Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method by Jun Zhang

“…The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. …”
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System Modeling to Optimize the Production Quantity of Men's and Women's Jackets and Achieve Maximum Profit: A Case Study at Konveksi ABC Cikarang Using Linear Programming by Wisnu Aji

“…The objective function is designed to maximize profit, and the model is solved using IBM ILOG CPLEX software. …”
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Removal of <i>para</i>-Phenylenediamine (PPD) Dye from Its Aqueous Solution by Adsorption Using the Activated Carbon Nanoparticles by Shabaa Fayyad Bdewi, Hanaa Hassan Hussein, Shireen Abdulmohsin Azeez

“…This study focused on the development of an efficient preparation method of activated carbon for the removal of para-phenylenediamine (PPD) dye in an aqueous solution. …”
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Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

“…An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. …”
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Insights into the Estimation of the Enhanced Thermal Conductivity of Phase Change Material-Containing Oxide Nanoparticles using Gaussian Process Regression Method by Tzu-Chia Chen, Hasan Sh. Majdi, Aras Masood Ismael, Jamshid Pouresmi, Danial Ahangari, Saja Mohammed Noori

“…In the following, a sensitivity analysis (SA) is used to explore the effectiveness of variables in terms of outputs and shows that the temperature (T) of nanofluid (NF) is the most efficient input parameter. …”
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Stability analysis of grid-connected hydropower plant considering turbine nonlinearity and parameter-varying penstock model by Chen Feng, Na sun, Chuang Zheng, Yongqi Zhu, Nan Zhang, Yahui Shan, Liping Shi, Xiaoming Xue

“…The nonlinear state space equations of GCHTGS with PVM and variable transfer coefficients are established. First, the influence of different penstock models on stability is investigated, and the comparison results show that the proposed PVM has a more precise stability region. …”
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Immunological Avalanches in Renal Immune Diseases by Davide Viggiano, Pietro Iulianiello, Antonio Mancini, Candida Iacuzzo, Luca Apicella, Renata Angela Di Pietro, Sarah Hamzeh, Giovanna Cacciola, Eugenio Lippiello, Andrea Gigliotti, Carmine Secondulfo, Giancarlo Bilancio, Giuseppe Gigliotti

“…Two distinct dynamic patterns emerged: large oscillations in eGFR, proteinuria, or biological age predicted declining function, while small oscillations indicated stability. …”
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Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects by Ahmed Zeeshan, Majeed Ahmad Yousif, Muhammad Imran Khan, Muhammad Amer Latif, Syed Shahzad Ali, Pshtiwan Othman Mohammed

“…Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The Kolmogorov-Arnold Network (KAN) is a computational framework rooted in the Kolmogorov-Arnold representation theorem, which states that any continuous function of multiple variables can be expressed as a superposition of univariate functions. …”
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Stochastic Analysis of Nonlinear Vehicle-Track Coupled Dynamic System and Its Application in Vehicle Operation Safety Evaluation by Fu-Shan Liu, Zhi-Ping Zeng, Wei-Dong Wang, Abdulmumin Ahmed Shuaibu

“…The nonlinear coupled vehicle-track dynamic system is used to accurately describe the wheel-rail contact state. The stochastic function-spectral representation is used to simulate the random track irregularity in the time domain for the first time; consequently, the frequency components in the irregularity are preserved and random variables are reduced. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Under the BIA, an alpha coefficient (α) of 15% is applied, whereas in the SA, each business line has a specific beta coefficient (β) ranging between 12% and 18%. …”
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qDESH: a method to quantify disproportionately enlarged subarachnoid space hydrocephalus by Sofia Behndig, Afroditi Lalou, Jan Axelsson, Jenny Larsson, Anders Wåhlin, Pavel Ryska, Ondrej Slezak, Katrine Riklund, Jan Zizka, Jan Malm, Anders Eklund

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Development and validation of a novel prediction model for osteoporosis: from serotonin to fat-soluble vitamins by Jinpeng Wang, Lianfeng Shan, Jing Hang, Hongyang Li, Yan Meng, Wenhai Cao, Chunjian Gu, Jinna Dai, Lin Tao

“…Stepwise discriminant analysis was performed to identify efficient predictors for osteoporosis. The prediction model was developed based on Bayes and Fisher’s discriminant functions, and validated via leave-one-out cross-validation. …”
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Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass by J. Meloche, N. R. Leroux, B. Montpetit, V. Vionnet, C. Derksen

“…This method, called radar-equivalent snowpack, is based on a <span class="inline-formula"><i>k</i></span>-means clustering algorithm to group the snow layers based on the extinction coefficient and a weighted average using the optical thickness applied to the snow properties. …”
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Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Farshad Ahmadi, Rasoul Mirabbasi, Ali Torabi Haghighi

“…The Pearson’s correlation coefficient (PCC) and Cosine Amplitude Sensitivity (CAS) as feature (input) selection process determine the only precipitation (P m ) as the most effective input variable among a list of on-site potential climate time series parameters recorded in the study area. …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The input solar PV power data are broken down into intrinsic mode functions (IMFs) using EMD technique is fed into the PSO-ANFIS, along with important meteorological variables. …”
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Predicting the Probability of Failure in Truss Structures Using Artificial Neural Networks by Mohammadreza Gholami, Seyed Ahmad Mobinipour, Mohammad Javad Haji Mazdarani, Seyed Rohollah Hoseini Vaez

“…The limitation of node displacement is considered as a limit state function. The data was split as 60% for training and 40% was used for testing and validation. …”
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Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits. by Mohsen Yoosefzadeh-Najafabadi, Dan Tulpan, Milad Eskandari

“…The RBF algorithm with highest Coefficient of Determination (R2) value of 0.81 and the lowest Mean Absolute Errors (MAE) and Root Mean Square Error (RMSE) values of 148.61 kg.ha-1, and 185.31 kg.ha-1, respectively, was the most accurate algorithm and, therefore, selected as the metaClassifier for the E-B algorithm. …”
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An Investigation of Knee Injury Prevalence and its Mechanism among Premier League Soccer Referees in Iran by Hamid Mahdavi Mohtasham, Shahnaz Shahrbanian

“…Using the Pearson correlation coefficient, this study examined the relationships between different variables including KOS subscales as well as the current level of self-reported knee joint function and proprioception. …”
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Analysis of Mobile JKN Application Service Quality With E-GovQual Method and IPA by Randy Rizki Ananda, Indriani Noor Hapsari

“…The results of the coefficient of determination (R-Square) show that overall, the variables of ease of use, reliability, trust, content and appearance, functionality and interaction and citizen support significantly affect service quality by 88.6%. …”
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