Choosing Improved Initial Values for Polynomial Zerofinding in Extended Newbery Method to Obtain Convergence by Saeid Saidanlu, Nor’aini Aris, Ali Abd Rahman

“…In all polynomial zerofinding algorithms, a good convergence requires a very good initial approximation of the exact roots. …”
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Advancing UAV Communications: A Comprehensive Survey of Cutting-Edge Machine Learning Techniques by Chenrui Sun, Gianluca Fontanesi, Berk Canberk, Amirhossein Mohajerzadeh, Symeon Chatzinotas, David Grace, Hamed Ahmadi

“…Finally, the use of state-of-the-art ML algorithms in these capabilities is explored and their potential extension to cloud and/or edge computing based network architectures is highlighted.…”
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3D Gravity Modeling of Complex Salt Features in the Southern Gulf of Mexico by Mauricio Nava-Flores, Carlos Ortiz-Aleman, Mauricio G. Orozco-del-Castillo, Jaime Urrutia-Fucugauchi, Alejandro Rodriguez-Castellanos, Carlos Couder-Castañeda, Alfredo Trujillo-Alcantara

“…By integrating results from different shape- and depth-source estimation algorithms, we built an initial model for the gravity anomaly inversion. …”
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Computational study of fluid forces over a cylinder attached with elastic beam: A finite element-based simulations by Yasir Arif, Rashid Mahmood, Mehdi Tlija, Afraz Hussain Majeed, Kamran Usman, Ehab Seif Ghith

“…In this paper, we describe numerical algorithms that can be used to solve the coupled fluid–structure interaction with incompressible viscous fluid. …”
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Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review by Arantxa Ortega-Leon, Daniel Urda, Ignacio J. Turias, Simón P. Lubián-López, Simón P. Lubián-López, Isabel Benavente-Fernández, Isabel Benavente-Fernández, Isabel Benavente-Fernández

“…In addition, we explore the potential of ML algorithms and discuss commonly used data sources, including clinical and neuroimaging data. …”
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Malignant Fibrous Histiocytoma of the Breast in Young Male Patient: A Case Report and a Review of the Literature by Esengul Kocak Uzel, Metin Figen, Tuba Tulin Bek, Kubilay Inanc, Senem Onder, Hazim orhan Kizilkaya

“…We believe that reporting such few cases would contribute to forming treatment algorithms of rare tumors.…”
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A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects by Isaac Kofi Nti, Juanita Ahia Quarcoo, Justice Aning, Godfred Kusi Fosu

“…The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the high number of free BDA tools, platforms, and data mining tools makes it challenging to select the appropriate one for the right task. …”
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A Study of Coupling Parameter Estimation Implemented by 4D-Var and EnKF with a Simple Coupled System by Guijun Han, Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, Ionel Michael Navon, Wei Li

“…It is found that both algorithms can improve the representation of air-sea coupling processes through CPE compared to state estimation only. …”
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Exploring Generative Adversarial Networks: Comparative Analysis of Facial Image Synthesis and the Extension of Creative Capacities in Artificial Intelligence by Tomas Eglynas, Dovydas Lizdenis, Aistis Raudys, Sergej Jakovlev, Miroslav Voznak

“…Neural networks have become foundational in modern technology, driving advancements across diverse domains such as medicine, law enforcement, and information technology. By enabling algorithms to learn from data and perform tasks autonomously, they eliminate the need for explicit programming. …”
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Reactive power optimization via deep transfer reinforcement learning for efficient adaptation to multiple scenarios by Congbo Bi, Di Liu, Lipeng Zhu, Chao Lu, Shiyang Li, Yingqi Tang

“…Existing reinforcement learning algorithms alleviate the computational complexity in optimization but suffer from the inefficiency of model retraining for different operating scenarios. …”
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Reliability Evaluation of NPP’s Power Supply System Based on Improved GO-FLOW Method by Jie Zhao, Tian Liu, Yu Zhao, Dichen Liu, Xiaodong Yang, Yi Lin, Zhangsui Lin, Yong Lei

“…Traditional GO-FLOW operators’ algorithms are improved. Comprehensively considering the effect of total signaling flow in the power supply system, the equivalent reliability parameter model and common cause failure probability model of multimodal repairable components are constructed. …”
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Effect of Feature Selection on the Prediction of Direct Normal Irradiance by Mohamed Khalifa Boutahir, Yousef Farhaoui, Mourade Azrour, Imad Zeroual, Ahmad El Allaoui

“…This paper aims to develop a set of deep learning models through feature importance algorithms to predict the DNI data. The proposed models are based on historical data of meteorological parameters and solar radiation properties in a specific location of the region of Errachidia, Morocco, from January 1, 2017, to December 31, 2019, with an interval of 60 minutes. …”
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Clustering and Investigation of Human Driving Behavior Using Autoencoder and Risk Assessment by Donghoon Shin, Jinhee Myoung, Woongsun Jeon, Kang-Moon Park

“…To address this, we utilize an autoencoder and human-centered risk assessment algorithms to investigate human driving behavior and collision risk. …”
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MAP: Mutation Arranger for Defining Phenotype-Related Single-Nucleotide Variant by In-Pyo Baek, Yong-Bok Jeong, Seung-Hyun Jung, Yeun-Jun Chung

“…Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. …”
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Impact of Loss Synchronization on Reliable High Speed Networks: A Model Based Simulation by Suman Kumar, Lin Xue, Seung-Jong Park

“…In particular, this paper aims to study the dynamic relationship between congestion control algorithms and queue management schemes, in order to develop a better understanding of the causal linkages between the two. …”
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An Improved Feature Selection Based on Effective Range for Classification by Jianzhong Wang, Shuang Zhou, Yugen Yi, Jun Kong

“…Therefore, IFSER outperforms the original ERGS and some other state-of-the-art algorithms. Experiments on several well-known databases are performed to demonstrate the effectiveness of the proposed method.…”
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A comprehensive review of remote sensing techniques for monitoring Ulva prolifera green tides by Xiaomeng Geng, Xiaomeng Geng, Xiaomeng Geng, Huiru Li, Huiru Li, Le Wang, Weidong Sun, Yize Li

“…Additionally, it identifies the limitations and unresolved challenges in current approaches, such as constraints on data resolution, algorithmic biases, and environmental variability. The potential for integrating multi-source remote sensing data with marine environmental parameters and deep learning techniques is discussed, emphasizing their roles in improving the accuracy and reliability of monitoring and predicting Ulva prolifera green tides. …”
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FORMALIZED EVALUATION OF SCENARIO DEVELOPMENT OF THE NATIONAL ECONOMY IN TERMS OF PENETRATION OF BLOCKCHAIN TECHNOLOGIES IN THE FINANCIAL SECTOR by M. R. Safiullin, A. A. Abdukaeva, L. A. Elshin, M. V. Savushkin

“…Having a very significant potential for transforming the established algorithms for the interaction of financial market participants, it is important to understand what are the boundaries of these changes, what new opportunities are presented by blockchain technologies and, finally, what are the expected consequences for the development of the financial sector itself and the other sectors of the national economic system associated with it. …”
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Condition Recognition of High-Speed Train Bogie Based on Multi-View Kernel FCM by Qi Rao, Yan Yang, Yongquan Jiang

“…Furthermore, the condition recognition rate of MvKFCM is higher than that of single-view and four other multiple-view clustering algorithms.…”
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A Hierarchical Framework for Selecting Reference Measures for the Analytical Validation of Sensor-Based Digital Health Technologies by Jessie P Bakker, Samantha J McClenahan, Piper Fromy, Simon Turner, Barry T Peterson, Benjamin Vandendriessche, Jennifer C Goldsack

“…However, the quality of the evidence reported for analytical validation of sDHTs—evaluation of algorithms converting sample-level sensor data into a measure that is clinically interpretable—is inconsistent and too often insufficient to support a particular digital measure as fit-for-purpose. …”
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