Research note: Genetic parameters estimation of egg quality traits in Beijing-You chickens by Xinying Xu, Yuze Yang, Xiaoke Zhang, Dexin Wang, Qin Li, Zhuo Chang, Aixin Ni, Ziyan Huang, Jingwei Yuan, Yanyan Sun, Yunlei Li, Adamu Mani Isa, Jilan Chen

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Ambulatory electrocardiographic monitoring in patients with Fabry disease: study design and cohort characterization by E. V. Kotelnikova, V. N. Senchikhin, T. P. Lipchanskaya

“…Most patients are active Internet users, are aware of telemedicine possibilities and are interested in remote monitoring. The main complaints were related to cardiac function interruptions, palpitations, and chest discomfort. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…Methodologically, the study used CNN algorithms optimised by Bayesian techniques for the prediction of eight water quality indices, coupled with SHAPley Additive exPlanations (SHAP) analysis under XAI to interpret the complex decision-making processes of these models. …”
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Wideband Reflectarray Antennas in the Microwave Range by L. М. Liubina, S. V. Ballandovich, G. A. Kostikov, Yu. G. Antonov

“…The phase error minimization algorithms were adapted to work in the extended frequency range.Results. …”
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Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…However, most existing CMOS PUFs are found to be vulnerable to modeling attacks based on machine learning (ML) algorithms. Memristors leveraging nanotechnology fabrication processes and highly nonlinear behavior became an interesting alternative to the existing CMOS-based PUF technology, introducing cryptographic and resilient random outputs. …”
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Cross-dimensional adaptivity research on a 3D earth observation data cube model by Yu Jinsongdi, Cui Zhanying, Baumann Peter, Tong Ruiju, Wei Dandan, Luo Yuan

“…The proposed method is based on a 3D adaptive data cube model constructed in a 3D adaptive space. The main objective is to achieve interoperability between EO data cubes of different dimensions while adhering to common geospatial standards. …”
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Compensation of Speckle Noise in 2D Images from Triangulation Laser Profile Sensors Using Local Column Median Vectors with an Application in a Quality Control System by Paweł Rotter, Dawid Knapik, Maciej Klemiato, Maciej Rosół, Grzegorz Putynkowski

“…The main function of triangulation-based laser profile sensors—also referred to as laser profilometers or profilers—is the three-dimensional scanning of moving objects using laser triangulation. …”
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OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…Current detection methods fall into two main categories: traditional methods and deep learning-based approaches. …”
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MRI machine learning model predicts nerve root sedimentation in lumbar stenosis: a prospective study by Qing Wang, Xianping Luo, Deng Li, Yi Zhai, Caiyun Ying

“…Recursive feature elimination with cross-validation (RFECV) was used to select predictive features, and models were established via random forest (RF), K-nearest neighbors (KNN), and extreme gradient boosting (XGBoost) algorithms and evaluated in terms of precision, recall, average F1 score, accuracy, and AUC. …”
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RESEARCH OF FACTORS, WHICH MAY LEED TO ECONOMIC EMERGENCY APPEARANCE by O. O. Trush, D. A. Gorovyi, O. M. Goncharenko

“…As it can be seen from the scheme, there are two main reasons for the appearance of an emergency, depending on the source of influence on this event — external or internal to the country. …”
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Modern strategies of alternative insulin delivery systems by І. О. Vlasenko, L. L. Davtian, V. V. Hladyshev

“…Innovations in alternative insulin delivery systems include algorithms for continuous glucose monitoring systems, glucose-sensitive polymer matrices and biological structures with insulin. …”
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Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory by Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore

“…Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. …”
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Markov model of representation of sensual images for the formation of the model of the outside world by A. A. Solodov

“…In this regard, the further development of the model may be associated with the assessment of the probability of the system response to external influences, taking into account the characteristics of these specific signals, as well as the development of optimal algorithms for decision-making about the presence or absence of impacts on the system from the outside world.…”
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Development and validation of a nomogram for predicting low Kt/Vurea in peritoneal dialysis patients by Danfeng Zhang, Tian Zhao, Liting Gao, Huan Zhu, Haowei Jin, Guiling Liu, Deguang Wang

“…Univariate logistic regression, LASSO analysis, and Random Forest (RF) algorithms were employed to identify potential biomarkers. …”
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Unsupervised Rural Flood Mapping from Bi-Temporal Sentinel-1 Images Using an Improved Wavelet-Fusion Flood-Change Index (IWFCI) and an Uncertainty-Sensitive Markov Random Field (US... by Amin Mohsenifar, Ali Mohammadzadeh, Sadegh Jamali

“…To resolve this issue, an unsupervised change detection approach, made up of two main steps, is proposed for detecting floodwaters from bi-temporal SAR data. …”
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Theoretical justification of the model of search for optimal solutions in complex resource management systems by Roman A. Khalturin, Roman O. Sudorgin, Nikita S. Akinshin

“…In multicriteria optimization under uncertainty, the lack of a unified mathematical framework requires the use of diverse methods such as combinatorics, graph theory, heuristics, linear and dynamic programming, and search algorithms. The research highlights the challenges of applying these methods in complex systems, where external and internal uncertainties complicate the formulation of constraints and the integration of qualitative and quantitative criteria. …”
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Problems in the formation and implementation of the methodology for investigating homicides related to domestic violence by R. L. Stepaniuk, V. O. Husieva, V. V. Kikinchuk

“…These classifications also make it possible to detail individual elements of the methodology for investigating the category of homicide under study, including typical investigative situations, versions, tactical tasks of the investigation, algorithms of investigator's actions and tactical operations. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…The back end of the methodology uses support vector machine (SVM) and extreme gradient boosting (XGB) classification algorithms to establish the relationship between the retrieved feature vector and breast functionality. …”
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Ensuring Measurement Integrity in Petroleum Logistics: Applying Standardized Methods, Protocols, and Corrections by Asta Meškuotienė, Paulius Kaškonas, Benas Gabrielis Urbonavičius, Justina Dobilienė, Edita Raudienė

“…This necessitates that all measurement results are traceable to reference conditions (mass in vacuum, volume at +15 °C). The proposed algorithms for oil mass and volume measurement and recalculation highlight the need for unified international regulations and a robust system.…”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. The main objective is to enhance the accuracy and robustness of IDS in smart grids. …”
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