Study of Urban Storm Intensity

2014 ◽  
Vol 539 ◽  
pp. 752-756
Author(s):  
Chao Zhang ◽  
Bo Fu Li ◽  
Zong De Wang ◽  
Jian Yong Zou ◽  
Ying He Jiang
Keyword(s):  
Comparative Analysis ◽  
Optimization Method ◽  
Least Square ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Annual Maximum ◽  
Storm Intensity ◽  
Maximum Value ◽  
New Formula ◽  
Urban Storm

All the rainfall data from 1983 to 2012 in HScity were collected andthe annual maximum value method was adopted to select the samples. Parameters of storm intensity formula of single return period were calculated through the optimization method and the least square methodfor itP tables.Then, the storm intensityformula was established. Through the comparative analysis of the precision of both the new formula and old one,the result indicated that the absolute mean square deviation and relative mean square deviation of new formula were less than 0.05mm/min and 5%,while old formula cannot meet the requirement ofoutdoor wastewater engineering design.

scholarly journals G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

2020 ◽  
Author(s):  
Tomonori Fukutani, ◽  
kohei Miyazawa ◽  
Satoru Iwata ◽  
Hiroko Satoh
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Three Dimensional ◽  
Valence Bond ◽  
Optimization Method ◽  
Molecular Structures ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Atomic Structures ◽  
Structure Search

<div>We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate the minimal RMSD value of two atomic structures by optimal superimposition. The method is not restricted to systems with an equal number of atoms or a unique atom matching and can handle any type of chemical structure, including transition states and non-valence bond structures. It requires only Cartesian coordinates for the structures, but can also include further information, i.e. atom and bond types. Applications of G-RMSD to the classification of alpha-D-glucose conformers and 3D partial structure search using a dataset containing equilibrium (EQ), dissociation channel (DC), and transition state (TS) structures are demonstrated. We find that G-RMSD allows for a successful classification and mapping for a wide variety of molecular structures.</div><div><br></div>

scholarly journals G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

2020 ◽  
Author(s):  
Tomonori Fukutani, ◽  
kohei Miyazawa ◽  
Satoru Iwata ◽  
Hiroko Satoh
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Three Dimensional ◽  
Valence Bond ◽  
Optimization Method ◽  
Molecular Structures ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Atomic Structures ◽  
Structure Search

<div>We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate the minimal RMSD value of two atomic structures by optimal superimposition. The method is not restricted to systems with an equal number of atoms or a unique atom matching and can handle any type of chemical structure, including transition states and non-valence bond structures. It requires only Cartesian coordinates for the structures, but can also include further information, i.e. atom and bond types. Applications of G-RMSD to the classification of alpha-D-glucose conformers and 3D partial structure search using a dataset containing equilibrium (EQ), dissociation channel (DC), and transition state (TS) structures are demonstrated. We find that G-RMSD allows for a successful classification and mapping for a wide variety of molecular structures.</div><div><br></div>

scholarly journals The evaluation of effectiveness of the device "Coilbox" on the mill 1680

2018 ◽  
pp. 300-308
Author(s):  
N.I. Podobedov ◽  
V.V. Verenev ◽  
V.V. Korennoi
Keyword(s):  
Comparative Analysis ◽  
Standard Deviation ◽  
Polyurethane Foam ◽  
Dynamic Loads ◽  
Dynamic Factor ◽  
Mean Square ◽  
Mean Square Deviation ◽  
The Mean ◽  
The Moment ◽  
Hot Rolled

The aim of the work is to conduct a comparative analysis of the results of rolling hot-rolled strips in the finishing group of mill stands of 1680 strips with and without the use of an intermediate rewinding device (PUF). A comparative analysis of the results of measurements of the moment and longitudinal thickness during rolling in the finishing group of stands is given. Given the distribution of torque in the cages along the length of the strip. It is shown that the mean square deviation of the moment is noticeably less than the rolling time without PUF. The level of dynamic loads and the dynamic factor of the moment of elastic force during the rolling of bands with polyurethane foam and without polyurethane foam practically did not change. It is shown that when rolling without PUF on the finished strip there remains a trace of the temperature wedge in the form of a wedge of thickness. When rolling with PUF, the thickness of the strip along its length becomes more uniform. When rolling without PUF, a trace of a wedge of thickness in the form of a wedge remains on the finished strip. When rolling with PUF, the thickness of the strip along its length becomes more uniform. In general, a comparison of the average moment along the stripes, the standard deviation, the coefficient of variation of the moment and the deviation of the thickness shows the advantages of rolling with PUF.

scholarly journals Improvement in a phenomenological formula for ground state binding energies

2016 ◽  
Vol 25 (08) ◽  
pp. 1650046
Author(s):  
G. Gangopadhyay
Keyword(s):  
Binding Energy ◽  
Ground State ◽  
Magic Number ◽  
Substantial Improvement ◽  
Binding Energies ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Neutron Magic Number ◽  
Experimental Values ◽  
New Formula

The phenomenological formula for ground state binding energy derived earlier [G. Gangopadhyay, Int. J. Mod. Phys. E 20 (2011) 179] has been modified. The parameters have been obtained by fitting the latest available tabulation of experimental values. The major modifications include a new term for pairing and introduction of a new neutron magic number at N = 160. The new formula reduced the root mean square deviation to 363[Formula: see text]keV, a substantial improvement over the previous version of the formula.

scholarly journals Comparison of practical expressions for E1 photon strength functions

2020 ◽  
Vol 239 ◽  
pp. 03012
Author(s):  
Oleksandr Gorbachenko ◽  
Igor Kadenko ◽  
Vladimir Plujko ◽  
Kateryna Solodovnyk
Keyword(s):  
Gamma Rays ◽  
Theoretical Calculations ◽  
Least Square ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Deviation Factor ◽  
Strength Functions ◽  
Gamma Decay ◽  
Lorentzian Model ◽  
Good Agreement

The closed-form expressions for the photon strength functions (PSF) are tested using the gamma-decay data of OSLO group. The theoretical calculations are performed for the Lorentzian models of PSF for electric and magnetic dipole gamma-rays. The criteria of minimum of least-square value as well as the root-mean-square deviation factor are used. It is shown that a rather good agreement is obtained within the Simple Modified Lorentzian model for E1 PSF modelling.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

scholarly journals GNINA 1.0: molecular docking with deep learning

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew T. McNutt ◽  
Paul Francoeur ◽  
Rishal Aggarwal ◽  
Tomohide Masuda ◽  
Rocco Meli ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Computational Cost ◽  
Scoring Function ◽  
Binding Pocket ◽  
Protein Docking ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Autodock Vina

AbstractMolecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline as they determine the fitness of sampled poses. Here we describe and evaluate the 1.0 release of the Gnina docking software, which utilizes an ensemble of convolutional neural networks (CNNs) as a scoring function. We also explore an array of parameter values for Gnina 1.0 to optimize docking performance and computational cost. Docking performance, as evaluated by the percentage of targets where the top pose is better than 2Å root mean square deviation (Top1), is compared to AutoDock Vina scoring when utilizing explicitly defined binding pockets or whole protein docking. Gnina, utilizing a CNN scoring function to rescore the output poses, outperforms AutoDock Vina scoring on redocking and cross-docking tasks when the binding pocket is defined (Top1 increases from 58% to 73% and from 27% to 37%, respectively) and when the whole protein defines the binding pocket (Top1 increases from 31% to 38% and from 12% to 16%, respectively). The derived ensemble of CNNs generalizes to unseen proteins and ligands and produces scores that correlate well with the root mean square deviation to the known binding pose. We provide the 1.0 version of Gnina under an open source license for use as a molecular docking tool at https://github.com/gnina/gnina.

Prediction of Performance and Design via Optimization of Ducted Propellers Subject to Non-axisymmetric Inflows

2005 ◽  
Author(s):  
Spyros A. Kinnas ◽  
Hanseong Lee ◽  
Hua Gu ◽  
Yumin Deng
Keyword(s):  
Nonlinear Optimization ◽  
Pressure Coefficient ◽  
Optimization Method ◽  
Least Square ◽  
Maximum Efficiency ◽  
Design Parameters ◽  
Blade Design ◽  
Constrained Nonlinear Optimization ◽  
Nonlinear Optimization Method ◽  
Ducted Propellers

Recently developed methods at UT Austin for the analysis of open or ducted propellers are presented, and then coupled with a constrained nonlinear optimization method to design blades of open or ducted propellers for maximum efficiency satisfying the minimum pressure constraint for fully wetted case, or the specified maximum allowable cavity area for cavitating case. A vortex lattice method (named MPUF3A) is applied to analyze the unsteady cavitating performance of open or ducted propellers subject to non-axisymmetric inflows. A finite volume method based Euler solver (named GBFLOW) is applied to predict the flow field around the open or ducted propellers, coupled with MPUF-3A in order to determine the interaction of the propeller with the inflow (i.e. the effective wake) or with the duct. The blade design of open or ducted propeller is performed by using a constrained nonlinear optimization method (named CAVOPT-BASE), which uses a database of computed performance for a set of blade geometries constructed from a base-propeller. The performance is evaluated using MPUF-3A and GBFLOW. CAVOPT-BASE approximates the database using the least square method or the linear interpolation method, and generates the coefficients of polynomials based on the design parameters, such as pitch, chord, and camber. CAVOPT-BASE finally determines the optimum blade design parameters, so that the propeller produces the desired thrust for the given constraints on the pressure coefficient or the allowed amount of cavitation.

Simple correlations for calculating NHTPB enthalpy of formation through molecular structures

2019 ◽  
Vol 15 (1) ◽  
pp. 258-264 ◽  
Author(s):  
Hamid Reza Ghaieni ◽  
Saeed Tavangar ◽  
Mohammad Moein Ebrahimzadeh Qhomi
Keyword(s):  
Enthalpy Of Formation ◽  
Design Methodology ◽  
Predictive Power ◽  
Cross Validation ◽  
Molecular Structures ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Simple Correlation ◽  
Content Type ◽  
Regression Methods

Purpose The purpose of this paper is to present simple correlation for calculating nitrated hydroxyl-terminated polybutadiene (NHTPB) enthalpy of formation. Design/methodology/approach It uses multiple linear regression methods. Findings The proposed correlation has determination coefficient 0.96. The correlation has root mean square deviation and the average absolute deviations values 53.4 and 46.1 respectively. Originality/value The predictive power of correlation is checked by cross-validation method (R2=0.96, Q L O O 2 = 0.96 ).

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