Research on the application of improved MCMC algorithm in the measurement of high-dimensional financial data by Naijia Liu, Yuchao Su

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Decomposition rate and property changes of deadwood across an altitudinal gradient: a case study in the Babia Góra Massif, Poland by Adam Górski, Ewa Błońska, Jarosław Lasota

“…In the case of coniferous wood (spruce and fir), the decomposition process proceeded at a similar rate across all altitudes, but more slowly compared to deciduous species. …”
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Alternative inflation rates by T. I. Gordievich, P. V. Ruzanov

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Subspace‐based distributed target detection method with small training data samples by Guangfen Wei, Zhan Zhou, Yuan Luo, Tao Jian, Xiaoming Tang

“…Abstract Detecting distributed targets precisely in homogeneous environments has been a hot topic in radar signal processing. Generally, distributed targets are often modelled with subspace models of unknown coordinates, and clutter is modelled as the complex Gaussian distribution with zero mean and unknown covariance matrix, while covariance matrix is estimated with a set of training data without the target signal. …”
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Research on the In-Depth Interpretation of Measured Pressure Data During Fluid Sampling with Dual Packers by YU Qiang, CHU Xiaodong, ZHOU Yanmin, QIN Xiaofei, KONG Sun, ZUO Youxiang

“…Dual packer is a kind of formation test pressure measurement sampling tool, the sampling process usually needs to be pumped for several hours or even more than ten hours to obtain formation fluid samples and pressure/flow rate data, but it can’t truly reflect the detection range of formation permeability. …”
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A mathematical model of the copper plating process in restoration of road transport equipment parts by A. S. Ianuta, G. S. Zadorozhnii, Yu. V. Shtephan

“…Mathematical processing using modern statistical data processing tools that excluded possible errors, providing to obtain the dependence of factors with the necessary accuracy was carried out.Results. …”
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Compartmental Models Driven by Renewal Processes: Survival Analysis and Applications to SVIS Epidemic Models by Divine Wanduku, Md Mahmud Hasan

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Can heart rate sequences from wearable devices predict day-long mental states in higher education students: a signal processing and machine learning case study at a UK university by Tianhua Chen

“…Having achieving statistically significant results over the baseline, this provides a understanding of how heart rate sequences alone may be used to characterize mental states through signal processing and machine learning, with the system poised for further testing as the ongoing data collection continues.…”
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Modal Regression Estimation by Local Linear Approach in High-Dimensional Data Case by Fatimah A. Almulhim, Mohammed B. Alamari, Ali Laksaci, Zoulikha Kaid

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Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models by Xingyu Zhang, Yanshan Wang, Yun Jiang, Charissa B. Pacella, Wenbin Zhang

“…Emergency severity was categorized into urgent (scores 1–3) and non-urgent (scores 4–5) based on the Emergency Severity Index. Unstructured data, including chief complaints and reasons for visit, were processed using a Bidirectional Encoder Representations from Transformers (BERT) model. …”
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Small language models enable rapid and accurate extraction of structured data from unstructured text: An example with plants and their specialized metabolites by Lucas Busta, Alan R. Oyler

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Evaluating the Effectiveness of Large Language Models in Converting Clinical Data to FHIR Format by Julien Delaunay, Daniel Girbes, Jordi Cusido

“…This study explores the potential of large language models (LLMs) to automate this conversion process, aiming to enhance data interoperability and improve healthcare outcomes. …”
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Data analysis-based framework for the design and assessment of chemical process plants: a case study in amine gas-treating systems by Rahul Gupta, Gladys Navas, Daniela Galatro

“…This work presents a process-integrity assessment framework to chemical process design that combines first principles, heuristics, vendor specifications, standards/codes, data analysis, and machine learning modelling, hypothesized as an efficient route for optimal process design. …”
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The sexual health assessment of practices and experiences (SHAPE) questionnaire: Adaptation Process and Results of the Data Collected during the Pre-Test in Portugal by Ana Luísa Patrão, Maria Yolanda Makuch, Vilma Zotareli, Pedro Nobre

“…The objective of this study is to describe the adaptation process and the results of the data collected during the pre-test. …”
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PRONAME: a user-friendly pipeline to process long-read nanopore metabarcoding data by generating high-quality consensus sequences by Benjamin Dubois, Mathieu Delitte, Salomé Lengrand, Claude Bragard, Anne Legrève, Frédéric Debode

“…However, Nanopore sequencing data exhibit a particular profile, with a higher error rate compared with Illumina sequencing, and existing bioinformatics pipelines for the analysis of such data are scarce and often insufficient, requiring specialized tools to accurately process long-read sequences.ResultsWe present PRONAME (PROcessing NAnopore MEtabarcoding data), an open-source, user-friendly pipeline optimized for processing raw Nanopore sequencing data. …”
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The efficiency of E-KON system in the design and development process of the Shurtan gas condensate field by B. Kh. Bekov, O. A. Khujaev

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Graph technologies in an intelligent system of complex analysis of data from Internet sources by I. I. Piletski, M. Р. Batura, L. Y. Shylin

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Advancing Credit Rating Prediction: The Role of Machine Learning in Corporate Credit Rating Assessment by Nazário Augusto de Oliveira, Leonardo Fernando Cruz Basso

“…The study evaluated multiple ML models, including Logistic Regression, Support Vector Machines, Decision Trees, Random Forest, Gradient Boosting (GB), and Neural Networks, using rigorous data pre-processing, feature selection, and validation techniques. …”
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FLC-Net: Innovative fraud classification in loan applications with dual channel graph advanced neural network by P. Pedda Sadhu Naik, Kalleda Appanolla Architha, Maddela Mahesh, Chitkula Anand, Gaddam Shriya Reddy, Patlola Suraj Reddy

“…The proposed Fraudulent Loan Classification Network (FLC-Net) addresses these limitations by integrating robust data preprocessing techniques, including missing value imputation, outlier removal, and normalization, to enhance data quality and consistency. …”
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Modification of Multilayer Perceptron Using Detection Rate Model for Prediction of Nominal Exchange Rate by Al-Khowarizmi Al-Khowarizmi, Romi Fadillah Rahmat, Michael J Watts, Akrim Akrim, Arif Ridho Lubis, Muhammad Basri

“…Multilayer perceptron (MLP) is one of the ANN methods that can be prediction all of data. Where the prediction needs to be reviewed because the prediction process does not always run normally. …”
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