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

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

“…Gamma pulses from a 3" Na(TI) scintillation detector were captured as single and double pulses for the purpose of testing the peak detection algorithms. The pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor yielding a reduction of the execution time to 2 msec…”
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A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

“…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
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Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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Heuristic Algorithm for Obtaining Approximate Optimum Stratification With Mixture of Ratio and Product Estimators by S. E. H. Rizvi (22052105)

Heat rate curve approximation for power plants without data measuring devices by Poullikkas, Andreas

“…In this work, a numerical method, based on the one-dimensional finite difference technique, is proposed for the approximation of the heat rate curve, which can be applied for power plants in which no data acquisition is available. Unlike other methods in which three or more data points are required for the approximation of the heat rate curve, the proposed method can be applied when the heat rate curve data is available only at the maximum and minimum operating capacities of the power plant. …”
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A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates by Andrianarison, O.

“…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
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BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”

Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

“…In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation by Ashhadul Islam (16869981)

“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”

KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…Several techniques have been proposed in the literature to add some semblance of balance to the data sets by adding artificial data points. Synthetic Minority Oversampling Technique(SMOTE) and Adaptive Synthetic Sampling(ADASYN) are some of the commonly used techniques to deal with class imbalance. …”

Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data by ODEH, HANEEN

“…In today's evolving educational arena, Adaptive learning experiences to individual needs has become a focal point. The Experience API (xAPI) provides a comprehensive mechanism to document all types of learning interactions, storing this stream of data into the Learning Record Store (LRS). …”
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A Secure and Decentralized Blockchain Based EV Energy Trading Model Using Smart Contract in V2G Network by Atif Iqbal (5504636)

Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study by Mutasim Baba, Fuad

“…It was found that the calibrated model achieved these metrics with RMSE of 0.3 ◦C, and MAD of 0.8 ◦C, and 85% of data points with an error less than 0.5 ◦C for a school building case.…”
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Semantic based navigation and lane keeping by Abdeen, Abdallah Adel

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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications by Estahbanati, Shahabeddin Vamegh

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…A total of eleven hundred experimental data points for nine FPs (two stratified and seven dispersed patterns) in horizontal wellbores are used to develop the MLs. …”

PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY by Noras, J.M.

“…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 pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor to give an execution time down to 2 msec.…”
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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