Evaluation of Face Stability for Mega Tunnel Under Varying Ground Strength Parameters by Deshpande Shilpa, Hedaoo Namdeo

“…This study investigates the impact of various geological strength variables, such as Young’s modulus and coefficient of lateral earth pressure, on Mega Tunnel face stability. …”
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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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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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Fuzzy Controller Design Optimized by the Grasshopper Algorithm to Realize Maximum Power in Photovoltaic Systems by Kamran Safaei, Aida Esmaeilian-Marnani, Hossein Emami, Amir Hossein Zaeri

“…For improvement of the controller performance and achievement of the maximum power, the fuzzy controller variables are improved by the Grasshopper Optimization Algorithm (GOA). …”
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Effect of a mix of condense and hydrolysable tannins feed additive on lactating dairy cows’ services per conception and days open by Alejandro R Castillo, Julio A Di Rienzo, Damiano Cavallini

“…Services per conception was modeled as a Poisson count using a generalized linear model with log link function. Days open was modeled with a generalized linear model for a gamma variable with log link function. …”
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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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Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

“…Two types of inputs were evaluated: regular variables (Type I) and dimensionless groups derived from these regular variables (Type II). …”
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Preventive-Corrective Control for Static Voltage Stability Under Multiple <tex>$N-1$</tex> Contingencies Considering Wind Power Uncertainty by Yuerong Yang, Shunjiang Lin, Qiong Wang, Mingbo Liu, Qifeng Li

“…The chance constraints of the static voltage stability margins (SVSMs) in the normal operation state and after each <tex>$N-1$</tex> contingency are included. The approximate functions between the probability density functions (PDFs) of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SVSM chance constraints into deterministic expressions. …”
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Investigating wave solutions in coupled nonlinear Schrödinger equation: insights into bifurcation, chaos, and sensitivity by Adil Jhangeer, Abdallah M. Talafha, Ariana Abdul Rahimzai, Lubomír Říha

“…The transformation of the coupled partial differential equation into ordinary differential equation is achieved by utilizing a complex wave variable. Exponential function combinations are applied to construct the wave solutions. …”
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Evaluasi Kinerja Aplikasi Penelusuran Online Cerah Informasi Pustaka (CIP) Perpustakaan Universitas Tridinanti Palembang Berdasarkan Persepsi Pustakwan by Rusmiatiningsih Rusmiatiningsih, Indah Solehati, Sagiman Sagiman, Marleni Marleni

“…The evaluation model used is the PIECES evaluation model by making a questionnaire based on 6 variables, namely Performance, Information, Economy, Control, Efficiency and Service and each variable is made into indicators. …”
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An Intelligent Inspection and Scheduling Algorithm for Integrated Pipe Gallery Based on Cloud Robot by ZHOU Xiwei, SHANG Xiao, SHANG Xinjuan, YAN Maode, WANG Fafa

“…The algorithm has very strong exploring precision and variable function, which makes this algorithm of fewer iterations, and can effectively improve the real-time detection of pipeline leakage source in pipeline corridor. …”
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Path following control of underground mining articulated vehicle based on the preview control method by MENG Yu, GAN Xin, BAI Guo-xing

“…The path following control system is a multi-variable, multi-constraint system. There are optimization problems under multiple constraints as well as challenges such as actuator saturation during the control process. …”
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Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA by Xucheng Chang, Jingyu Wang, Kang Li, Xinhui Zhang, Qian Tang

“…Confronted with the difficulty of balancing calculation speed and accuracy in the DWA algorithm, a dynamic time step adjusted according to the environment was designed to weigh the computational efficiency. Aiming at the poor environmental adaptability of the DWA algorithm, a trajectory evaluation function with variable weights was put forward to improve environmental fitness. …”
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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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Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. …”
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The performance of 76 kHz positional acoustic telemetry is challenged by acoustic conditions in the tailrace of a hydroelectric dam by C. Ryan Hill, Antóin M. O’Sullivan, R. Allen Curry, Tommi Linnansaari, Philip M. Harrison

“…Performance improved marginally for the second array (i.e., 200–500 m downstream), but position efficiency was ultimately low (1%), variable across transmitter locations, and negatively correlated with discharge. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…The resulting objective function is highly nonlinear and complex. To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The Lasso function is used for elastic net regression analysis to evaluate the impact of design variables on the objective functions. …”
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