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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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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Relación entre comunidad íctica y cobertura vegetal riparia en dos períodos hidrológicos (Eje Cafetero, Colombia) by María Angélica Pérez-Mayorga, Saúl Prada-Pedreros

“…Therewere no significant differences (P>0.05) among the structural variables, the HYPE and the RVC. According to r and r2 the diet of most fish species did not vary as a function of RVC and HYPE; however, according to the CCA diet varies as a function of HYPE but not of RVC. …”
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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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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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Faktor-Faktor Yang Mempengaruhi Pertumbuhan Ekonomi Di Jawa Timur Dengan Pendekatan Spatial Regression by Rendra Erdkhadifa

“…The research results show that the weighting function used is fixed gaussian, and the spatial model has a coefficient of determination of 92.97%. …”
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Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms by Nurcan Öztürk

“…In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function.…”
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带传动软启动装置蜗杆的优化设计 by 赵江平

“…By the mechanical analysis of the belt drives soft-start equipment,tow-objective function is established with the worm axial modulus and spiral angle as the independent variables.Based on self-locking constraint and fuzzy constraint conditions,constraint subset is established.Compared with the general design parameters,the rustle shows that the spiral angle is increased and the worm axial modulus is decreased.The test shows that the optimize design effectively improve the transmission efficiency,and reduce the minimum power of the speed adjustment motor.…”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…These parameters function as decision variables, and the objective function aimed for minimization is the sum square error (SSE) between the predicted and actual measured cell voltages. …”
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Impact of Product, Process, Organisational, and Marketing Innovation on Micro, Small and Medium Scale Enterprises' Sustainability by Erna Listyaningsih, Yuliansyah Yuliansyah, Rissa A. Martinouva, Febrianty Febrianty, Muazza Muazza, Shofia Amin, Etty Puji Lestari, Amirul Mukminin

“…Objective: This study aimed to investigate how innovation, sustainability, and performance function as moderators in Micro, Small, and Medium-Scale Enterprises (MSMES). …”
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A Combined Approach to Solving Applied Metal Forming Problems by Matvej Baldin, Nikita Kondratev, Peter Trusov, Kirill Ostapovich

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