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  1. 1561

    Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass by J. Meloche, N. R. Leroux, B. Montpetit, V. Vionnet, C. Derksen

    Published 2025-08-01
    “…A reduction in the mathematical complexity of SWE retrieval cost functions and a reduction in computation of up to 80 % can be gained by using fewer layers in the SWE retrieval.…”
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    Article
  2. 1562

    Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Farshad Ahmadi, Rasoul Mirabbasi, Ali Torabi Haghighi

    Published 2025-06-01
    “…The Pearson’s correlation coefficient (PCC) and Cosine Amplitude Sensitivity (CAS) as feature (input) selection process determine the only precipitation (P m ) as the most effective input variable among a list of on-site potential climate time series parameters recorded in the study area. …”
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    Article
  3. 1563

    Advanced microfluidic strategies for core-shell nanoparticles: the next-generation of polymeric and lipid-based drug nanocarriers by Giuseppe Nunziata, Alessandro Borroni, Filippo Rossi

    Published 2025-05-01
    “…Microfluidic technology has transformed the synthesis of core-shell nanoparticles (CSNPs), providing an unprecedented level of control over their structural and functional properties. This review critically evaluates recent advancements, highlighting the superiority of microfluidic methods over conventional batch techniques, which often suffer from variability and scalability issues. …”
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    Article
  4. 1564

    Exploring the Impact of School-Based Physical and Perceived Environments on Students’ Physical Activity During Recess: A Case Study of Four Schools in Xi’an, China by Qing Wang, Yan Wang, Lan Zhou, Yong Nan

    Published 2024-10-01
    “…The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. …”
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    Article
  5. 1565

    An assessment of the likely impact of strain-related phenotypic plasticity on hominin fossil species identification by M. Collard, S.J. Lycett

    Published 2009-07-01
    “…We divided the measurements into three groups: measurements of features subject to high masticatory strain, measurements of features subject to low-to-moderate masticatory strain, and measurements of features that do not remodel and therefore are not prone to strain-related phenotypic plasticity. Next, we used the coefficient of variation and ANOVA to investigate whether masticatory strain is a cause of variability. …”
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  6. 1566

    Optimum System Design Using Rough Interval Multi-Objective De Novo Programming by Iftikhar Hussein, Hegazy Zaher, Naglaa Ragaa Saeid, Hebaa Sayed Roshdy

    Published 2024-05-01
    “…This paper suggested a new approach for solving uncertainty of De novo programming problems (DNP) using a combination model consisting of a rough interval multi-objective programming (RIMOP) and DNP, where coefficients of decision variables of objective functions and constraints are rough intervals (RIC). …”
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    Article
  7. 1567

    Development of Speech Therapy Application for Children with Stuttering (STACS) by Janith Raj Jayaraju, Amudhu Sankar

    Published 2025-09-01
    “…Conclusion: Most parents found this prototype app easy to use, efficient in training their children, and highly functional. …”
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    Article
  8. 1568

    Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

    Published 2022-12-01
    “…Due to the spectral overlap of the crops in some time periods, network training was associated with a relatively high loss and therefore, for the test area, the overall classification accuracy was 69% (percent) and the kappa coefficient was 0.55. In the next step, the functions that were developed as phenological features for crops were applied on the time series of the bands, and for each crop, a feature channel was obtained as the special feature of that crop. …”
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    Article
  9. 1569

    Testing the Level of Alternative Institutions as a Slowdown Factor of Economic Development: the Case of Montenegro by Mimo Draškovic, Sanja Bauk, Dalia Streimikiene, Veselin Draskovic

    Published 2017-05-01
    “…On the basis of the conducted statistical examines: standard error of the regression estimate, correlation coefficient, and coefficient of determination are calculated on the basis of previously determined regression coefficients and forecast values of the linear function of free variables (factors: a, b, and c). …”
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    Article
  10. 1570

    Bifurcations of Spatially Inhomogeneous Solutions of a Boundary Value Problem for the Generalized Kuramoto–Syvashinsky Equation by Alina V. Sekatskaya

    Published 2017-10-01
    “…In this paper, a differential partial equation with an unknown function of three variables time and two spatial variables – is considered. …”
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    Article
  11. 1571

    Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

    Published 2021-09-01
    “…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
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  12. 1572

    On the approximation of sum of lognormal for correlated variates and implementation. by Asyraf Nadia Mohd Yunus, Nora Muda, Abdul Rahman Othman, Sonia Aïssa

    Published 2025-01-01
    “…In probabilistic modeling across engineering, finance, and telecommunications, sums of lognormal random variables frequently occur, yet no closed-form expression exists for their distribution. …”
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    Article
  13. 1573

    Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD by J. Alberto Neder, Giles Santyr, Brandon Zanette, Miranda Kirby, Marina Pourafkari, Matthew D. James, Sandra G. Vincent, Carrie Ferguson, Chu-Yi Wang, Nicolle J. Domnik, Devin B. Phillips, Janos Porszasz, William W. Stringer, Denis E. O’Donnell

    Published 2024-12-01
    “…Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients’ out-of-proportion dyspnea. …”
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    Article
  14. 1574

    Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive D... by Duc Nam Nguyen, Thanh-Phong Dao, Ngoc Le Chau, Van Anh Dang

    Published 2019-01-01
    “…The optimization problem considers three design variables and two objective functions. An efficient hybrid optimization approach of central composite design (CDD), finite element method (FEM), Kigring metamodel, and multiobjective genetic algorithm (MOGA) is developed. …”
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  15. 1575

    Development of Sub-channel Program and Multi-objective Optimization Method Research for Printed Circuit Heat Exchanger by CHEN Liqin, HUO Honglei, XIE Renyao, YANG Yi

    Published 2024-12-01
    “…The results of sensitivity analysis show that as the flow channel width and height of the cold side flow channel increase, the sensitivity of the objective function to the variables continues to decrease, the optimization effect gradually becomes worse, and there are optimal design points, which are 4 mm and 1 mm respectively. …”
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  16. 1576

    Fuzzy Controller Design Optimized by the Grasshopper Algorithm to Realize Maximum Power in Photovoltaic Systems by Kamran Safaei, Aida Esmaeilian-Marnani, Hossein Emami, Amir Hossein Zaeri

    Published 2024-08-01
    “…In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. …”
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  17. 1577

    Land-Cover Semantic Segmentation for Very-High-Resolution Remote Sensing Imagery Using Deep Transfer Learning and Active Contour Loss by Miguel Chicchon, Francisco James Leon Trujillo, Ivan Sipiran, Ricardo Madrid

    Published 2025-01-01
    “…We assessed the U-Net-scSE, FT-U-NetFormer, and DC-Swin architectures, incorporating transfer learning and active contour loss functions to improve performance on semantic segmentation tasks. …”
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    Article
  18. 1578

    Providing a Roadmap for the Adaption of Agricultural Sector to Water Scarcity Conditions (Case Study: Selected Crops of Tajan Basin, Iran) by H. Fouladi, H. Amirnejad, S. Shirzadi Laskookalayeh

    Published 2024-09-01
    “…For this reason, the void of using an efficient model that can provide all economic and environmental aspects at the same time was completely felt. …”
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    Article
  19. 1579

    SCIENCE TEACHERS’ ICT USE FREQUENCY AND THE BARRIERS THEY WERE EXPOSED by Fatma TAŞKIN EKİCİ, Seçil DEMİRHAN, İzzet KARA, Erhan EKİCİ

    Published 2014-07-01
    “…</p><p>In the pilot study (n=231), it has been revealed that the Cronbach Alfa internal consistency coefficient for FOU was α=0,91and for BFU was α=0,88. …”
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  20. 1580

    Ridge regression and its applications in genetic studies. by M Arashi, M Roozbeh, N A Hamzah, M Gasparini

    Published 2021-01-01
    “…On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. …”
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    Article