Research

9 pages, 3248 KiB

Open AccessArticle

Transformations for FIR and IIR Filters’ Design

by V. N. Stavrou, I. G. Tsoulos and Nikos E. Mastorakis

Symmetry 2021, 13(4), 533; https://doi.org/10.3390/sym13040533 - 25 Mar 2021

Cited by 14 | Viewed by 2386

In this paper, the transfer functions related to one-dimensional (1-D) and two-dimensional (2-D) filters have been theoretically and numerically investigated. The finite impulse response (FIR), as well as the infinite impulse response (IIR) are the main 2-D filters which have been investigated. More [...] Read more.

In this paper, the transfer functions related to one-dimensional (1-D) and two-dimensional (2-D) filters have been theoretically and numerically investigated. The finite impulse response (FIR), as well as the infinite impulse response (IIR) are the main 2-D filters which have been investigated. More specifically, methods like the Windows method, the bilinear transformation method, the design of 2-D filters from appropriate 1-D functions and the design of 2-D filters using optimization techniques have been presented. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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17 pages, 6283 KiB

Open AccessArticle

Induction Motor Multiclass Fault Diagnosis Based on Mean Impact Value and PSO-BPNN

by Chun-Yao Lee and Hong-Yi Ou

Symmetry 2021, 13(1), 104; https://doi.org/10.3390/sym13010104 - 08 Jan 2021

Cited by 8 | Viewed by 1598

Abstract

This paper presents a feature selection model based on mean impact value (MIV) to solve induction motor (IM) fault diagnosis on the current signal. In this paper, particle swarm optimization (PSO) is combined with back propagation neural network (BPNN) to classify the current [...] Read more.

This paper presents a feature selection model based on mean impact value (MIV) to solve induction motor (IM) fault diagnosis on the current signal. In this paper, particle swarm optimization (PSO) is combined with back propagation neural network (BPNN) to classify the current signal of IM. First, the purpose of this study is to establish IM fault diagnosis system. Additionally, this study proposes a feature selection process that is composed of MIV, whose objective is to reduce the number of classifier input features. Secondly, the features are extracted as a feature database after analyzing the current signal of IM, and the fault diagnosis is established through the model of PSO-BPNN. Finally, redundant features are deleted through this feature selection process and a classifier is built. The result shows that the feature selection model based on MIV can filter the features effectively at a signal to noise ratio of 30 dB and 20 dB for the IM fault detection problem. In addition, the computing time of BPNN is also reduced which is helpful for online detection. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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27 pages, 3247 KiB

Open AccessArticle

Design of Fuzzy TS-PDC Controller for Electrical Power System via Rules Reduction Approach

by Badr Alshammari, Rim Ben Salah, Omar Kahouli and Lioua Kolsi

Symmetry 2020, 12(12), 2068; https://doi.org/10.3390/sym12122068 - 12 Dec 2020

Cited by 7 | Viewed by 2118

Abstract

In this paper, a new Takagi–Sugeno Fuzzy Logic controller (TS-FLC) is presented and applied for modeling and controlling the nonlinear power systems even in the presence of disturbances. Firstly, a nonlinear mathematical model for the electrical power system is presented with consideration of [...] Read more.

In this paper, a new Takagi–Sugeno Fuzzy Logic controller (TS-FLC) is presented and applied for modeling and controlling the nonlinear power systems even in the presence of disturbances. Firstly, a nonlinear mathematical model for the electrical power system is presented with consideration of PSS and AVR controller. Then, a Takagi–Sugeno Fuzzy Logic controller is employed to control power system stability. Nevertheless, the study of the stability of Takagi–Sugeno fuzzy models will be difficult in the case where the number of nonlinearities is important. To cope with this problem, this study proposed a methodology to reduce the number of rules and to guarantee the global stability of the power system. The new model included only two rules. All the other nonlinearities were considered as uncertainties. In addition, a Parallel Distributed Compensation controller is designed using the Linear Matrix Inequalities constraints in order to guarantee system stability. Finally, this approach is applied on a Single Machine Infinite Bus affected by fault perturbation. To show the novelty of Takagi Sugeno’s method, we compared our approach to the Taylor linearization method. The numerical simulations prove the feasibility and performance of the proposed method. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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20 pages, 5672 KiB

Open AccessArticle

Quasi-Delay-Insensitive Implementation of Approximate Addition

by Padmanabhan Balasubramanian and Nikos E. Mastorakis

Symmetry 2020, 12(11), 1919; https://doi.org/10.3390/sym12111919 - 20 Nov 2020

Cited by 1 | Viewed by 2616

Abstract

Asynchronous quasi-delay-insensitive (QDI) implementation of approximate addition is described in this article. The objective is to provide an insight into the optimization in design metrics that can be achieved with approximate addition compared to accurate addition based on a QDI implementation by considering [...] Read more.

Asynchronous quasi-delay-insensitive (QDI) implementation of approximate addition is described in this article. The objective is to provide an insight into the optimization in design metrics that can be achieved with approximate addition compared to accurate addition based on a QDI implementation by considering a practical digital image processing application. For the QDI implementation, some approximate adder architectures are considered which are deemed suitable for both ASIC and FPGA based implementations. The accurate and approximate adders considered are of size 32-bits. The delay-insensitive dual-rail code was used for data encoding, and four-phase return-to-zero (RTZ) and return-to-one (RTO) handshake protocols were used separately for data communication. The implementations used a 32/28-nm complementary metal oxide semiconductor (CMOS) technology. The simulation results show that an approximate adder HOERAA achieves a 19.7% reduction in cycle time, a 12.5% reduction in area, and an 17.7% reduction in energy compared to the accurate adder for RTZ handshaking. For RTO handshaking, HOERAA achieves an 18.7% reduction in cycle time, a 12.4% reduction in area, and a 16.6% reduction in energy compared to the accurate adder. Another approximate adder HEAA achieves a 19.7% reduction in cycle time, a 12.9% reduction in area, and a 20.2% reduction in energy, compared to the accurate adder for RTZ handshaking. For RTO handshaking, HEAA achieves an 18.7% reduction in cycle time, a 12.9% reduction in area, and a 19.2% reduction in energy compared to the accurate adder. Nevertheless, the RTO handshaking is preferable to RTZ handshaking as the former facilitates slightly better optimizations in design metrics compared to the latter. The mean absolute error (MAE) and the root mean square error (RMSE), which are popular error metrics used in approximate computing, were calculated for the approximate adders and are given for a comparison. While the MAE of HOERAA and HEAA are comparable, HOERAA has 8.6% reduced RMSE compared to HEAA. Digital image processing results based on accurate and approximate additions are also given, to substantiate the usefulness of approximate addition. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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18 pages, 955 KiB

Open AccessArticle

Reading-Network in Developmental Dyslexia before and after Visual Training

by Tihomir Taskov and Juliana Dushanova

Symmetry 2020, 12(11), 1842; https://doi.org/10.3390/sym12111842 - 06 Nov 2020

Cited by 9 | Viewed by 2478

Abstract

Electroencephalographic studies using graph-theoretic analysis have found aberrations in functional connectivity in dyslexics. How visual nonverbal training (VT) can change the functional connectivity of the reading network in developmental dyslexia is still unclear. We studied differences in the local and global topological properties [...] Read more.

Electroencephalographic studies using graph-theoretic analysis have found aberrations in functional connectivity in dyslexics. How visual nonverbal training (VT) can change the functional connectivity of the reading network in developmental dyslexia is still unclear. We studied differences in the local and global topological properties of functional reading networks between controls and dyslexic children before and after VT. The minimum spanning tree method was used to construct the reading networks in multiple electroencephalogram (EEG) frequency bands. Compared to controls, pre-training dyslexics had a higher leaf fraction, tree hierarchy, kappa, and smaller diameter (θ—γ-frequency bands), and therefore, they had a less segregated neural network than controls. After training, the reading-network metrics of dyslexics became similar to controls. In β1 and γ-frequency bands, pre-training dyslexics exhibited a reduced degree and betweenness centrality of hubs in superior, middle, and inferior frontal areas in both brain hemispheres compared to the controls. Dyslexics relied on the left anterior temporal (β1, γ1) and dorsolateral prefrontal cortex (γ1), while in the right hemisphere, they relied on the occipitotemporal, parietal, (β1), motor (β2, γ1), and somatosensory cortices (γ1). After training, hubs appeared in both hemispheres at the middle occipital (β), parietal (β1), somatosensory (γ1), and dorsolateral prefrontal cortices (γ2), while in the left hemisphere, they appeared at the middle temporal, motor (β1), intermediate (γ2), and inferior frontal cortices (γ1, β2). Language-related brain regions were more active after visual training. They contribute to an understanding of lexical and sublexical representation. The same role has areas important for articulatory processes of reading. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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24 pages, 14178 KiB

Open AccessArticle

Diagnosis of Defective Rotor Bars in Induction Motors

by Chun-Yao Lee, Kuan-Yu Huang, Lai-Yu Jen and Guang-Lin Zhuo

Symmetry 2020, 12(11), 1753; https://doi.org/10.3390/sym12111753 - 22 Oct 2020

Cited by 5 | Viewed by 2899

Abstract

This paper proposes a diagnosis method, combining signal analysis and classification models, to the rotor defect problems of motors. Two manufacture technologies, nonmagnetic high-temperature resistant ceramic adhesive and electrical discharge machining (EDM), are applied to make testing samples, including blowhole and perforation defects [...] Read more.

This paper proposes a diagnosis method, combining signal analysis and classification models, to the rotor defect problems of motors. Two manufacture technologies, nonmagnetic high-temperature resistant ceramic adhesive and electrical discharge machining (EDM), are applied to make testing samples, including blowhole and perforation defects of rotor bars in this study. The typical multiresolution analysis (MRA) model is used to analyze acquired source current signals of motors. The features are extracted from the signals of each column of MRA-matrix, including maximum, mean, standard deviation, root-mean-square, and summation. The typical back-propagation neural network (BPNN) model is used to diagnose the rotor bar defects of motors, and then the various signal-to-noise ratio (SNR) of white Gaussian noise (WGN), 30, 25, and 20 dB, are added to the signals to verify the robustness of the proposed method. The results show the availability of the proposed method to diagnose the rotor bar defects of motors. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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19 pages, 2934 KiB

Open AccessArticle

A Trajectory for Advancing the Meta-Cognitive Solving of Mathematics-Based Programming Problems with Scratch

by Wajeeh Daher, Nimer Baya’a, Otman Jaber and Juhaina Awawdeh Shahbari

Symmetry 2020, 12(10), 1627; https://doi.org/10.3390/sym12101627 - 02 Oct 2020

Cited by 18 | Viewed by 2575

Abstract

It is the intention of the current study to suggest a trajectory for the advancement of prospective mathematics teachers’ use of meta-cognitive skills in solving mathematics-based programming problems with Scratch. Scratch is a code-based program that can be utilized in teaching various disciplines, [...] Read more.

It is the intention of the current study to suggest a trajectory for the advancement of prospective mathematics teachers’ use of meta-cognitive skills in solving mathematics-based programming problems with Scratch. Scratch is a code-based program that can be utilized in teaching various disciplines, especially geometry and its rich range of subjects such as the topic of symmetry. The present study suggests that advancing prospective teachers’ meta-cognitive skills in the Scratch environment could be done through problem solving and negotiations. The present paper analyzed the implementation of the trajectory by two pedagogic supervisors who attempted, in the frame of one-year preparation (2018–2019), to educate 18 prospective teachers to use meta-cognitive skills in mathematics-based programming activities, where this attempt was based on problem solving and negotiation processes. Data were collected through videoing and recording the learning sessions of the prospective teachers and was analyzed using deductive and inductive constant comparison methods. The deductive analysis utilized theoretical models of meta-cognitive processes and negotiation processes. The research results indicated that the negotiation processes supported the development of the prospective teachers’ meta-cognitive processes in solving mathematics-based programming problems with Scratch. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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9 pages, 1607 KiB

Open AccessArticle

Teaching Theory of Probability and Statistics during the Covid-19 Emergency

by Andrea Jahodova Berkova and Radek Nemec

Symmetry 2020, 12(9), 1577; https://doi.org/10.3390/sym12091577 - 22 Sep 2020

Cited by 7 | Viewed by 4479

Abstract

The state of emergency caused by the covid-19 pandemic has shown that teaching at this time is not easy. Teachers have to make more use of distance education and students have to adapt to that. Classic face-to-face study is not possible but asymmetric [...] Read more.

The state of emergency caused by the covid-19 pandemic has shown that teaching at this time is not easy. Teachers have to make more use of distance education and students have to adapt to that. Classic face-to-face study is not possible but asymmetric communication between the teacher and his students may be replaced by greater student independence and greater student effort. Within the subject theory of probability and statistics, a questionnaire was created to find how students manage distance education. It has been found out that they use the prepared tutorial videos and online assignments (in WeBWork platform) the most. They expressed that distance education prepared by the teacher can replace face-to-face study, but this form of learning is much more demanding and therefore they prefer classic face-to-face study. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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12 pages, 691 KiB

Open AccessArticle

Prospective Teachers’ Development of Meta-Cognitive Functions in Solving Mathematical-Based Programming Problems with Scratch

by Juhaina Awawdeh Shahbari, Wajeeh Daher, Nimer Baya’a and Otman Jaber

Symmetry 2020, 12(9), 1569; https://doi.org/10.3390/sym12091569 - 22 Sep 2020

Cited by 9 | Viewed by 2585

Abstract

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study [...] Read more.

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study was conducted among 18 prospective teachers, who engaged in a sequence of mathematical problems that utilize Scratch. The data sources included video recordings and solution reports while they performed mathematical problems. The findings indicated that the participants developed their meta-cognitive functions as problem solvers related to both mathematics and programming aspects. The findings also indicated that the participants developed regulation meta-cognitive functions more than awareness and evaluation ones in mathematical and programming aspects. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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15 pages, 1484 KiB

Open AccessArticle

A Heuristic Simulation–Optimization Approach to Information Sharing in Supply Chains

by KyoungJong Park

Symmetry 2020, 12(8), 1319; https://doi.org/10.3390/sym12081319 - 07 Aug 2020

Cited by 8 | Viewed by 2023

Abstract

The sustainability of the supply chain is possible only if the profitability of all the tiers participating in that supply chain is guaranteed. The profitability of each of these tiers is ensured if information sharing as well as an effective and seamless coordination [...] Read more.

The sustainability of the supply chain is possible only if the profitability of all the tiers participating in that supply chain is guaranteed. The profitability of each of these tiers is ensured if information sharing as well as an effective and seamless coordination system are realized between the tiers. This process reduces the influence of an important risk factor known as the bullwhip effect. The purpose of the current study is to determine the necessary information sharing level to optimize the supply chain that has asymmetric flows of input and output values and to examine the effects of information sharing on the order fill rate (OFR) and total inventory cost (TIC) of the supply chain through analysis of variance (ANOVA) testing. In this work, the supply chain was optimized by using the particle swarm optimization (PSO) technique, with an objective function that assumes the maximization of OFR and minimization of TIC. The proposed method showed excellent results in comparing the mean, variance, and coefficient of variation. In addition, the method used the ANOVA test with a 5% significance level to verify the impact of the information sharing level. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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