Modelagem da produtividade e gestão da qualidade acadêmica by Annibal Parracho Sant'Anna

“…It is a hierarchical model because technical coefficients of the academic production function are modeled as function of second level explanatory variables in such a way that such production function is allowed to change coherently from one department to another. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…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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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

“…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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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…An optimization analysis of CPD−PS is conducted using response surface methodology (RSM), and the influence of design variables on the objective function (<i>η</i>_ave and <i>p</i>) is analyzed. …”
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Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

“…Our analysis underscores S-ANFIS’s superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. …”
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Bivariate Epanechnikov-exponential distribution: statistical properties, reliability measures, and applications to computer science data by H. M. Barakat, M. A. Alawady, I. A. Husseiny, M. Nagy, A. H. Mansi, M. O. Mohamed

“…The statistical properties of the EP-EX-FGM model are examined, including product moments, coefficient of correlation between the internal variables, moment generating function, conditional distribution, concomitants of order statistics (OSs), mean residual life function, and vitality function. …”
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Non-Iterative Estimation of Multiscale Geographically and Temporally Weighted Regression Model by Ya-Di Dai, Hui-Guo Zhang

“…The results demonstrate that the non-iterative estimation method for MGTWR significantly enhances computational efficiency while effectively capturing the scale effects of spatiotemporal variation in the regression coefficient functions for each predictor.…”
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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…The optimization targeted the perforation friction coefficient <italic>k</italic>_perf as the primary unknown variable. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. …”
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A secondary analysis of gait after a 4-week postural intervention for older adults with hyperkyphosis by L. C. Hughes, A. L. Ellis, H. L. Rogers, M. Hadley, R. V. Galloway

“…Pearson correlation coefficients were utilized to investigate correlations between all variables at baseline and in pre- and post intervention change values. …”
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Improved Deflection Prediction Model for PSC Box Girder with Stay Cable System during Tensioning Phase by Gangnian Xu, Weimin Xu, Zhanhong Wang, Ruishuo Zhang

“…Uncertainty and sensitivity analysis are conducted for the Dongming Huanghe River Highway Bridge. An objective function is applied to select the optimal combination of random variables, and a modified model is established and verified for accuracy. …”
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Implementasi Indonesia National Single Window (INSW): Suatu pendekatan Business Intelligence System (BIS) by Muhammad Ibnu Fajar, Arief Rahman

“…Meanwhile, the dependent variable includes the implementation of Indonesia National Single Window (INSW) by Business Intelligence System (BIS) approach. …”
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Correlation Analysis of Radical Polymerization Reactor Operating Conditions to Industrial Scale Swelling Capacity of Superabsorbent by Willy Aulia Ilham, Teguh Kurniawan, Saepurahman Saepurahman, Ratna Sari siti Aisyah

“…The analysis determined that the variables that had the strongest correlation with the SC were retention time and reaction temperature, with correlation coefficient values of 0.31 and -0.26. …”
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Factors Influencing The Use of QRIS in Digital Transactions by Fadhil Muhammad, Arif Imam Suroso, Setiadi Djohar

“…Purpose: The purpose of QRIS is to expand the efficient acceptance of non-cash payments, focusing on traditional mass economic functions (such as traditional markets and MSMEs). …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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An improved robust variance inflation factor: Reducing the negative effects of good leverage points by Osman Ufuk Ekiz

“…It is defined as the function of the coefficient of determination between the explanatory variables, and it is based on the maximum likelihood estimator of the regression coefficients. …”
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Evaluation of Face Stability for Mega Tunnel Under Varying Ground Strength Parameters by Deshpande Shilpa, Hedaoo Namdeo

“…This study investigates the impact of various geological strength variables, such as Young’s modulus and coefficient of lateral earth pressure, on Mega Tunnel face stability. …”
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Exploring restoration efforts from a social lens: statistical models reveal relationships between salmon habitat restoration efforts and ecological and social characteristics of th... by Brittany D King, Robert Fonner

“…We specified statistical models to explain the variation in the number of restoration worksites undertaken in subwatersheds as a function of environmental and social variables. Using a common set of explanatory variables, we fit four models to examine the distribution of worksites associated with particular types of restoration actions (instream, riparian, land acquisition, and fish passage) and a fifth model to examine the distribution of all aquatic-based restoration worksites across action types. …”
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Bifurcations of Spatially Inhomogeneous Solutions of a Boundary Value Problem for the Generalized Kuramoto–Syvashinsky Equation by Alina V. Sekatskaya

“…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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