Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

Convergence behavior of the normalized least mean fourth algorithm by Zerguine, A.

“…Sufficient conditions for the NLMF algorithm convergence in the mean are obtained and the analysis of the steady-state performance is carried out using the feedback approach. …”
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A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS by Zerguine, Azzedine

“…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”

Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…Among these, K-means is widely used for efficiently solving clustering problems. …”
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A Survey of Data Clustering Techniques by Sobeh, Salma

“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

Convergence and steady-state analysis of the normalized least mean fourth algorithm by Zerguine, Azzedine

“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”

Convergence and steady-state analysis of the normalized least mean fourth algorithm by Zerguine, Azzedine

“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models by Asan G. A. Muthalif (16888818)

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

“…The data embedding algorithm guarantees that a maximum of one partition is modified per message segment, therefore, in a given CU, either 0, 1 or 2 partitions are modified. …”
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Using Data Mining in CRM to Understand the Insurance Market by Qadadeh, Wafa

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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

“…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”

Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …”
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Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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