Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…Performance metrics such as accuracy, precision, recall, Matthews Correlation Coefficient, ROC Area, and F1-measure were used to compare the classifiers. …”
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SYNTHESIS OF QUASI BAND LADDER TRANSFORMING HIGH ORDER FILTERS by A. E. Kurochkin

“…To achieve this goal, all the synthesis tasks were solved, including the choice of the prototype, frequency transposition, calculation of the poles of the transfer function of the prototype, calculation of the poles of the transfer function of the filter, calculation of the reflection coefficient of the filter, the calculation of the input resistance of the filter, the implementation of the ladder chain by the Cauer method and denormalization of the values of the elements of the ladder chain. …”
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Modelling and optimisation of solar photovoltaic power using response surface methodology by Abdulrahman Mohammad, Mudhar Al-Obaidi, Hassan Dakkama, Haitham Bahlol

“…The response surface methodology model has indicated a linear relationship between the independent variables and power generated with a coefficient of determination of 98.45%. …”
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Evaluation of Multiparameter Likelihoods through Iteration of Two-dimensional Slices by Joel S. Jayson

“…Markov Chain Monte Carlo (MCMC) computation has been the dominant instrument for evaluating multiparameter functions. For applications with a quasi-linear variable such as, A _s , the 2D iterative method is orders of magnitude more efficient than MCMC.…”
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Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study by M.-C. Casabán, J.-C. Cortés, J.-V. Romero, M.-D. Roselló

“…The study is based on Random Variable Transformation method. The obtained results are given in terms of the probability density functions of the data, namely, initial condition, forcing term, and diffusion coefficient. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…SCR model estimates of abundance, the density-covariate coefficient β and the movement-related scale parameter of the detection function σ were robust to ignoring temporal variation in detection, with relative bias, CV and RMSE of the two models generally being within 4% of each other. …”
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ANALYSIS AND OPTIMIZATION OF QUICK-RETURN CHARACTERISTICS OF THE BEATING⁃UP SLEY BASED ON MULTIVARIABLE DESIGN by QIU HaiFei

“…For improving the quick‑return characteristics of the sley movement,an optimal mathematical model for maximum curve displacement Sm of the connectingarm pin was proposed through beating‑up principle analysis and mechanism deduction.A multivariable design space was constructed by use of the component length(lc,lh,lr,lf)and crankangleα.The parametric functional model development of the four‑bar beating‑up with short connecting rod was realized,and its kinematic posture and centroid trajectory were analyzed and verified through mechanism simulation.The results of the case study indicate that the variable lc andαhave more greater influence on the sensitivity of the objective function F(X),and multivariable(DV_1,DV_2,DV_3)coupling can effectively enhance the design plasticity of the quick‑return characteristics of the sley.When the maximum curve displacement Sm of the connectingarm pin increases to 71.41 mm,the extreme position angleθand the travel speed ratio coefficient K are increased by 10.96°and 0.131 respectively,and the quick-return motion effect of the sley is obviously improved.The optimization results accord with the conditions of rod length and mechanism transmission requirement,which are conductive to the design innovation and performance improvement of the four‑bar beating‑up system.…”
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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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The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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PENGARUH MUTASI TERHADAP SEMANGAT KERJA PEGAWAI NEGERI SIPIL PADA KANTOR PELAYANAN PAJAK PRATAMA KOTA PEMATANG SIANTAR by Arnimisari Juliana Ambarita, Hatta Ridho

“…The data processed by the correlation coefficient and the determinant Moment Product to see the great influence of the variable X against Y variable. …”
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First-principles investigation on structural, electronic, and optical properties of (Cd1-xZnx)3As2 by Yu Deng, Xun Ge, Rongxiu Feng, Yunye Liang, Xiaohao Zhou

“…Calculations on the optical properties (dielectric function, absorption coefficient) of (Cd1-xZnx)3As2 show that it behaves well in the near infrared and far infrared. …”
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Estimating Daily Rice Crop Evapotranspiration in Limited Climatic Data and Utilizing the Soft Computing Algorithms MLP, RBF, GRNN, and GMDH by Pouya Aghelpour, Hadigheh Bahrami-Pichaghchi, Farzaneh Karimpour

“…The ETc rates were calculated by seven meteorological variables, the FAO-56 Penman-Monteith equation, and the regional calibrated rice crop coefficient and considered as the reference data. …”
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Enhancing Thermal–Hydraulic Performance in Nuclear Reactor Subchannels with Al₂O₃ Nanofluids: A CFD Analysis by Mohammad A. I. Sardar, Mushfiqur Rahman, Philip Rubini

“…The result shows a gradual enhancement in the heat transfer coefficient with increasing volume concentrations and Reynolds numbers. …”
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Multivariate predictive modeling of compressive strength in ground granulated blast furnace slag/fly ash-based alkali-activated concrete by Dina A. Emarah

“…Using a comprehensive dataset of 1590 samples with 14 input variables, it captures the complex, multi-variable dependencies affecting AAC's mechanical behavior. …”
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Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

“…The diffusion coefficient extracted from the moisture ratio function was used to assess the drying kinetics, while SEC was used to evaluate the energy efficiency of the EHD dehydrator under different parameter settings. …”
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The Model of Fundamental Chemical Training of Bachelors of Technical and Technological Directions in the Conditions of Blended Learning by N. M. Vostrikova

“…The concept and the structural-functional model of the fundamental chemical training of bachelors in the information-and-activity-based educational environment of blended learning have been proposed. …”
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Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…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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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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How to personalise ventilation of infants with congenital diaphragmatic hernia? A simulation study by Barbara Stankiewicz, Magdalena Mierzewska-Schmidt, Krzysztof J. Pałko, Marek Darowski, Maciej Kozarski

“…The T1/T2 and CW/CL correlated with defect size (gamma coefficient: 1; P < 0.05), duration of mechanical ventilation and hospitalization (Spearmen’s coefficient: 0.99; P < 0.01). …”
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