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

“…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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EM Algorithm in the Modified Slash Power Maxwell Distribution with an Application by Francisco A. Segovia, Yolanda M. Gómez, Héctor J. Gómez, Inmaculada Barranco-Chamorro, Héctor W. Gómez

“…We study its probability density function and some properties, such as moments, asymmetry and kurtosis coefficient. …”
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An Empirical Analysis of Herding Behavior in the Stock Market: Evidence from Various Economic and Social Conditions in Iran by Majid Aghaei

“…This approach models the response of the dependent variable to the independent variable at various quantiles, denoted as "τ," making it an effective tool for analyzing non-normal distributions. …”
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THE STRUCTURE OF HAPPINESS REPRESENTATION FOR RUSSIAN AND AMERICAN REPRESENTATIVES by S. Yu. Zhdanova, A. V. Pecherkina, A. A. Strokanov

“…Statistical analysis of the data was based on the use of the coefficient of φ-angular Fisher transform, correlation coefficient φ, and cluster analysis.Results and scientific novelty. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The optimal model was used to visualize the dynamic distribution of these values. (3) Results: the crude fatty acid values exhibited a positive correlation with storage time, functioning as a direct indicator of soybean quality. …”
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Evaluation of Data Mining and Artificial Intelligence Methods to Predict Daily Precipitation by Yaseen Ahmed Hamaamin

“…In ANFIS modelling, for several input variables up to 6 variables, this study recommends using the grid partition method to divide variable ranges into membership functions. …”
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OpenConMap: A Matlab toolbox for mapping the interior of the unit circle to the exterior of simple closed curves by Kai He, Kai Wang

“…Featuring a user-friendly GUI program, the toolbox efficiently computes conformal mapping functions, streamlining the solving process.…”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Results revealed that all NN models particularly PSO-NNs were efficient in prediction of Kfs. However, further evaluations may be recommended for other soil conditions and input variables to quantify their potential uncertainties and wider potential and versatility before they are used in other geographical locations/soil conditions.…”
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Dual effects of leptin in perioperative gas exchange of morbidly obese patients. by Michele Carron, Giovanna Ieppariello, Gabriele Martelli, Giulia Gabellini, Mirto Foletto, Egle Perissinotto, Carlo Ori

“…Leptin has shown positive effects on respiratory function in experimental settings. The role of leptin on perioperative respiratory function in morbidly obese patients has not been established. …”
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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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High-Resolution Core Gene-Associated Multiple Nucleotide Polymorphism (cgMNP) Markers for Strain Identification in the Wine Cap Mushroom <i>Stropharia rugosoannulata</i> by Fei Liu, Bin Cao, Hongmei Dai, Guojie Li, Shoumian Li, Wei Gao, Ruilin Zhao

“…Using core gene-associated multiple nucleotide polymorphism (cgMNP) markers, we developed an efficient and transferable framework for strain discrimination. …”
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Which Metrics Can I Monitor? Test-Retest Reliability of Countermovement Jump and Countermovement Rebound Jump Force-Time Metrics in Youth Soccer Players In-Season by Andrew Badby, Paul Comfort, Nicholas Ripley, Matthew Cuthbert, Francisco Robles-Palazón, Peter Mundy, John McMahon

“…Objective measures provide the most effective means of monitoring the magnitude and time course of changes in neuromuscular function (NMF) resulting from physical activity if measurements are repeatable (reliability). …”
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A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study. by Patrizio Barca, Fabio Paolicchi, Giacomo Aringhieri, Federica Palmas, Daniela Marfisi, Maria Evelina Fantacci, Davide Caramella, Marco Giannelli

“…An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f50%/f10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. …”
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Analisis Kualitas Website Balai Besar Taman Nasional Gunung Gede Pangranggo (BBTNGGP) menggunakan Metode Webqual 4.0 by Muhammad Syahid Qadhafi, Atit Pertiwi

“…The results of the analysis of the quality of this website concluded that the variable usability and information quality had a good value compared to the variable service interaction quality. …”
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Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
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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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The Fuzzy Response Surface Reliability Analysis Method of Turbine Blades by PAN Cheng-yi, WEI Wen-long, ZHANG Chun-yi

“…The analysis result shows that the blade reliability indexes decrease with the increase of fuzzy coefficient. Compared with the traditional method based on random variables, this method is more reasonable for the description of uncertainty, and the evaluation of reliability is more accurate theoretically.…”
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Numerical Analysis of the Preloading Consolidation of the Soft Foundation with a Plastic Drainage Plate by Linjie Li, Shuaidong Yang, Tong Su

“…The permeability coefficient and void ratio are related to the stress state of the soil, which manifests as the temporal and spatial variability of consolidation. …”
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Sensitivity analysis of melting heat transfer in Williamson fluid by Aliya Batool, Zakir Hussain, Dilawar Hussain

“…The model is simplified to ordinary differential equations by introducing similarity variables and tackled by bvp4c Matlab function. The significant variables on flow model are identified by Response Surface Method (RSM). …”
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Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…Initially, the model introduces symbols: x as the vector of design variables, and y as the vector of control variables. …”
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