BAYESIAN ESTIMATE OF TELECOMMUNICATION SYSTEMS PREPAREDNESS by V. E. Emelyanov, S. P. Matyuk

“…The parameters of the a priori information can be determined by different methods or on the basis of sufficient statistical data. …”
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A Multidimensional Analysis Approach Toward Sea Cliff Erosion Forecasting by Maria Krivova, Michael J. Olsen, Ben A. Leshchinsky

“…This study presents an innovative Geographic Information Systems (GIS) algorithm to forecast sea cliff erosion progression utilizing imagery datasets (hereafter referred to as ‘rasters’). …”
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Deterring Street Crimes Using Aerial Police: Data-Driven Joint Station Deployment and Patrol Path Planning for Policing UAVs by Zuyu Chen, Yan Liu, Shengze Hu, Xin Zhang, Yan Pan

“…Evolved from the path planning algorithm, the second module utilizes a data-driven method to estimate the deterring effect of the candidate UAV stations with different numbers of UAVs. …”
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Strategic Traffic Management in Mixed Traffic Road Networks: A Methodological Approach Integrating Game Theory, Bilevel Optimization, and C-ITS by Areti Kotsi, Ioannis Politis, Evangelos Mitsakis

“…The methodology includes defining a model to achieve optimal mixed equilibria, designing an algorithm for multiclass traffic assignment, formulating strategic games to analyze player interactions, and establishing key performance indicators to evaluate network efficiency and effectiveness. …”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

“…crops, different weeds grow along with potatoes in agricultural fields. …”
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Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

“…This situation stresses the need to develop a computer-based system using a machine learning algorithm to classify words into proper grammatical notations. …”
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Methodology for classification of land use and vegetation cover using MODIS-EVI data by Vagner P. Mengue, Denise C. Fontana, Tatiana S. da Silva, Daniel Zanotta, Fernando C. Scottá

“…The procedures included the use of MODIS Sensor images, altimetric data and nighttime images, associated with a hierarchical decision tree classifier, constructed using the C4.5 algorithm. The proposed approach stems from the consideration that the study area has varying characteristics and, therefore, should be treated simultaneously by different and intuitive classifiers, which justifies the choice of decision tree. …”
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HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis by Dawit Kefale Wassie, Lebsework Negash Lemma, Abrham Tadesse Kassie

“…The study of the control of quadrotors was addressed extensively in different AAV research areas. In this work, the nonlinear dynamic model of the quadrotor has been developed using the Newton-Euler technique. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The combination of the single model and multi-model approach with UNet and UNetPlusPlus results in four base learners, each displaying varying accuracy for different landmarks. To leverage the strengths of these individual models, three ensemble methods are explored, that includes supervised ensembling with XGBoost, unsupervised ensembling with the DBSCAN algorithm, and mathematical aggregation using weighted averaging. …”
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Optimal design of a hybrid system composed of coagulation process and multi-stage filtration unit for on-site treatment of greywater in rural area by Zahra Akbari, Fereshteh Nourmohammadi Dehbalaei, Zahra Mohammad Hosseini, Seyed Taghi Omid Naeeni

“…Multilayer nonlinear machine learning model was utilized to evaluate the performance of this hybrid system and adaptive heuristic search algorithm was used to achieve the optimal configuration of multilayer sand filter using optimization technique. …”
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Development of An Optimal Low-Noise Voice-Coil Actuator for Precision Motion Control Applications by Suorena Saeedi, Ali Sadighi, Masoud Shariat Panahi

“…Finally, the effectiveness of the multi-physics-based modeling approach, enhanced by experimentally-driven characteristics, is evaluated against empirical results.…”
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Universal Modeling for Non-Destructive Testing of Soluble Solids Content in Multi-Variety Blueberries Based on Hyperspectral Imaging Technology by Lingqi Meng, Guoliang Chen, Dayang Liu, Ning Tian

“…The characteristic wavelengths were optimized in stages by uninformative variables elimination (UVE) and the successive projections algorithm (SPA), and the model was simplified by multiple linear regression (MLR). …”
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Low-Field Magnetic Resonance Imaging: A Full-Wave Simulation of Radiofrequency Birdcage Coils for Musculoskeletal Limb Imaging by Giulio Giovannetti, Francesca Frijia, Maria Filomena Santarelli, Vincenzo Positano

“…<b>Methods:</b> This paper describes the application of a numerical full-wave method based on the finite-difference time-domain (FDTD) algorithm for the simulation and the design of birdcage coils for musculoskeletal low-field MRI. …”
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Machine learning based shear strength prediction in reinforced concrete beams using Levy flight enhanced decision trees by Aybike Özyüksel Çiftçioğlu, Anıl Delikanlı, Torkan Shafighfard, Faramarz Bagherzadeh

“…A comprehensive dataset comprising 195 experimentally tested T-beams is used to train and evaluate six different regression models, including optimized Decision Tree, Random Forest, AdaBoost, K-Nearest Neighbors, Ridge Regression, and the proposed Levy-DT. …”
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Using machine learning to study the population life quality: methodological aspects by E. V. Shchekotin, В. Л. Гойко, P. A. Basina, B. B. Bakulin

“…Various approaches to text vectorisation, publicly available neural network models pre-trained on large Russian-language text corpora, as well as metrics for evaluating the algorithms results were analysed. Computational experiments with different algorithms were carried out, according to the results of which the Rubert-tiny algorithm was selected due to its high learning and classification rate. …”
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Memory Efficient Local Features Descriptor for Identity Document Detection on Mobile and Embedded Devices by Daniil P. Matalov, Elena E. Limonova, Natalya S. Skoryukina, Vladimir V. Arlazarov

“…In this paper, we propose a data-driven approach to training a memory-efficient local feature descriptor for identity documents location and classification on mobile and embedded devices. The proposed algorithm for retrieving a dataset of patches is based on the specifics of document detection in smartphone camera-captured images with a template matching approach. …”
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Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…Hyperparameter optimization for the classifiers was conducted using GridSearchCV, while feature selection was performed with the recursive feature elimination (RFE) algorithm. Model performance was evaluated using seven different metrics: Accuracy, Precision, Recall, F1-score, receiver operating characteristic area under the curve (ROC AUC), precision recall area under the curve (PR AUC), and Matthews correlation coefficient (MCC). …”
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THE STUDY OF THE BRAIN IN A PATIENT WITH TYPE 1 DIABETES MELLITUS USING TECHNIQUES OF MAGNETIC RESONANCE IMAGING by Yu. G. Samoylova, N. G. Zhukova, M. V. Matveyeva, M. A. Rotkank, O. S. Tonkikh

“…The study of the brain, namely structural and metabolic manifestations of diabetes, is one of the priority problem of modern medical science.The aim of the study was to evaluate dynamics in the different techniques of magnetic resonance imaging in the diagnosis of brain changes in patients with T1DM.Research methods included physical examination, in accordance with the diagnostic algorithm of patients with T1DM, a neurologist consultation, an assessment of cognitive function, analysis of brain changes using standard magnetic resonance imaging and spectroscopy. …”
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On assessing the efficiency of executive authorities in achieving the national development goals by N. E. Buletova, T. A. Zolotko

“…Based on the analysis of the dynamics and structure of the number of state and municipal employees and their remuneration in the Russian Federation, Southern Federal district and Volgograd region, the differences in the work of state and municipal employees at different levels are reasoned and proposals are developed for the use of a system of key performance indicators (KPI) linked to the goals and objectives of national projects at all levels of executive power. …”
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Predicting the Spatial Distribution of Geological Hazards in Southern Sichuan, China, Using Machine Learning and ArcGIS by Ruizhi Zhang, Dayong Zhang, Bo Shu, Yang Chen

“…Several machine learning models were evaluated, including random forest, XGBoost, and CatBoost, with model optimization performed using the Sparrow Search Algorithm (SSA) to enhance prediction accuracy. …”
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