Design and evaluation of BOOGIE: a collector for the analysis of cloud composition and processes by M. Vaitilingom, M. Vaitilingom, C. Bernard, M. Ribeiro, C. Verhaege, C. Verhaege, C. Gourbeyre, C. Berthod, A. Bianco, L. Deguillaume, L. Deguillaume

“…<p>In situ cloud studies are fundamental to study the variability in cloud chemical and biological composition as a function of environmental conditions and assess their potential for transforming chemical compounds. …”
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A Reliable Approach for Solving Transmission Network Expansion Planning with Objective of Planning Cost Reduction by Yongqiu Liu

“…The candidate plans are evaluated using a fitness function that considered objective function for transmission expansion planning problem is composed of two terms. …”
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Effects of Different Irrigation Regimes on Root Growth and Physiological Characteristics of Mulch-Free Cotton in Southern Xinjiang by Feiyan Su, Ziyang Guo, Bingrong Wu, Jichuan Wang, Shuangrong Chen

“…It can be concluded that no mulching has a certain impact on cotton root distribution and leaf physiological function. When the irrigation amount is 450–525 mm and irrigation times is 10–12, it is beneficial for promoting root growth and plays a role in leaf physiological function, and the water use efficiency (WUE) is high, which can provide reference for the scientific water management of mulch-free cotton in production practice.…”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…The accurate identification of weed type and density is crucial for its efficiency. In this study, we propose the ensemble of the lightweight deep neural networks, namely EfficientNetV2B0 and DenseNet121 for weed identification in the groundnut crop. …”
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Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor by Jun Yang, Xian-yu Wu, Zhen-guo Wang

“…The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. …”
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Why is Multi-Business Forestry Needed to Overcome the Low Performance of Forestry Governance and Food Security in Indonesia? by Suryanto Suryanto, Dodik Ridho Nurrochmat, Suria Darma Tarigan, Iskandar Zulkarnaen Siregar, Ishak Yassir, Mangarah Silalahi, Irdika Mansur, Rhett D. Harisson, Agus Wahyudi, Lutfy Abdulah

“…Results showed that CLD formulated in 280 sub-models in a total of 4,764 decision variables with an error deviation of 6.4%. The SM Mb-F simulation on two sample concession units produces a projected increase in wood supply, employment, and state revenue, plus the provision of new functions such as food, NTFP, and environmental services. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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Supplier Selection and Order Allocation in A Pharmaceutical Wholesaler by Ryan Hikmah Fadilla, Cucuk Nur Rosyidi, Wakhid Ahmad Jauhari

“…As part of the system modeling, a sensitivity analysis was performed to explore the effects of specific parameters on the objective function and decision variables, assessing variations in inventory costs, shortage costs, and demand. …”
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Predictive model of small choroidal melanoma progression after eye-saving treatment based on clinical, morphometric and immunological parameters by E. B. Myakoshina, I. G. Kulikova, N. V. Balatskaya, L. A. Katargina, S. V. Saakyan

“…A formula was calculated where P (z) is the value of the logistic function; Z, linear combination of symptoms; bo , intercept (free term), bi – regression coefficients for parameters Zi.P (z) = 1 : 1 + e – b0– b1z1– b2z2– b3z3– b4z4The logistic function increases monotonically and takes the values from 0 to 1 for any b and Z values [P∈ (0;1)]. …”
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Optimization of the Screw Conveyor Device Based on a GA-BP Neural Network by Qiang Guo, Yunpeng Zhuang, Houzhuo Xu, Wei Li, Haitao Li, Zhidong Wu

“…In this paper, we analyze the force and velocity components acting on the straw, give the design principles for the screw’s conveying parameters under the premise of ensuring maximum conveying capacity and minimum power consumption, and determine the optimal design variables, objective functions, and constraints according to the specific optimization problem; we establish a specific mathematical model, and introduce algorithm optimization for nonlinear problems with many variables and large amounts of calculations. …”
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Investigating the relationship between the monetary policy shock through the exchange rate channel on the management quality index in the banking system: by examining the productiv... by Farhad Sharifi Bagha, Jafar Haqiqat, Zahra Karimi Takanloo

“…During this time, the number of changes in the target variables by the variables themselves decreases and the changes in the variables caused by the shock of the exchange rate channel increase. …”
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Market orientation and corporate performance of small and medium-sized enterprises in Saudi Arabia by Nabil Mohamed Abdo Alabsy

“…Corporate performance is a dependent variable, whereas business orientation, competitor orientation and inter-functional orientation are used as independent variables. …”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…Horizontal well fracturing technology, as a core tool for efficient development of tight oil and gas reservoirs, is of strategic significance for enhancing the recovery rate of unconventional oil and gas resources. …”
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Impact of pulmonary rehabilitation in sleep in COPD patients measured by actigraphy. by Suman B Thapamagar, Kathleen Ellstrom, James D Anholm, Ramiz A Fargo, Nagamani Dandamudi

“…Paired comparisons (t-test or Wilcoxon-signed-rank test) were performed before and after PR data on all variables.<h4>Methods</h4>This retrospective study of COPD patients undergoing PR utilized actigraphy watch recordings before and after 8-weeks of PR to assess changes in sleep variables including total time in bed (TBT), total sleep time (TST), sleep onset latency (SOL), sleep efficiency (SE), wakefulness after sleep onset (WASO) and total nocturnal awakenings. …”
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Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…Through an approximation of the nonparametric functions with free-knot splines, we develop a Bayesian sampling approach that can be applied by the Markov chain Monte Carlo (MCMC) approach and design an efficient Metropolis–Hastings within the Gibbs sampling algorithm to explore the joint posterior distributions. …”
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Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

“…This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Taking these process parameters (<italic>x</italic>, <italic>y</italic>, <italic>z</italic>, <italic>d</italic>, <italic>h</italic>, <italic>n</italic>, <italic>a</italic>_p, <italic>a</italic>_e, <italic>f</italic>_z) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. …”
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Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…Abstract The hierarchical analysis of user needs, function mapping, and the intelligent extraction and matching of related product patent technical features are crucial for seeking innovative design solutions and improving design efficiency. …”
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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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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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