Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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ANALYSIS OF CONTACT LOADS CONCENTRATION IN PRESSURE COUPLINGS OF THIN-WALL COMPONENTS by S. V. Shishkin

“…Deviations of the shape of the contact surfaces from the straightness are taken into account by its respective pressure coupling function. The analysis of the findings suggests that the concentration coefficient value slumps as the contact compliance coefficient of the borderline layer increases. …”
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Investigation of Effective Factors to Reduce Natural Disaster Risks through Public Participation

“…Results from Pearson Correlation Coefficient indicated that independent variables, i.e., Social Sympathy, Feelings of Inability, Intellectual Function, Level of Awareness (from a given event) and Socio - economic Status, were significantly related to the dependent variable, namely, cooperation in decreasing risks from natural disasters. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The dataset included 768 instances with nine attributes, where the target variable indicated whether a patient tested positive for diabetes. …”
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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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The effects of IT capability and distribution competence on business performance of retailers in Omnichannel by Anh T.D. Nguyen

“…Results: Information technology capability and distribution competence have a direct impact on business performance, with beta coefficients of 0.198 and 0.271, respectively. Meanwhile, the regression coefficients of indirect relationships through mediating variables are 0.204 and 0.097, respectively. …”
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The Impact of Land Circulation on Common Prosperity in the Digital Economy Context by Cong Xu, Feng Wu, Jingran Lin, Yie-Ru Chiu

“…It finds that land circulation is consistent with the theory of the siphoning effect. DE (DE) variables accelerate the circulation of information factors and improve the allocative efficiency of land, technology, and capital factors. …”
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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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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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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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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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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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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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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

“…This analysis has been carried out using the RNG k-epsilon turbulence model with standard wall function in ANSYS FLUENT 2022R1. The impact of various flow conditions and nanofluid concentrations has been examined. …”
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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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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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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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