scholarly journals Selection of Filtration Methods in the Analysis of Motion of Automated Guided Vehicle

2016 ◽  
Vol 16 (4) ◽  
pp. 183-189 ◽  
Author(s):  
Magdalena Dobrzańska ◽  
Paweł Dobrzański ◽  
Mirosław Śmieszek ◽  
Paweł Pawlus
Keyword(s):  
Error Correction ◽  
Experimental Studies ◽  
Digital Filtering ◽  
Automated Guided Vehicle ◽  
Simulation Studies ◽  
Data Set ◽  
Real Movement ◽  
Selection Of ◽  
Analysis Of Motion

AbstractIn this article the issues related to mapping the route and error correction in automated guided vehicle (AGV) movement have been discussed. The nature and size of disruption have been determined using the registered runs in experimental studies. On the basis of the analysis a number of numerical runs have been generated, which mapped possible to obtain runs in a real movement of the vehicle. The obtained data set has been used for further research. The aim of this paper was to test the selected methods of digital filtering on the same data set and determine their effectiveness. The results of simulation studies have been presented in the article. The effectiveness of various methods has been determined and on this basis the conclusions have been drawn.

scholarly journals Functional Method of Designing Self-Compacting Concrete

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 267
Author(s):  
Tomasz Rudnicki
Keyword(s):  
Coarse Aggregate ◽  
Cement Mortar ◽  
Experimental Studies ◽  
Functional Method ◽  
Structural Viscosity ◽  
Self Compacting Concrete ◽  
Theoretical Assumptions ◽  
Concrete Mix ◽  
Selection Of ◽  
Double Coating

The article presents a new functional method of designing self-compacting concrete (SCC). The assumptions of the functional method of designing self-compacting concrete were based on the double coating assumption (i.e., it was assumed that the grains of coarse aggregate were coated with a layer of cement mortar, whereas the grains of sand with cement paste). The proposed method is composed of four stages, each of which is responsible for the selection of a different component of the concrete mix. The proposed designing procedure takes into consideration such a selection of the mineral skeleton in terms of the volumetric saturation of the mineral skeleton, which prevents the blocking of aggregate grains, and the designed liquid phase demonstrated high structural viscosity and low yield stress. The performed experimental studies, the simulation of the elaborated mathematical model fully allowed for the verification of the theoretical assumptions that are the basis for the development of the method of designing self-compacting concrete.

Numerical simulation studies of Cs3Bi2I9 perovskite solar device with optimal selection of electron and hole transport layers

Optik ◽  
2021 ◽  
Vol 231 ◽  
pp. 166417 ◽  
Author(s):  
Md Tohidul Islam ◽  
Md Rafsun Jani ◽  
Kazi Md Shorowordi ◽  
Zameer Hoque ◽  
Ali Mucteba Gokcek ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Hole Transport ◽  
Optimal Selection ◽  
Simulation Studies ◽  
Hole Transport Layers ◽  
Selection Of

scholarly journals Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3389
Author(s):  
Marcin Kamiński ◽  
Krzysztof Szabat
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Dynamic Properties ◽  
Experimental Studies ◽  
Drive System ◽  
Particle Swarm Optimizer ◽  
The Neural Network ◽  
Control Concept ◽  
Constant Coefficients ◽  
Selection Of

This paper presents issues related to the adaptive control of the drive system with an elastic clutch connecting the main motor and the load machine. Firstly, the problems and the main algorithms often implemented for the mentioned object are analyzed. Then, the control concept based on the RNN (recurrent neural network) for the drive system with the flexible coupling is thoroughly described. For this purpose, an adaptive model inspired by the Elman model is selected, which is related to internal feedback in the neural network. The indicated feature improves the processing of dynamic signals. During the design process, for the selection of constant coefficients of the controller, the PSO (particle swarm optimizer) is applied. Moreover, in order to obtain better dynamic properties and improve work in real conditions, one model based on the ADALINE (adaptive linear neuron) is introduced into the structure. Details of the algorithm used for the weights’ adaptation are presented (including stability analysis) to perform the shaft torque signal filtering. The effectiveness of the proposed approach is examined through simulation and experimental studies.

Constraints on the accuracy of messenger RNA movement

1985 ◽  
Vol 18 (4) ◽  
pp. 423-450 ◽  
Author(s):  
C. G. Kurland ◽  
Måns Ehrenberg
Keyword(s):  
Messenger Rna ◽  
Experimental Studies ◽  
Physical Problem ◽  
Translational Accuracy ◽  
Trna Species ◽  
Selection Of

SUMMARYTheoretical as well as experimental studies of translational accuracy have most often been concerned with the selection of aminoacyl-tRNA by codon-programmed ribosomes. The selection of the successive codons on the mRNA has received much less attention, probably because it represents both conceptually and experimentally, a much more demanding physical problem. Nevertheless, it would seem that errors in the selection of the codon are potentially much more destructive than errors in selection of aminoacyl-tRNA species. This can be appreciated from the following.

scholarly journals Collective Losses of Low Power Cage Induction Motors—A New Approach

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1749
Author(s):  
Elzbieta Szychta ◽  
Leszek Szychta
Keyword(s):  
Control System ◽  
Experimental Studies ◽  
Complex Problem ◽  
Accurate Estimation ◽  
New Approach ◽  
Water Pumping ◽  
Efficiency Control ◽  
Interacting Systems ◽  
Cage Induction Motor ◽  
Selection Of

Energy efficiency of systems of water pumping is a complex problem since efficiency of two distinct interacting systems needs to be combined: water and power supply. This paper introduces a non-intrusive method of calculating the so-called “collective losses” of a cage induction motor. The term “collective losses”, which the authors define, allows for accurate estimation of motor efficiency. Control system of a pump determines operating point of a pumping station, and thus its efficiency. General estimated performance characteristics of a motor, components of a control system, are assumed to serve selection of a range of pumping speed variations. Rotational speed has a direct effect on motor load torque, pump power and head, and thus on motor performance. Hellwig’s statistical method was used to specify characteristics of estimated collective losses on the basis of experimental studies of 21 motors rated at up to 2.2 kW. The results of simulations and experiments are used to verify validity and efficiency of the suggested method. The method is non-intrusive, simple to use, and requires minimum data.

Cascade control of «smart home» heating

2022 ◽  
Vol 14 (4) ◽  
pp. 82-89
Author(s):  
Sergey Polyakov ◽  
V. Akimov ◽  
A. Polukazakov
Keyword(s):  
Structural Changes ◽  
Experimental Studies ◽  
Residential Building ◽  
Heating System ◽  
Cascade Control ◽  
Virtual Object ◽  
Coolant Temperature ◽  
Home Heating ◽  
Input Signals ◽  
Selection Of

The article discusses the issues of implementing the conversion of input signals of «smart» sensors for automation of the heating system, an algorithm for calculating the parameters of measuring circuits with a nonlinear element and an operational amplifier is developed. The issues of modeling cascade control of residential building heating systems are investigated. The results of the analysis and selection of parameters of the cascade control system are presented. An algorithm implementing the operation of a virtual object is given. The structures of management of residential building objects are proposed. The method of calculating the adjustment of the controller for cascade control is given. For the heating system stand, the procedure for setting the parameters of the process of PID control of the coolant temperature is considered. The results confirming the achievability of the proposed structural changes are obtained. The results of experimental studies are presented.

Investigation of Regression-Based Effect Size Methods Developed in Single-Subject Studies

2021 ◽  
pp. 014544552110540
Author(s):  
Nihal Sen
Keyword(s):  
Effect Size ◽  
Experimental Studies ◽  
Single Subject ◽  
Single Subject Design ◽  
Data Set ◽  
Design Studies ◽  
Sample Data ◽  
The Difference ◽  
D Values ◽  
Effect Size Calculation

The purpose of this study is to provide a brief introduction to effect size calculation in single-subject design studies, including a description of nonparametric and regression-based effect sizes. We then focus the rest of the tutorial on common regression-based methods used to calculate effect size in single-subject experimental studies. We start by first describing the difference between five regression-based methods (Gorsuch, White et al., Center et al., Allison and Gorman, Huitema and McKean). This is followed by an example using the five regression-based effect size methods and a demonstration how these methods can be applied using a sample data set. In this way, the question of how the values obtained from different effect size methods differ was answered. The specific regression models used in these five regression-based methods and how these models can be obtained from the SPSS program were shown. R2 values obtained from these five methods were converted to Cohen’s d value and compared in this study. The d values obtained from the same data set were estimated as 0.003, 0.357, 2.180, 3.470, and 2.108 for the Allison and Gorman, Gorsuch, White et al., Center et al., as well as for Huitema and McKean methods, respectively. A brief description of selected statistical programs available to conduct regression-based methods was given.

MONITORING AND CLASSIFYING THE STATE OF HARD DISKS USING RECURRENT NEURAL NETWORKS

2021 ◽  
pp. 36-43
Author(s):  
L. A. Demidova ◽  
A. V. Filatov
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Experimental Studies ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Dense Layer ◽  
Hard Disks ◽  
Destructive Testing ◽  
Data Set ◽  
State Classification

The article considers an approach to solving the problem of monitoring and classifying the states of hard disks, which is solved on a regular basis, within the framework of the concept of non-destructive testing. It is proposed to solve this problem by developing a classification model using machine learning algorithms, in particular, using recurrent neural networks with Simple RNN, LSTM and GRU architectures. To develop a classification model, a data set based on the values of SMART sensors installed on hard disks it used. It represents a group of multidimensional time series. At the same time, the structure of the classification model contains two layers of a neural network with one of the recurrent architectures, as well as a Dropout layer and a Dense layer. The results of experimental studies confirming the advantages of LSTM and GRU architectures as part of hard disk state classification models are presented.

scholarly journals Selection of X-chromosome Inactivation Model

2017 ◽  
Vol 16 ◽  
pp. 117693511774727 ◽  
Author(s):  
Jian Wang ◽  
Rajesh Talluri ◽  
Sanjay Shete
Keyword(s):  
X Chromosome ◽  
X Chromosome Inactivation ◽  
Association Test ◽  
Chromosome Inactivation ◽  
Simulation Studies ◽  
Nucleotide Polymorphisms ◽  
Unified Approach ◽  
Cancer Genetic ◽  
Single Nucleotide ◽  
Selection Of

To address the complexity of the X-chromosome inactivation (XCI) process, we previously developed a unified approach for the association test for X-chromosomal single-nucleotide polymorphisms (SNPs) and the disease of interest, accounting for different biological possibilities of XCI: random, skewed, and escaping XCI. In the original study, we focused on the SNP-disease association test but did not provide knowledge regarding the underlying XCI models. One can use the highest likelihood ratio (LLR) to select XCI models (max-LLR approach). However, that approach does not formally compare the LLRs corresponding to different XCI models to assess whether the models are distinguishable. Therefore, we propose an LLR comparison procedure (comp-LLR approach), inspired by the Cox test, to formally compare the LLRs of different XCI models to select the most likely XCI model that describes the underlying XCI process. We conduct simulation studies to investigate the max-LLR and comp-LLR approaches. The simulation results show that compared with the max-LLR, the comp-LLR approach has higher probability of identifying the correct underlying XCI model for the scenarios when the underlying XCI process is random XCI, escaping XCI, or skewed XCI to the deleterious allele. We applied both approaches to a head and neck cancer genetic study to investigate the underlying XCI processes for the X-chromosomal genetic variants.

scholarly journals Data Set for the Reporting of Malignant Odontogenic Tumors: Explanations and Recommendations of the Guidelines From the International Collaboration on Cancer Reporting

2018 ◽  
Vol 143 (5) ◽  
pp. 587-592 ◽  
Author(s):  
Pieter J. Slootweg ◽  
Edward W. Odell ◽  
Daniel Baumhoer ◽  
Roman Carlos ◽  
Keith D. Hunter ◽  
...  
Keyword(s):  
International Collaboration ◽  
Case Series ◽  
Initial Step ◽  
Odontogenic Tumors ◽  
Data Set ◽  
Expert Opinions ◽  
Organ Systems ◽  
Standardized Reporting ◽  
Selection Of ◽  
Cancer Reporting

A data set has been developed for the reporting of excisional biopsies and resection specimens for malignant odontogenic tumors by members of an expert panel working on behalf of the International Collaboration on Cancer Reporting, an international organization established to unify and standardize reporting of cancers. Odontogenic tumors are rare, which limits evidence-based support for designing a scientifically sound data set for reporting them. Thus, the selection of reportable elements within the data set and considering them as either core or noncore is principally based on evidence from malignancies affecting other organ systems, limited case series, expert opinions, and/or anecdotal reports. Nevertheless, this data set serves as the initial step toward standardized reporting on malignant odontogenic tumors that should evolve over time as more evidence becomes available and functions as a prompt for further research to provide such evidence.

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