Vehicle Pose Estimation Method Based on Maximum Correntropy Square Root Unscented Kalman Filter by Shuyu Liu, Ying Guo

“…The method first generates an estimate of the predicted state and covariance matrix through the Unscented Transform (UT), and then obtains the square root matrix of the covariance through Cholesky and QR decomposition to replace the original covariance, effectively preserving the positive definiteness of the covariance and improving the accuracy of the algorithm. …”
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Analysis of signals from air conditioner compressors with ordinal patterns and machine learning by Keila Barbosa, Alejandro C Frery, George DC Cavalcanti

“…Integrating machine learning methods with a symbolic transformation offers a robust approach for the early and accurate diagnosis of potential failures, enhancing the predictive maintenance of air conditioning equipment.…”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…This study proposes a stroke risk classification model using ensemble learning that combines Random Forest and XGBoost algorithms. A Kaggle dataset with 5110 samples (249 stroke, 4861 non-stroke) presented significant class imbalance. …”
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DIGITAL TWINS AND THEIR APPLIANCE IN TRANSPORT ECONOMICS by O. N. Rimskaya, I. V. Anokhov

“…The consequence of this is the emergence of digital twins that allow modeling and predicting the behavior of both individual processes and enterprises as a whole.The aim of the article is to investigate the process of digitalization in the transport industry. …”
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CALCULATION OF WEIGHT COEFFICIENTS IN CONTINUOUS PARTICLE FILTER by K. A. Rybakov

“…In addition, it is planned to develop algorithms for predicting the states of stochastic diffusion and jump-diffusion systems based on the calculation of weight coefficients in the particle filter considered in this article.…”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater by Marco Baldan, Paolo Di Barba

“…Eventually, the ePINN predicts the temperature field within the graphite plate.…”
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Modeling Particle Transport in Astrophysical Outflows and Simulations of Associated Emissions from Hadronic Microquasar Jets by D. A. Papadopoulos, O. T. Kosmas, S. Ganatsios

“…In this work, after improving the formulation of the model on particle transport within astrophysical plasma outflows and constructing the appropriate algorithms, we test the reliability and effectiveness of our method through numerical simulations on well-studied galactic microquasars as the SS 433 and the Cyg X-1 systems. …”
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Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
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Multi-omics identification of a polyamine metabolism related signature for hepatocellular carcinoma and revealing tumor microenvironment characteristics by Yuexi Yu, Huiru Liu, Kaipeng Liu, Meiqi Zhao, Yiyan Zhang, Runci Jiang, Fengmei Wang

“…Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. …”
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An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics by Emir Žunić, Dženana Đonko, Emir Buza

“…Moreover, as the performance of the algorithm depends on the set of control parameters and constants, a predictive model that adaptively adjusts these parameters and constants according to historical data is proposed. …”
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Regulatory Framework of the Conduct of Forensic Construction Examination by A. A. Revunov

“…In order to improve the current situation concerning the regulation of forensic construction and technical examinations, the following measures have been proposed: revision and improvement of their methodological, theoretical, and legal foundations, in-depth analysis of the content of urban planning legislation from the point of view of requirements mandatory for application by a forensic expertbuilder, specifying the limits of an expert’s competence, the formation of unified algorithms and forms of presenting research, the development of sub-theories on the legal and organizational support of the nonstate forensic activity, the active involvement of research institutions and higher educational institutions in the conduct of expert examinations.…”
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Expected Transmission Energy Route Metric for Wireless Mesh Senor Networks by YanLiang Jin, HuiJun Miao, Quan Ge, Chi Zhou

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Postcholecystectomy syndrome: the modern approach: resolution of Advisory council by V. T. Ivashkin, A. V. Okhlobystin, D. S. Bordin, E. Ya. Seleznyova, Yu. A. Kucheryavy, Ye. V. Bystrovskaya, O. C. Vasnev, M. F. Osipenko, G. H. Musayev, Yu. O. Shulpekova

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Quantum ensemble learning with a programmable superconducting processor by Jiachen Chen, Yaozu Wu, Zhen Yang, Shibo Xu, Xuan Ye, Daili Li, Ke Wang, Chuanyu Zhang, Feitong Jin, Xuhao Zhu, Yu Gao, Ziqi Tan, Zhengyi Cui, Aosai Zhang, Ning Wang, Yiren Zou, Tingting Li, Fanhao Shen, Jiarun Zhong, Zehang Bao, Zitian Zhu, Zixuan Song, Jinfeng Deng, Hang Dong, Pengfei Zhang, Wei Zhang, Hekang Li, Qiujiang Guo, Zhen Wang, Ying Li, Xiaoting Wang, Chao Song, H. Wang

“…Based on the probabilistic nature of quantum measurement, the algorithm improves the prediction accuracy by refining the attention mechanism during the adaptive training and combination of quantum classifiers. …”
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On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates by Neelesh Rampal, Peter B. Gibson, Steven Sherwood, Gab Abramowitz

“…Abstract While deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. …”
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Correcting the Arcjet Thruster Disturbance in GOES‐16 Magnetometer Data by S. Califf, D. Early, M. Grotenhuis, T. M. Loto'aniu, J. Kronenwetter

“…This study presents a correction algorithm that removes the arcjet signal from the magnetometer data. …”
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Dynamic VaR Measurement of Gold Market with SV-T-MN Model by Fenglan Li, Jie Wang, Liyun Su, Bao Yang

“…Secondly, future sample volatility prediction was realized by using approximate filtering algorithm. …”
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An MCV Nonhydrostatic Atmospheric Model with Height-Based Terrain following Coordinate: Tests of Waves over Steep Mountains by Xingliang Li, Xueshun Shen, Feng Xiao, Chungang Chen

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Nonlinear Elasto-Mammography for Characterization of Breast Tissue Properties by Z. G. Wang, Y. Liu, G. Wang, L. Z. Sun

“…The results demonstrate that the projective displacements acquired in X-ray mammography provide sufficient constitutive information of the tumor and prove the usability and robustness of the proposed method and algorithm.…”
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