Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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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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An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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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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Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Education Data Mining to Predict Student Exam Grades in Vocational Institutes by Saleh, Ashjan Ahmad

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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Approximation and heuristic algorithms for computing backbones in asymmetric ad-hoc networks by Abu-Khzam, Faisal N.

“…We consider the problem of dominating set-based virtual backbone used for routing in asymmetric wireless ad-hoc networks. …”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²), were used to assess the prediction accuracy of the models. The results of the correlation matrices showed that the blueberry yield and losses (leaf loss, blower loss) had medium to strong correlations accessed based on the correlation coefficient (r) range 0.37–0.79. …”

On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”

A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

“…In certain situations, the requirement for clusters to be cliques was deemed excessively stringent, leading to the proposal of alternative relaxed clique models for dense subgraphs, such as s-club. In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle by Wadi, Ali H M

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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). …”

Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

“…The data was used as training and testing sets to analyze certain machine learning algorithms in terms of performance (cost / benefit analysis) and accuracy (mean error square and confusion matrix). …”
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Heuristic Algorithm for Obtaining Approximate Optimum Stratification With Mixture of Ratio and Product Estimators by S. E. H. Rizvi (22052105)

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. …”