Showing 1,121 - 1,140 results of 1,457 for search '(variable OR variables) function efficiency.', query time: 0.14s Refine Results
  1. 1121

    Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

    Published 2025-07-01
    “…During the optimization process, these controlling parameters are used as a design variable whereas the objective function required to me be a maximum is the summation of turbidity removal and salinity removal. …”
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  2. 1122

    Application of marine bacterial alginate lyases in wastewater treatment, biofilm removal and green technology by M.U.K. Anjung, H. Nursyam, A.A. Prihanto, E. Chasanah

    Published 2025-07-01
    “…In recent years, marine bacteria have emerged as a valuable and diverse source of these enzymes, owing to their unique adaptations to extreme marine conditions such as high salinity, variable potential of hydrogen, and fluctuating temperatures. …”
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  3. 1123

    Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

    Published 2025-02-01
    “…In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. …”
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  4. 1124

    Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

    Published 2024-01-01
    “…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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    Article
  5. 1125

    Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

    Published 2025-01-01
    “…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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  6. 1126

    Seq2scFv: a toolkit for the comprehensive analysis of display libraries from long-read sequencing platforms by Marianne Bachmann Salvy, Luca Santuari, Emanuel Schmid-Siegert, Nikolaos Lykoskoufis, Ioannis Xenarios, Bulak Arpat

    Published 2024-12-01
    “…With its versatile and standalone functionality, we anticipate that the implementation of Seq2scFv tools in antibody discovery pipelines will efficiently expedite the full characterization of display libraries and potentially facilitate the identification of high-affinity antibody candidates.…”
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  7. 1127

    Fabrication of Wood-Derived Carbon Aerogel/Mg(OH)<sub>2</sub> Bio-Composite and Its High Performance for Adsorption and Separation of Cadmium Ions by Ran An, Jinyue Liu, Haomiao Ma, Yuqing Yan, Yuanru Guo, Qingjiang Pan, Shujun Li

    Published 2025-05-01
    “…The resulting wood-derived carbon aerogels (WCA) were functionalized with Mg(OH)<sub>2</sub> to boost their environmental remediation potential. …”
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  8. 1128

    Non-destructive textural quality assessment of peaches and nectarines using near-infrared spectroscopy integration time by Eva Cristina Correa, Paola Baltazar, Pilar Barreiro, Natalia Hernández-Sánchez, Lourdes Lleó, Ángela Melado-Herreros, Belén Diezma

    Published 2025-12-01
    “…A principal component analysis (PCA) was used to analyze textural variability, and discriminant function analysis (DFA) and artificial neural networks (ANNs) were applied to classify fruit firmness levels.PCA effectively defined a new variable, PC1, that captured the variance in fruit texture, correlating positively with juiciness and negatively with firmness. …”
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  9. 1129

    Effects of Exercise on Physical Fitness in Older Adults with and Without Severe Cognitive Impairment by Oliver Ramos-Álvarez, Elkin Eduardo Roldán-Aguilar, Mariano Altamiranda-Saavedra, Juan Carlos Marín, Víctor Arufe-Giráldez

    Published 2025-03-01
    “…Physical fitness is defined as the ability to perform daily activities efficiently and without excessive fatigue, involving anthropometric variables and physical capacities. …”
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  10. 1130

    Advancing the modified face name associative memory exam in cognitive aging research: insights into connectomic correlates and task reliability by Yilin Liu, Yilin Liu, Mark H. Sundman, Mark H. Sundman, Dalen Hinderaker, Allison Yu-Chin Chen, Allison Yu-Chin Chen, Jacob M. Green, Jacob M. Green, Lisbeth G. Haaheim, Lisbeth G. Haaheim, Hannah M. Siu, Hannah M. Siu, Catherine Jezerc, Kaitlyn Lai, Carol Chen, Parker Guss, Ying-hui Chou, Ying-hui Chou, Ying-hui Chou

    Published 2025-07-01
    “…Experiment 2 revealed significant associations between mFNAME performance and network properties like global efficiency, local efficiency, and system segregation in the default mode network (DMN) and medial temporal network (MTN). …”
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  11. 1131

    Engineering safe anti-CD19-CD28ζ CAR T cells with CD8a hinge domain in serum-free media for adoptive immunotherapy by Muthuganesh Muthuvel, Muthuganesh Muthuvel, Thamizhselvi Ganapathy, Trent Spencer, Sunil S. Raikar, Saravanabhavan Thangavel, Alok Srivastava, Alok Srivastava, Alok Srivastava, Sunil Martin

    Published 2025-05-01
    “…CARs are modular synthetic antigen receptors integrating the single-chain variable fragment (scFv) of an immunoglobulin molecule to the TCR signaling. …”
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  12. 1132

    Signatures of Rapidly Rotating Stars with Chemically Homogeneous Evolution in the First Galaxies by Boyuan Liu, Yves Sibony, Georges Meynet, Volker Bromm

    Published 2025-01-01
    “…We find that the rest-frame UV luminosity of star-forming galaxies can be significantly enhanced by a factor of  ∼3−6 when CHE stars above a minimum initial mass of ${m}_{\star ,\min }^{\mathrm{CHE}}\sim 2-10\,{M}_{\odot }$ account for more than half of the total stellar mass following a Salpeter initial mass function. As a result, the UV luminosity functions observed at z  ∼ 12−16 can be reproduced with less extreme values of star formation efficiency and UV luminosity stochastic variability. …”
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  13. 1133

    Monitoring Abiotic Stressors in Rainfed Vineyards Involves Combining UAV and Field Monitoring Techniques to Enhance Precision Management by Federico Valerio Moresi, Pasquale Cirigliano, Andrea Rengo, Elena Brunori, Rita Biasi, Giuseppe Scarascia Mugnozza, Mauro Maesano

    Published 2025-02-01
    “…A fine-scale characterization, based on the spatial variability of soil’s physical–chemical and hydrological traits combined with temporal variability of vine canopy temperature extracted from UAV thermal images has been adopted in a rainfed vineyard of central Italy, for better understanding the impact of soil and climate abiotic factors in the vineyard for planning precision adaptation strategies encouraging sustainable resource use. …”
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  14. 1134

    Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

    Published 2024-10-01
    “…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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  15. 1135

    Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

    Published 2025-06-01
    “…However, significant variability within high‐frequency data sets can result in poor explanation of temporal dynamics using the simple C‐Q equation. …”
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  16. 1136

    Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

    Published 2025-07-01
    “…This model introduces the WTConv convolutional modules to expand the sensory field and improve computational efficiency, adopts the iRMB inverted residual block attention mechanism to enhance the modeling capability of crop spatial structure, and uses the UIOU loss function to effectively mitigate the misdetection and omission problem in the region of dense and overlapping targets. …”
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  17. 1137

    Biomechanical Analysis of <i>Camellia oleifera</i> Branches for Optimized Vibratory Harvesting by Rui Pan, Ziping Wan, Mingliang Wu, Shikui Lu, Lewei Tang

    Published 2024-12-01
    “…The nonlinear least squares method, based on the hyperbolic tangent function, was employed to fit the bending load–deflection curves of the branches. …”
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  18. 1138

    Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

    Published 2025-01-01
    “…Despite advances, existing diagnostic methods face challenges such as resource dependency, variability in accuracy, and limited accessibility, especially in underserved regions. …”
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  19. 1139

    Molecular and immune landscape of melanoma: a risk stratification model for precision oncology by Miao Sun, Junliang Wu

    Published 2025-05-01
    “…Knockdown efficiency was confirmed by qRT-PCR. Functional assays revealed that KIR2DL4 silencing significantly reduced cell proliferation, as assessed by MTT assay, and impaired migratory capacity, as demonstrated by wound healing assay. …”
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  20. 1140

    A simple model of the rheological curve of HPAM solutions at different temperatures by Eduar Pérez, Dario Alviso, Mauricio Carmona, Eduardo Manrique, Guillermo Artana

    Published 2024-12-01
    “…The solvent viscosity and relaxation time-employed as references to define these parameters-are functions of temperature. On the master surface, while the power coefficient of Carreau-Yasuda (n) exhibits only a slight dependency on temperature, the relative viscosity depends monotonically on this variable. …”
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