Kernel Density Estimation for Joint Scrambling in Sensitive Surveys by Alvan Caleb Arulandu, Sat Gupta

“…Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. …”
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Application of artificial neural network in deoxygenation of water by glucoseoxidase immobilized in calcium alginate/MnO2 composite by A. Abdi, M.Sh Izadkhah, A. Karimi, M. Razzaghi, H. Moradkhani

“…The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.…”
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Relationship Between Household Consumption and Disaggregated Wealth Components in OECD Countries: Panel Data Analysis for the Period 2010-2017 by Ahmet Hamdi Yanık, Ahmet İncekara

“…These tests indicate that the coefficients obtained using the augmented mean group estimator, which accounts for heterogeneity, are more reliable. …”
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PENDUGAAN FUNGSI KEUNTUNGAN DAN RISIKO USAHATANI SAWI PAHIT (Brasischa juncea) DI DESA SAMBIREJO KECAMATAN SELUPU REJANG KABUPATEN REJANG LEBONG by Satria Putra Utama, Redy Badrudin, Merry Rien

“…Result of this research showed that, the average of farmer’s profit from the bitter mustard farming in sambirejo village, rejang lebong region on planting season of May/Juni are Rp.914.382,33/farm or Rp.4.747.964,79/Ha, and planting season of Feb/Maret are Rp.1.025.509,72/farm or Rp.6.698.378,53/Ha. Variable which influenced negatively and  significantly  on profit function of bitter mustard farming in sambirejo village, Selupu Rejang district of Rejang Lebong region on planting season of Feb/Maret and May/Juni are the land fare (X8*), production amount (X9*) and dummy variable (season plant). whereas, variables which influenced negatively and unsignificantly are the price of seed (X1*), the price of urea (X2*), but the price of dursban (X5*) influence positively and also has tendency to increase the profit of bitter mustard profit. …”
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Fractional Dynamics of Laser-Induced Heat Transfer in Metallic Thin Films: Analytical Approach by M. A. I. Essawy, Reham A. Rezk, Ayman M. Mostafa

“…Dynamic profiles demonstrate the responsiveness of heat transfer to thermal and optical variables. The innovation resides in the meticulous analytical formulation utilizing a realistic laser source, the clear significance of the absorption parameter that enhances the temperature amplitude, the incorporation of the Mittag–Leffler function, and a comprehensive investigation of fractional photothermal effects in metallic nano-systems. …”
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A Predictive Model for Estimating Reservoir Impounding Time Based on the Net Inflow and Storage Volume by Harimukti Rosita R., Pitojo T. Juwono, Lily M. Limantara, Emma Yuliani

“…By using the base equation of linear regression: Ln(D)=m×Ln(S)+n×Ln(Inet) and based on the analysis result of 28 combinations, there is selected the combination with the best determination coefficient (R2) that is 0.99 with m = 1.047 and n = -1.08807. …”
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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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Sparse Learning of the Disease Severity Score for High-Dimensional Data by Ivan Stojkovic, Zoran Obradovic

“…This problem is solved by addressing a dual formulation which is smooth and allows an efficient optimization. The proposed approach might be used as an effective and reliable tool for both scoring function learning and biomarker discovery, as demonstrated by identifying a stable set of genes related to influenza symptoms’ severity, which are enriched in immune-related processes.…”
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Translation and validation of Gujarati version of Indian HAQ in RA patients by Jaspreet Kaur Kang, Neeta J Vyas

“…Results: Internal consistency of each item was evaluated by Cronbach's alpha and the Construct validity was evaluated by determining Spearman's correlation between the Gujarati Indian HAQ score and disease activity variables. Reliability testing showed an intraclass coefficient for HAQ of 0. 848. …”
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Analysis of fuzzy TOPSIS Method in Determining Priority of Small Dams Construction by Desyta Ulfiana, Suharyanto Suharyanto

“…The first step was determining membership function and weighting each criteria. Then, TOPSIS method was applied to ranked eight alternatives. …”
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Three-Dimensional Modified Cross-Section Hydrofoil Design and Performance Study by Hongpeng Cao, Yudong Xie, Zilei Ji

“…To improve the hydrodynamic performance of hydrofoils, this study combines the shape characteristics of flat and elliptical wings, uses parabolic function to fit the leading and trailing edges of hydrofoils, introduces the cross-section coefficient <i>λ</i> to characterize the cross-sectional size of hydrofoils along the spreading direction, and designs five hydrofoils with different cross-sections. …”
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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. …”
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Determinants of growth differentiation factor 15 plasma levels in outpatients with peripheral arterial disease by Emma Skau, Philippe Wagner, Jerzy Leppert, Johan Ärnlöv, Pär Hedberg

“…Results: The multivariable analysis identified independent relations of GDF-15 with several of the included variables (adjusted R2 = 0.48). Diabetes (beta coefficient [β] of 0.37, 95% confidence interval [95% CI] 0.25 to 0.50), low-density lipoprotein (LDL) cholesterol (β = −0.22, 95% confidence interval [CI]: −0.34 to −0.09), and physical activity (β = −0.16, 95% CI: −0.25 to −0.06) had the strongest associations. …”
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THE BONITATION METHOD FOR ASSESSING THE FERTILITY OF THE CHERNOZEM by Mariana BURCEA, Nicoleta OLTENACU

“…Statistical indicators have been determined using the functions from Excel Program, such as: average, standard deviation, coefficient of variability, annual growth rate. …”
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Analyzing Worn-Out Texture Regeneration from Urban Branding Perspective Using Structural Equation Modeling (SEM) (Case Study: Worn-Out Texture of Shahr-e-Kord) by Dvood Mahdavi, Ali Mohammadi Gojani, Waliullah Nazari

“…Furthermore, the findings demonstrated a strong, positive, and significant influence of the branding variable on the regeneration of the worn-out urban fabric with an impact coefficient of 0.833. …”
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Optimization by RSM of reinforced concrete domes with meridian ribs, under static loading. by Logzit N., Raouache E., Bentoumi M., Bentoumi A., Khababa I.

“…Ultimately, a cost-oriented objective function is derived, incorporating a load-bearing capacity coefficient. …”
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COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) by Yuniar Farida, Ida Purwanti, Nurissaidah Ulinnuha

“…The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. …”
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Sexuality Assessment in Women Diagnosed with Ovarian Cancer by Patricio Jaramillo Guerrero, Edison Enrique Sotalin Nivela, Eduardo Leonel Alvarado Pico

“…<br /><strong>Objective:</strong> to evaluate sexuality in women diagnosed with ovarian cancer, with central interest in changes in sexual function, sexual desire, sexual satisfaction and sexual problems related to the disease and its treatment. …”
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Assessing the effect of dynamics of unpredictable locust invasive behavior and its effect on food security and community livelihood by Mfano Charles Petro

“…Additionally, it was observed that the deterrent coefficient in the invaded and source zones (ηi and ηs) has a significant impact on controlling the dynamic behavior of locusts.…”
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Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

“…Based on such datasets, LSSVR is capable of generalizing a multivariate function that estimates values of pile bearing capacity based on a set of variables describing pile characteristics and ground conditions. …”
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