Optimal shunt compensators at nonsinusoidal busbars by El-Amin, I.M.

“…The Direct Search Polytope algorithm is used. The solution of this model yields an optimal shunt LC compensator for the nonlinear load. …”
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Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet by Vineet Dhanawat (22361395)

“…To guarantee accuracy and uniformity, the data is preprocessed by addressing missing values and ensuring consistency. …”

Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam Eljilany (14151588)

“…The cost of the algorithm was the cost of the genotyping assay. The model event probability inputs were extracted from major literature clinical trials, and the setting-specifc and cost inputs were locally obtained. …”

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

“…Yet, most of them do not capture the semantic meaning embedded in online social media data, which are usually highly heterogeneous and unstructured, and do not identify event relationships (e.g., car accident temporally occurs after storm, and geographically occurs near soccer match). …”
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OPTIMAL SHUNT COMPENSATORS AT NON-SINUSOIDAL BUSBARS by El-Amin, I.M.

“…The Direct Search Polytope algorithm is used. The solution of this model yields an optimal shunt LC compensator for the nonlinear lend. …”
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Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

“…This made finding certain text classification algorithms that fit a specific language or a set of languages a difficult task for researchers. …”
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Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges by Muhammad Mohsin Khan (22303366)

“…It made it possible for healthcare professionals to understand AI-driven recommendations, by this means increasing transparency and trust. Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. …”

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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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…In future, other neural network algorithms such as the RNN, LSTM will be implemented, and Arabic tweets will be included in the future.…”
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Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Computation of conformal invariants by Mohamed M.S. Nasser (16931772)

“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”

Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…The main task is to detect changes in data distribution that might cause changes in the decision bound aries for a classification algorithm. Upon drift detection, the classifica tion algorithm may reset its model or concurrently grow a new learning model. …”
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A combinatorial auction‐based approach for ridesharing in a student transportation system by Chefi Triki (14158860)

“…Three meta-heuristics, namely particle swarm optimization, dragonfly algorithm, and imperialist competitive algorithm, are implemented in the proposed framework, whose performances are assessed and compared. …”

Toward automatic motivator selection for autism behavior intervention therapy by Siyam, Nur

“…We use a Q-learning algorithm to solve the modeled problem. Our proposed solution is then implemented as a mobile application developed for special education plans coordination. …”
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A PLC based power factor controller for a 3-phase induction motor by Al-Ali, A.R.

“…This work focuses on the implementation of a laboratory model for a PLC based PFC to improve the power factor of a three-phase induction motor. …”
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Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... by Tarik Elhadd (5480393)

“…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…”

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method by Mohamed Massaoudi (16888710)

“…The proposed model is thoroughly assessed through an empirical study using a real data set from Australia. The simulation results confirm the performance superiority of the proposed model over the existing forecasting models with the lowest average root mean square error and mean absolute percentage error of 3.88kW and 2.30%, respectively.…”

PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…In future, other neural network algorithms such as the RNN, LSTM will be implemented, and Arabic tweets will be included in the future.…”
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study by Masurkar, Faeez

“…Fifth, it is also observed that the actuation and sensing position plays a crucial role in receiving the time-domain data with a sufficient SNR and the one that is easy to analyze and interpret. …”
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…An ANN model consists of three layers, 15 neutrons and 260 <i>epochs</i> accurately predict the CMP with 99.1% of data within ±10% deviation of the mean experimental value. …”