Evolutionary algorithms for state justification in sequential automatic test pattern generation حسب 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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An image processing and genetic algorithm-based approach for the detection of melanoma in patients حسب 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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A method for optimizing test bus assignment and sizing for system-on-a-chip حسب 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 حسب 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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Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems حسب Tarek Berghout (16905132)

Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection حسب 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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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning حسب Far, Reza Davoodi

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Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development حسب Abdulqadir J. Nashwan (11659453)

"…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …"

A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates حسب 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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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm حسب Saima Hassan (14918003)

"…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …"

Deepfakes Signatures Detection in the Handcrafted Features Space حسب Hamadene, Assia

"…These synthetic databases contain synthetic genuine and forgeries specimens which are used to train and build signature verification systems. Researches on generative data assume that synthetic data are as close as possible to real data, this is why, they are either used for training systems when used for data augmentation tasks or are used to fake systems as synthetic attacks. …"
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Inertial Navigation system of In-pipe Inspection Robot حسب Al-Masri, Wasim

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

"…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. However, if the training data is not balanced among different classes, the performance of ML models deteriorate heavily. …"

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images حسب Ahila A (18394806)

"…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …"

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

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Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St... حسب Mohamed Elsayed Saad Aboudonya (18466385)

"…</p><h3>Results</h3><p dir="ltr">The descriptive and inferential data analysis (Table 1) reflected that four out of the seven KPIs had a significant improvement after conducting the training program.…"

Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators حسب Abu Zitar, Raed

"…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …"
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms حسب Md Ferdous Wahid (13485799)

"…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …"

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control حسب Farhat Mahmood (15468854)

"…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …"

Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques حسب Fares, Samar

"…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …"
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