Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

Real-Time Path-Planning using Depth/INS Sensor Fusion for Localization by Alkhawja, Fares Amin E

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On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”

Transaction Dependency Based Approach for Database Damage Assessment Using a Matrix by Haraty, Ramzi Ahmed

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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. …”

Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning by MEZAHEM, FATEMA HAMAD

“…Prior to performing sentiment analysis, it is necessary to prepare the data so that it may be used to train machine learning (ML) algorithms. …”
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Mixed precision iterative refinement with adaptive precision sparse approximate inverse preconditioning by Noaman Khan (19810050)

“…<p dir="ltr">Hardware trends have motivated the development of mixed precision algorithms in numerical linear algebra, which aim to decrease runtime while maintaining acceptable accuracy. …”

What are artificial intelligence literacy and competency? A comprehensive framework to support them by Thomas K.F., Chiu

“…We also identify five effective learning experiences to foster abilities and confidences, and suggest five future research directions: prompt engineering, data literacy, algorithmic literacy, self-reflective mindset, and empirical research.…”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar by Sankaran Rajendran (14152830)

“…The performance of the algorithms was studied using WorldView-3 data, which provided the R2 values of 60% and the best suitability of the NDCI algorithm and MSI data to map the concentration of Chl-a. …”

The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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Logic-based Benders decomposition combined with column generation for mobile 3D printer scheduling problem by Tao Li (86810)

“…After analyzing the characteristics and structure of the model, a logic-based Benders decomposition algorithm framework is designed for solving this problem. …”

Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

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Using artificial intelligence to improve body iron quantification: A scoping review by Abdulqadir J. Nashwan (11659453)

“…The search revealed a wide range of machine learning algorithms used by different studies. Notably, most studies used a single data type. …”

Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids by Ahmed Ouammi (14151039)

“…<p>This paper presents a scheduling framework based algorithm for reducing/shaving the peak loads in a team of cooperating microgrids (TCM) powered smart buildings taking advantages of vehicle-to-building (V2B) concept and operational flexibilities of electric vehicles (EVs). …”

Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions by Yinsong Chen (16685508)

“…We also evaluate the strengths and limitations of the existing boundary issue solutions and discuss their applicability to different classification of decomposition-based models for wind power forecasting. This study will provide useful references for a wide range of future studies for developing accurate and practical wind power forecasting models.…”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”