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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Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…To further improve computational efficiency of comeSn_JFNK, in the JFNK solution, neutron scalar fluxes instead of neutron angular fluxes were chosen as the global solution variables. …”

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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Mitigating Load Imbalance and Enhancing Distribution Transformer Performance via Fuzzy Inference System by Althoff Hibban, Azriyenni Azhari Zakri, Dirman Hanafi, Boy Ihsan, Umair Ali

“…To address this issue, this study proposes a fuzzy logic-based approach using a Mamdani-type Fuzzy Inference System (FIS). The input variables, current magnitudes in phases R, S, and T, are represented by trapezoidal membership functions classified into several categories. …”
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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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GDP per capita vs foreign direct investment: key drivers of a country's technological leadership by Aleksy Kwilinski

“…A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. …”
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Enhanced Stability and Control of Solar Powered EV Charging Stations Using Disturbance Observer-Based Adaptive Sliding Mode Control for DC Voltage Stabilization by Surabhi Bagherwal, Subhasish Mahapatra

“…To address the chattering issue, a barrier function based SMC (BFSMC) approach is proposed. The distinctive aspects of this BFSM control approach is its capability to stabilize the designed sliding variable to a predefined neighbourhood around the origin within a limited duration, eliminating the need for prior understanding of the maximum limit of the lumped disturbance. …”
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AESware: Developing AES-enabled low-power multicore processors leveraging open RISC-V cores with a shared lightweight AES accelerator by Eunjin Choi, Jina Park, Kyuseung Han, Woojoo Lee

“…And importantly, we propose the most energy-efficient architecture for multicore processors equipped with AESware. …”
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Autonomous obstacle avoidance of underground coal mine transport robots based on intrinsic motivation reinforcement learning algorithm by ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui

“…Existing robot obstacle avoidance methods mostly rely on preset rules or external reward signals, making it difficult to adapt to the complex and variable underground environment in coal mines. To achieve autonomous and efficient obstacle avoidance for underground coal mine transport robots, an autonomous obstacle avoidance method for underground coal mine transport robot based on Intrinsic Motivation Reinforcement Learning (IM-RL) algorithm was proposed. …”
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Optimization of Sparse Concentric Ring Arrays for Low Sidelobe by Kesong Chen, Yafei Li, Jiajia Shi

“…The MGA uses real number to code the optimization variable, and it reduces the complexity of coding and improves the search efficiency. …”
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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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Estimation of Total Suspended Solids Concentration in Streams Using Regression and Artificial Neural Networks Methods by Betül Mete, Sinan Nacar, Adem Bayram, Osman Tuğrul Bak

“…Root mean square error, mean absolute error, and Nash-Sutcliffe (NS) efficiency coefficient statistics were used to evaluate the model and method performances. …”
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Design and Simulation of Ornithopter based on Four-bar Mechanism by Zhao Zhifang, Qi Mingsi, Feng Jingkai, Zhang Wei, Wang Junyuan, Zhang Jiping

“…The brushless motor driving two stage reducer,provides input for four-bar mechanism. The robot has a function of the periodic flapping motion,the frequency change and size of the attitude angle adjustment. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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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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