Parallel implementation of clique partitioning using artificial neural networks. (c2000) حسب Hajj, Hisham

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Synthesis with VHDL. (c2001) حسب Halawi, Hatem

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Topics in graph algorithms حسب Abu-Khzam, Faisal Nabih

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On the periodic hierarchical Chinese postman problem حسب Muhammed Emre Keskin (19457413)

Human digital thought clones: the <i>Holy Grail</i> of artificial intelligence for big data حسب Jon Truby (14153022)

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling حسب Majed Hadid (17148364)

"…Therefore, this paper proposes a clustering and stochastic optimization methodology to handle the various challenges of OCA planning and scheduling. A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …"

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE حسب SHWEDEH, FATEN

"…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …"
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Stacking-based ensemble learning for remaining useful life estimation حسب Begum Ay Ture (17773170)

A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks حسب Umesh Kumar Lilhore (17727684)

"…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …"

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques حسب Ameema Zainab (16864263)

"…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…"

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method حسب Amit Kumar Balyan (18288964)

"…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"

Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"

Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning حسب Amer, Hala Nagi

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Evaluation of mortality attributable to SARS-CoV-2 vaccine administration using national level data from Qatar حسب Adeel A. Butt (3697705)

Data Generation for Path Testing حسب Mansour, Nashat

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BUC algorithm for iceberg cubes حسب Nasr, George E.

"…The Uniform distribution is used as a basis for comparison. Results show that when the cube is sparse there is a correlation between the data distribution and the running time of the algorithm. …"
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An enhanced quorum selection algorithm حسب Haraty, Ramzi A.

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An Improved Quorum Selection Algorithm حسب Haraty, Ramzi A.

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Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan حسب AL RAWASHDEH, HANEEN MOHAMMAD

"…Different classification algorithms were applied to the dataset using the Rapidminer tool. …"
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The use of multi-task learning in cybersecurity applications: a systematic literature review حسب Shimaa Ibrahim (22155739)

"…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …"