Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …"

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…In our research, we introduce a comprehensive approach to Arabic poetry text classification using deep learning techniques. We have used an almost one-million record dataset of Arabic poetry verses extracted from a poetry encyclopedia. …"
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Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique حسب Iqbal Hassan (22155274)

"…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …"

An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure حسب Fahmy, Ahmed

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Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks حسب Sharma, Neetan

"…The proposed ANN based algorithm has been used for unswerving petite term forecasting. …"
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HVAC system attack detection dataset حسب Mariam Elnour (14147790)

"…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…"

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review حسب Avneet Kaur (712349)

"…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …"

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma حسب 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. …"

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain حسب Farshad Rahimi Ghashghaei (20880995)

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features حسب Mariam Bahameish (19255789)

"…<p dir="ltr">Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. …"

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images حسب Rehan Raza (17019105)

A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation حسب Kfouri, Ronald

"…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …"
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach حسب Muhammad Adeel Asghar (6724982)

"…A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. …"

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test حسب Hasan T. Abbas (8115014)

"…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …"

Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems حسب Khaled Dhibi (16891524)

"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network حسب Fares Almomani (12585685)

"…The developed model can be used to forecast the CMP as a function of operating temperature, the substrate composition, and chemical dose, and can be used for scaling-up and cost analysis purposes.…"

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context حسب SALIM, MAHA JAWDAT

"…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …"
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Can AI Help in Screening Viral and COVID-19 Pneumonia? حسب Muhammad E. H. Chowdhury (14150526)

Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles حسب Zainab Akhtar (15192184)

"…The MLNN observer, employing a modified back-propagation algorithm, is used for the quadrotor’s state estimation. …"

Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review حسب Rehaan Hussain (22302742)

"…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …"