Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …”
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An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…Textual data contains much useless information that must be pre-processed. …”

Bee colony algorithm for assigning proctors to exams. (c2013) by Taha, Mohamad Kassem

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

“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

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

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

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The buffered work-pool approach for search-tree based optimization algorithms by Abu-Khzam, Faisal N.

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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

“…The classification technique has the unique feature of cutting down the computation largely by only allowing the event of interest to be executed by a particular algorithm. The set-up was also tested with random signals from a 137Cs test source. …”
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I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams by Raun, Kristo

“…This paper introduces a new approximate algorithm – I Will Survive (IWS). The algorithm utilizes the trie data structure to improve the calculation speed, while remaining memory-efficient. …”
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An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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Education Data Mining to Predict Student Exam Grades in Vocational Institutes by Saleh, Ashjan Ahmad

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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining by Alqaryouti, Omar

“…An integrated web application is developed to mock up the end-to-end process in ecommerce. Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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Heuristic Algorithm for Obtaining Approximate Optimum Stratification With Mixture of Ratio and Product Estimators by S. E. H. Rizvi (22052105)

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

“…In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes mellitus (T2DM). Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …”