Reputation-based cooperative detection model of selfish nodes in cluster-based QoS-OLSR protocol. (c2014) by Moati, Nadia

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

“…These impractical predictions would compromise the scheduling and control decisions made based on them. …”

Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

“…The novel LSTM time series algorithm proved to work best for demand forecasting. …”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…To categorize electronic text in these two cases, deep learning models such as convolutional neural networks and recurrent neural networks and a combination of CNN-RNN were trained on this data. …”
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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Structural similarity evaluation between XML documents and DTDs by Tekli, J.

“…The automatic processing and management of XML-based data are ever more popular research issues due to the increasing abundant use of XML, especially on the Web. …”
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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
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Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3 by Chakar, Joseph

“…We also explore variational dropout: a technique that finds individual and unbounded dropout rates for each neural network weight. …”
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A survey and comparison of wormhole routing techniques in a meshnetworks by 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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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This research highlights the ability of AI to develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts. …”

A comparative analysis to forecast carbon dioxide emissions by Md. Omer Faruque (17545671)

“…Based on multivariate time series prediction, four deep learning algorithms are analyzed in this work, those are convolution neural network (CNN), CNN long short-term memory (CNN–LSTM), long short-term memory (LSTM), and dense neural network (DNN). …”

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. …”

Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…Hence, there is a great need to automate this process. In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. …”
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The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…Identifying semantic implication between similar queries (if a user searches for the images containing a car, he would probably mean auto, vehicle, van or sport-car as well) will improve the fragmentation process. …”
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Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…A dataset generated by a digital learning platform used by a private school in Jordan is utilised. Various ML algorithms, such as Support Vector Machines, Logistic Regression, K-Nearest Neighbors, Naïve Bayes, Decision Trees, Random Forest, AdaBoost, Bagging, and Artificial Neural Networks are applied to predict student performance. …”
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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. …”