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  1. 461

    A New Mathematical Model for Flank Wear Prediction Using Functional Data Analysis Methodology by Sonja Jozić, Branimir Lela, Dražen Bajić

    Published 2014-01-01
    “…Regression coefficients of the model are in the form of time dependent functions that have been determined through the use of functional data analysis methodology. The mathematical model has been developed by means of applied cutting parameters and measured cutting forces components during the end milling of workpiece made of 42CrMo4 steel. …”
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  2. 462

    Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

    Published 2023-08-01
    “…Cloud forensics plays a vital role to address the security issues related to cloud computing by identifying, collecting and studying digital evidence in cloud environment.The aim of the research paper is to explore the concept of cloud forensic by applying optimization for feature selection before classification of data on cloud side. The data is classified as malicious and non-malicious using convolutional neural network. …”
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  3. 463

    Nanoantenna modelling for their further use as data transmitter-receiver devices on 3-d integral circuits by D. A. Serov, K. V. Pershina, I. V. Burdina

    Published 2020-12-01
    “…As a result of the study, a model has been identified that has the most balanced parameters suitable for its further use as the main device for receiving and transmitting data on three-dimensional integrated circuits.…”
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  4. 464

    Data-Driven Estimation Models for Chloride Ion Diffusion Coefficient in Concrete Using Bayesian Approach by Ruifu Cui, Huihui Yang, Jiehong Li, Honghui Tang, Guowen Yao, Yang Yu, Xuanrui Yu

    Published 2024-01-01
    “…To enhance the accuracy of chloride diffusivity estimation, this paper has collected 109 sets of experimental data. These data were used to develop a Bayesian prediction model for a more precise estimation of chloride diffusivity. …”
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  5. 465

    Updating Categorical Soil Maps Using Limited Survey Data by Bayesian Markov Chain Cosimulation by Weidong Li, Chuanrong Zhang, Dipak K. Dey, Michael R. Willig

    Published 2013-01-01
    “…A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. …”
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  6. 466

    Using Adjoint-Based Forecast Sensitivity Method to Evaluate TAMDAR Data Impacts on Regional Forecasts by Xiaoyan Zhang, Hongli Wang, Xiang-Yu Huang, Feng Gao, Neil A. Jacobs

    Published 2015-01-01
    “…This study evaluates the impact of Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observations on regional 24-hour forecast error reduction over the Continental United States (CONUS) domain using adjoint-based forecast sensitivity to observation (FSO) method as the diagnostic tool. …”
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  7. 467
  8. 468

    Application of Landsat High Spatial Resolution Phenological Synthesized Data in Mountainous Land Cover Classification by Zhengzheng Hu, Fei Xiao, Yun Du, Zhou Wang, Jiahuan Luo, Qi Feng, Miaomiao Chen

    Published 2025-07-01
    “…Furthermore, the results demonstrate that, in the absence of terrain data, multi-year synthesized phenology data provide even greater enhancements in land cover classification accuracy using remote sensing imagery.…”
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  9. 469

    Predictions of Equatorial Vertical Plasma Drift Using TEC Data and a Neural Network Model by S. A. Reddy, X. Pi, C. Forsyth, A. Aruliah, A. Smith

    Published 2025-06-01
    “…The uniqueness of VIPER is that it uses TEC data for the prediction, and the data is globally and readily available. …”
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  10. 470

    Black Ice Prediction Model for Road Pavement Using Weather Forecast Data and GIS Database by Tam Minh Phan, Min-Seok Jang, Dae-Wook Park

    Published 2022-12-01
    “…The model has been developed based on the Python programming language. …”
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  11. 471

    A hybrid model for multimedia data compression using generative adversarial networks and chaotic encryption by P.T. Sivagurunathan, A. Sridevi

    Published 2025-12-01
    “…With the onset of web 2.0 and booming communication technologies like 5G, the amount of internet data being generated on a day-to-day basis has become massive and unimaginable. …”
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  12. 472
  13. 473

    Low Power Delay Product 8-bit ALU Design using Decoder and Data Selector by Nagarjuna Telagam, Nehru Kandasamy

    Published 2024-02-01
    “…This paper proposes a new low power 8 bit ALU digital circuit for nano scale regions. The proposed ALU has two 4x1 data selectors, 2x4 decoder and an adder circuit as sub modules. …”
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  14. 474

    Use of Optimised LSTM Neural Networks Pre-Trained With Synthetic Data to Estimate PV Generation by Miguel Martínez-Comesaña, Javier Martínez-Torres, Pablo Eguía-Oller, Javier López-Gómez

    Published 2025-06-01
    “…The use of simulated data as pre-training for deep learning models has increased in different fields. …”
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  15. 475

    A semantic segmentation framework with UNet-pyramid for landslide prediction using remote sensing data by Arush Kaushal, Ashok Kumar Gupta, Vivek Kumar Sehgal

    Published 2024-12-01
    “…Currently, Deep Learning is constrained by the lack of applicability, lack of data, and low efficiency in landslide detection but with recent advancement in deep learning-based solutions for landslide detection has sparked considerable advantages over traditional techniques. …”
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  16. 476

    Framework for Prioritizing Solutions in Overcoming Data Quality Problems Using Analytic Hierarchy Process (AHP) by Imelda Aritonang, Achmad Nizar Hidayanto, Nur Fitriah Ayuning Budi, Rahmat M. Samik Ibrahim, Solikin Solikin

    Published 2019-01-01
    “…The results of the study indicate that the proposed model can be used to formulate solutions to data problems in BPS.…”
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  17. 477

    Stacked LSTM for Short-Term Wind Power Forecasting Using Multivariate Time Series Data by Manisha Galphade, V. B. Nikam, Biplab Banerjee, Arvind W. Kiwelekar, Priyanka Sharma

    Published 2025-06-01
    “…To improve the performance, data preprocessing is carried out using two techniques such as removal of missing values and imputing missing values using Random Forest Regressor (RFR). …”
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