …”

Design and Optimization of a Planar Cable Robot by Kassem, Mohamad Hassan

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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

“…Most of the studies used data sets with a size of <10,000 samples (32/47, 68%). Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …”

Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. …”
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Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”

Mobile Robot Trajectory Tracking Using Neural Networks by Mohareri, Omid

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Optimization metaheuristic for software testing by Mansour, Nashat

“…In our work, we model web applications by associating features or web pages with states; state transition diagrams are based on events representing state transitions. …”
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LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…We applied the SHAP algorithm to demonstrate the importance of most dominating features that were leveraged in the model. …”

Quality Degradation And Pricing of Perishable Food Products by Alastal, Haya

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Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

“…Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …”
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Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

“…A system architecture is designed for a cloud-based IoT framework to implement the proposed algorithm efficiently. …”

Computation of conformal invariants by Mohamed M.S., Nasser

“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”
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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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Dynamic adaptation for video streaming over mobile devices. (c2013) by Jalloul, Rayan A.

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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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Supervised term-category feature weighting for improved text classification by Attieh, Joseph

“…GradientDescentANN replaces the iterative additive process mentioned previously by computing the term-category matrix using a gradient descent ANN model. Training the ANN using the gradient descent algorithm allows updating the term-category matrix until reaching convergence. …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

“…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine by Shomope, Ibrahim

“…The type of algorithm employed to predict drug release from liposomes plays an important role in affecting the accuracy. …”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”