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A quantum multiplier based on the quantum Fourier transform algorithm
Published 2022-03-01Get full text
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A Note on the Cowles-EM Algorithm for Bayesian Ordinal Probit Models
Published 2024-12-01Get full text
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84
Use of hybrid quantum-classical algorithms for enhancing biomarker classification.
Published 2025-01-01“…Our study addresses the need for improved execution time and accuracy in QSVC and QNN algorithms compared to SVC and NN for binary classification. …”
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Image encryption algorithm based on improved Clifford chaotic system
Published 2022-06-01Get full text
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Efficient Big Integer Multiplication and Squaring Algorithms for Cryptographic Applications
Published 2014-01-01“…Improving the efficiency of public-key cryptosystem through speeding up calculation and using fewer resources are among the main goals of cryptography research. In this paper, we introduce new symbols extracted from binary representation of integers called Big-ones. …”
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Classification Algorithms for Early Tooth Demineralization Assessment by Impedance Spectroscopy
Published 2025-05-01Get full text
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Predicting Voluntary Auditor Change Using the Water Cycle Algorithm
Published 2024-06-01“…In this regard, the purpose of this research is to predict voluntary auditor change (non-continuation of the relationship with the current client) using a meta-heuristic algorithm (Water Cycle Algorithm, WCA) and to compare the results with the logistic regression method.MethodsThe statistical sample is 185 companies listed on the Tehran Stock Exchange, selected by the systematic elimination method from 2017 to 2023, and their information was collected. …”
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Analyzing cryptographic algorithm efficiency with in graph-based encryption models
Published 2025-07-01“…Consequently, this research conducts a comparative analysis of RSA and ElGamal cryptographic algorithms by applying them to mixed data, including binary, text, and image files. …”
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Investigating the contributory factors influencing speeding behavior among long-haul truck drivers traveling across India: Insights from binary logit and machine learning technique...
Published 2024-12-01“…While conventional statistical methods like binary logit technique lacked prediction capabilities, machine learning (ML) algorithms including decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost) were employed to model speeding behavior among LHTDs. …”
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Digital Art Feature Association Mining Based on the Machine Learning Algorithm
Published 2021-01-01“…The research scope is set in the field of digital art, and all kinds of accidental factors of digital art creation based on the machine learning algorithm are mined and analyzed for feature correlation. …”
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Sustainable Selection of Machine Learning Algorithm for Gender-Bias Attenuated Prediction
Published 2025-01-01“…As the vast dataset for engineering rules, standards and experiments are based on men, a bias towards women is the subject of research. Accordingly, any bias should be contained before the algorithms are deployed to the service of the sustainable society. …”
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Optimizing Data Filtering in Multi-Armed Bandit Algorithms for Reinforcement Learning
Published 2025-01-01“…The algorithms were evaluated in static and dynamic environments using the MovieLens dataset and transferred to binary rewards to measure performance. …”
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Two-Step Quantum Search Algorithm for Solving Traveling Salesman Problems
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Brain Computer Interface using Genetic Algorithm with modified Genome and Phenotype Structures
Published 2023-08-01“…The human machine interface research in the light of modern fast computers and advanced sensors is taking new heights. …”
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Genetic algorithm-based active noise control systems - simulations using Internet
Published 2004-01-01Get full text
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Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis
Published 2025-06-01Get full text
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Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks
Published 2024-11-01“…From the study result, it can be conclude that the Decision Tree algorithm performs better in detecting anomalies in binary data with an accuracy of 99,71%. …”
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