scholarly journals Сonstruction of regression models for developing the technology to obtain tablets based on medicinal ginger

2021 ◽  
Vol 7 (4) ◽  
pp. 3-13
Author(s):  
О. V. Kutova ◽  
O. A. Ruban ◽  
R. V. Sahaidak-Nikitiuk ◽  
I. V. Kovalevska ◽  
N. V. Demchenko
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Mathematical Description ◽  
Regression Models ◽  
Scientific Research ◽  
Complex Model ◽  
Model Structure ◽  
Input Output ◽  
Static Systems

Scientific research in pharmacy, due to their multifactorial nature, is closely related to modeling of complex static systems. For this purpose, the so-called “input-output” mathematical models, which are built based on the results of the experiment, are widely used. Modeling of static systems based on the experimental data requires the solution of three interrelated tasks: planning of the experiment and its implementation; identification of the model structure and its parameters; approximation, if necessary, of a complex model to a simpler mathematical description.

Alternative Regression Model Structure for the HCM-6 Equal-Capacity Passenger Car Equivalency Methodology

2021 ◽  
pp. 036119812199582
Author(s):  
Antonio Hurtado-Beltran ◽  
Laurence R. Rilett
Keyword(s):  
Regression Models ◽  
New Technologies ◽  
Complex Model ◽  
Model Parameters ◽  
Model Structure ◽  
Highway Capacity ◽  
Passenger Car ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Equal Capacity

In the current version of the Highway Capacity Manual (HCM-6), equal-capacity passenger car equivalencies (EC-PCEs) are used to account for the effect of trucks for capacity analyses. The EC-PCEs for freeway segments were estimated using a microsimulation-based methodology where the capacities of the mixed-traffic and car-only flow scenarios were modeled. A nonlinear regression (NLR) model was used to develop capacity adjustment factor (CAF) models using the microsimulation data as input. The NLR model has a complex model structure and includes 15 model parameters. It is argued in this paper that simpler regression models could provide comparable results. This would allow CAF and EC-PCE equations to be used directly in the HCM-6 rather than tables. It would also allow for the development of new regression models for exploring new technologies such as connected and automated vehicles (CAVs). The objective of this paper was to develop alternative and simpler regression models of CAFs needed to derive the EC-PCE values in the HCM-6 methodology for freeway and multilane highway segments. It was found that simpler regression models provided similar results as those obtained with the current NLR model. Additionally, it was found that the current NLR model may not be adequate for analyzing CAV traffic conditions. If the HCM-6 EC-PCE methodology is expected to be used to analyze traffic conditions beyond the scope of the HCM-6, it is important to perform a deeper assessment of the form and error of the regression models used in fitting the simulated and estimated data.

An implementation framework for wastewater treatment models requiring a minimum programming expertise

2009 ◽  
Vol 59 (2) ◽  
pp. 367-380 ◽  
Author(s):  
J. Rodríguez ◽  
G. C. Premier ◽  
R. Dinsdale ◽  
A. J. Guwy
Keyword(s):  
Mathematical Models ◽  
Model Simulation ◽  
Complex Model ◽  
Model Structure ◽  
State Variables ◽  
Implementation Framework ◽  
Software Packages ◽  
Treatment Models ◽  
User Friendly ◽  
Excel File

Mathematical modelling in environmental biotechnology has been a traditionally difficult resource to access for researchers and students without programming expertise. The great degree of flexibility required from model implementation platforms to be suitable for research applications restricts their use to programming expert users. More user friendly software packages however do not normally incorporate the necessary flexibility for most research applications. This work presents a methodology based on Excel and Matlab-Simulink for both flexible and accessible implementation of mathematical models by researchers with and without programming expertise. The models are almost fully defined in an Excel file in which the names and values of the state variables and parameters are easily created. This information is automatically processed in Matlab to create the model structure and almost immediate model simulation, after only a minimum Matlab code definition, is possible. The framework proposed also provides programming expert researchers with a highly flexible and modifiable platform on which to base more complex model implementations. The method takes advantage of structural generalities in most mathematical models of environmental bioprocesses while enabling the integration of advanced elements (e.g. heuristic functions, correlations). The methodology has already been successfully used in a number of research studies.

Integrating experimental data and mathematical models in simulation of physical systems

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 1787-1790
Author(s):  
Boris A. Zeldin ◽  
Andrew J. Meade
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Physical Systems

scholarly journals Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 28
Author(s):  
Anna V. Kalyuzhnaya ◽  
Nikolay O. Nikitin ◽  
Alexander Hvatov ◽  
Mikhail Maslyaev ◽  
Mikhail Yachmenkov ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Learning Approach ◽  
Model Structure ◽  
Evolutionary Learning ◽  
Learning Models ◽  
Computationally Efficient ◽  
Performance Models ◽  
Generative Design ◽  
Computational Resources ◽  
Machine Learning Models

In this paper, we describe the concept of generative design approach applied to the automated evolutionary learning of mathematical models in a computationally efficient way. To formalize the problems of models’ design and co-design, the generalized formulation of the modeling workflow is proposed. A parallelized evolutionary learning approach for the identification of model structure is described for the equation-based model and composite machine learning models. Moreover, the involvement of the performance models in the design process is analyzed. A set of experiments with various models and computational resources is conducted to verify different aspects of the proposed approach.

scholarly journals A Magneto-Active Elastomer Crawler with Peristaltic and Caterpillar Locomotion Patterns

Actuators ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 74
Author(s):  
Tsam Lung You ◽  
Hemma Philamore ◽  
Fumitoshi Matsuno
Keyword(s):  
Magnetic Field ◽  
Experimental Data ◽  
External Magnetic Field ◽  
Mathematical Models ◽  
Confined Spaces ◽  
Low Mass ◽  
Structural Simplicity

In this work we present a soft crawler fabricated using a magneto-active elastomer. The crawler is controlled by an external magnetic field to produce two locomotion patterns: peristaltic and caterpillar crawling. Due to its structural simplicity, low mass, wirelessly controlled actuation and compliant body the design of this crawler has the potential to address the key challenges faced by existing crawling robots. Experimental data were gathered to evaluate the performance of the crawler locomotion in a pipe. The results validated the mathematical models proposed to estimate the distance traveled by the crawler. The crawler shows potential for use in exploration of confined spaces.

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

Electron drift caused by rf field gradient creates many plasma phenomena: An attempt to distinguish the cause and the effect

2011 ◽  
Vol 78 (2) ◽  
pp. 165-174 ◽  
Author(s):  
C. L. XAPLANTERIS ◽  
E. D. FILIPPAKI ◽  
I. S. MISTAKIDIS ◽  
L. C. XAPLANTERIS
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Low Temperature ◽  
Mathematical Models ◽  
Field Gradient ◽  
Collision Frequency ◽  
The Other ◽  
Frequency Effect ◽  
Electron Drift ◽  
Plasma Parameters

AbstractMany experimental data along with their theoretical interpretations on the rf low-temperature cylindrical plasma have been issued until today. Our Laboratory has contributed to that research by publishing results and interpretative mathematical models. With the present paper, two issues are being examined; firstly, the estimation of electron drift caused by the rf field gradient, which is the initial reason for the plasma behaviour, and secondly, many new experimental results, especially the electron-neutral collision frequency effect on the other plasma parameters and quantities. Up till now, only the plasma steady state was taken into consideration when a theoretical elaboration was carried out, regardless of the cause and the effect. This indicates the plasma's complicated and chaotic configuration and the need to simplify the problem. In the present work, a classification about the causality of the phenomena is attempted; the rf field gradient electron drift is proved to be the initial cause.

Modelling and computation of liquid crystals

Acta Numerica ◽  
2021 ◽  
Vol 30 ◽  
pp. 765-851
Author(s):  
Wei Wang ◽  
Lei Zhang ◽  
Pingwen Zhang
Keyword(s):  
Liquid Crystals ◽  
Numerical Methods ◽  
Mathematical Models ◽  
Soft Matter ◽  
Scientific Research ◽  
Crystalline Solids ◽  
The Past ◽  
Tremendous Progress

Liquid crystals are a type of soft matter that is intermediate between crystalline solids and isotropic fluids. The study of liquid crystals has made tremendous progress over the past four decades, which is of great importance for fundamental scientific research and has widespread applications in industry. In this paper we review the mathematical models and their connections to liquid crystals, and survey the developments of numerical methods for finding rich configurations of liquid crystals.

scholarly journals Mathematical models as practical tool for road fatalities forecasts on road network in regions

2018 ◽  
Vol 231 ◽  
pp. 01018 ◽  
Author(s):  
Joanna Wachnicka
Keyword(s):  
Mathematical Models ◽  
Traffic Safety ◽  
Road Safety ◽  
Regression Models ◽  
Road Network ◽  
Statistical Data ◽  
Safety Management ◽  
National Data ◽  
Local Characteristics ◽  
Practical Tool

The analysis of national data on the number of deaths showed that in Poland from 2010 to 2016 it was possible to reduce the number of fatalities by about 22%. The tendency of changes in the number of fatalities, however, is not homogeneous. When data of individual voivodships is analyzed, the situation is different. The largest reduction in fatalities in the analyzed period of time concerned voivodship Świętokrzyskie, where there was more than 45% drop in the number of fatalities. The following voivodships: Łódzkie, Lubelskie and Podkarpackie recorded a decrease in over 30% of fatalities. Unfortunately, at the end of the classification there were four voivodships with a fall below 8%, and what is disturbing voivodship Lubuskie recorded a nearly 5% increase in the number of fatalities. The current traffic safety management at the level of voivodships is often the implementation of central recommendations, which, as results from the analysis of statistical data, are not equally effective in every province. Therefore, models for forecasting changes in road safety are required. Taking into account local characteristics and implemented actions can be used to manage security more effectively at the regional level. This paper presents examples of the use of mathematical models to predict the number of fatalities in individual voivodships depending on the adopted action scenarios. Regression models were developed, taking into account demographic, infrastructural, economic and automotive factors. It turned out that in individual voivodships, various factors affect the level of road safety on roads differently. Therefore, an individual approach to each voivodship is important in order to reliably forecast the level of security.

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