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  1. 361

    Efficacy of a Metal Artifact Reduction Algorithm in CBCT Images of Teeth With Ceramic Brackets With/Without Coated Archwires: An In Vitro Study by Parisa Soltani, Mariangela Cernera, Marzie Kachuie, Amirhossein Moaddabi, Mehran Khoramian, Gianrico Spagnuolo, Niccolò Giuseppe Armogida, Carlo Rengo

    Published 2025-02-01
    “…ABSTRACT Objective This study aimed to assess the efficacy of a metal artifact reduction (MAR) algorithm for cone‐beam computed tomography (CBCT) scans of teeth with ceramic brackets with/without coated archwires. …”
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  2. 362
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    Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm by Yunhe Shi, Xiaofei Zhang, Shengxinlai Han

    Published 2025-02-01
    “…The virtualization of the array further increases the available DOFs, while the hole-filling strategy ensures better spatial coverage and continuity. On the algorithmic side, we introduce a dimensionality-reduction root MUSIC algorithm tailored for uniform planar arrays after virtualization. …”
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  4. 364

    Metal artifact reduction combined with deep learning image reconstruction algorithm for CT image quality optimization: a phantom study by Huachun Zou, Zonghuo Wang, Mengya Guo, Kun Peng, Jian Zhou, Lili Zhou, Bing Fan

    Published 2025-06-01
    “…Background Aiming to evaluate the effects of the smart metal artifact reduction (MAR) algorithm and combinations of various scanning parameters, including radiation dose levels, tube voltage, and reconstruction algorithms, on metal artifact reduction and overall image quality, to identify the optimal protocol for clinical application. …”
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    Article
  5. 365

    Unleashing Predicting a Comparative Study of Machine Learning for Bankruptcy Risk Prediction by Yupeng Li, Ke Sun

    Published 2024-03-01
    “…Predictive analytics are advanced through the utilization of sophisticated machine learning methodologies, specifically the Random Forest classification model (RFC), The Grasshopper Optimizer Algorithm (GOA), and the Artificial Rabbits Optimizer (ARO). …”
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    Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning by Wangsong Xie

    Published 2022-01-01
    “…With the gradual integration of global economy and finance, the financial market presents many complex financial phenomena. To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm. …”
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    Prediction of Imbalance Prices Through Gradient Boosting Algorithms: An Application to the Greek Balancing Market by Konstantinos Plakas, Nikos Andriopoulos, Dimitrios Papadaskalopoulos, Alexios Birbas, Efthymios Housos, Ioannis Moraitis

    Published 2025-01-01
    “…In the first stage, the quantiles of system imbalance are predicted employing the Quantile Regression Forest algorithm. …”
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    Review of Modular Multiplication Algorithms over Prime Fields for Public-Key Cryptosystems by Hai Huang, Jiwen Zheng, Zhengyu Chen, Shilei Zhao, Hongwei Wu, Bin Yu, Zhiwei Liu

    Published 2025-06-01
    “…Furthermore, the core concepts, implementation challenges, and research advancements of multiplication algorithms are systematically summarized. This paper also gives a brief overview of modular reduction algorithms for various types of moduli and discusses the implementation principles, application scenarios, and current research results. …”
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  17. 377

    Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

    Published 2025-12-01
    “…This study investigates and predicts the likelihood of operational risk occurrence in the banking industry using machine learning algorithms. …”
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    Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms by Milad Shahvaroughi Farahani

    Published 2021-03-01
    “…Thus, if you can forecast the interest rate, you can predict the parallel markets too. The main goal of this article, as it is clear from the title, is the prediction of interest rate using ANN and improving the network using some novel heuristic algorithms such as Moth Flame Optimization algorithm (MFO), Chimp Optimization Algorithm (CHOA), Time-varying Correlation Particle Swarm Optimization algorithm (TVAC-PSO), etc. we used 17 variables such as oil price, gold coin price, house price, etc. as input variables. …”
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