A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…Secondly, a two-stage feature-selection method is employed, in which the partial autocorrelation function (PACF) is used to select relevant lagged features, while the maximal information coefficient (MIC) is applied to identify key variables from both historical and external data. …”
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Donor Parameters and Platelet Yield during Plateletpheresis: A Cross-sectional Prospective Study by Ruchi Singh, Ganga S. Pilli, Ramadevi Vivek Wani

“…A relationship between pre-donation donor variables and platelet yield was studied using the Pearson correlation coefficient (r). …”
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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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Modeling Overall Survival in Patients With Pancreatic Cancer From a Pooled Analysis of Phase II Trials by Eva Rahman Kabir, Faruque Azam, Tanisha Tabassum Sayka Khan, Hasina Yasmin, Namara Mariam Chowdhury, Syeda Maliha Ahmed, Baejid Hossain Sagar, Nasrin Ahmed Tahrim

“…The relationship between predictors and OS was explored by a gamma generalized linear model (GLM) with a log‐link function and compared with linear models. Results The Spearman rank correlation coefficient between PFS/TTP and OS was 0.88 (95% confidence interval [CI] 0.85–0.89; p < 0.0001; n = 610) and between ORR and OS was 0.58 (0.52–0.64; p < 0.0001; n = 514). …”
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A Predictive Model for Estimating Reservoir Impounding Time Based on the Net Inflow and Storage Volume by Harimukti Rosita R., Pitojo T. Juwono, Lily M. Limantara, Emma Yuliani

“…The initial impounding of a reservoir represents the first test following the completion of dam construction, during which the reservoir begins to function as intended. Therefore, the expected outcome of this research is to formulate a model that estimates the duration required to fill the reservoir to its designated storage level. …”
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Solving Linear Programming Problems by Reducing to the Form with an Obvious Answer by Gleb D. Stepanov

“…From the coefficients of the mentioned functionals, a matrix is formed, which is called the LPP matrix. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In addition, the closed-form solutions of the optimized variables are obtained. Simulation results demonstrate that the proposed collaborative training scheme based on D2D can reduce the impact of heterogeneity on FL model performance and IRA can effectively reduce energy consumption while simultaneously enhancing training efficiency of FL.…”
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Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents by Zhifeng Zhou, Long Qian, Jinping Xu, Yumin Lu, Fen Hou, Jingyi Zhou, Jinpei Luo, Gangqiang Hou, Wentao Jiang, Hengguo Li, Xia Liu

“…Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. …”
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Impact of viscous dissipation, chemical reaction over a Carreau hybrid nanofluids flow across a permeable curved Riga surface by R. Mahesh, U.S. Mahabaleshwar, Basma Souayeh

“…Subsequently, the original partial differential equations are transformed using boundary layer approximations and similarity variables to produce a dimensionless ordinary differential equation. …”
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Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…The water production rate and the total annual cost rate were considered as two objective functions. Also, five design variables are selected after considering their effects on the objective functions. …”
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Time-Jerk Optimal Robotic Trajectory Planning Under Jerk and Continuity Constraints via Convex Optimization by Chen Qian, Jianjun Yao, Yikun Zhang

“…Additionally, the objective function is improved to optimize both time and joint jerk simultaneously. …”
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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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A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm by Mahdi M. M. El-Arini, Ahmed M. Othman, Ahmed Fathy

“…The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. …”
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A Three-Block Inexact Heterogeneous Alternating Direction Method of Multipliers for Elliptic PDE-Constrained Optimization Problems with a Control Gradient Penalty Term by Xiaotong Chen, Tongtong Wang, Xiaoliang Song

“…In some practical applications, it is necessary to smooth the control variables and suppress their large fluctuations, especially at the boundary. …”
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Optimization of Aerodynamic Design of a Winged UAV Through Genetic Algorithms and Large Eddy Simulation by Mohammad Javad Ebrahimi, Mahmoud Pasandidehfard, Ali Esmaeili, Mohammad Hossein Moghimi Esfandabadi

“…Optimization was conducted for six variables in a single stage, with 25 tests performed. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Optimal tuning of multi-PID controller using improved CMOCSO algorithm by Ying Hu, Xiongyan Liu, Hao Chen

“…In this model, the parameters are designated as decision variables, the performance index serves as the objective function, and the stability constraints of the system are incorporated. …”
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Performance Investigation of Coated Carbide Tools in Milling Procedures by Paschalis Charalampous

“…The optimization of the manufacturing conditions in milling processes composes a crucial task for enhancing machining efficiency and extending the tool’s lifespan. This study presents an investigation of the cutting tool’s performance under varying machining parameters via the generation of an experimental dataset that was obtained through laboratory-controlled milling operations. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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Understanding the Role of Organic Hole Transport Layers on Pinhole Blocking and Performance Improvement in Sb2Se3 Solar Cells by Thomas P. Shalvey, Christopher H. Don, Leon Bowen, Tim D. Veal, Jonathan D. Major

“…After successive record‐efficiencies using a range of device structures, spiro‐OMeTAD has emerged as the default hole transport material (HTM), however, the function of HTM layers remains poorly understood. …”
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