Symmetry doi: 10.3390/sym12101605

Authors: Kountchev Mironov Kountcheva

In this work is introduced one new hierarchical decomposition for cubical tensor of size 2n, based on the well-known orthogonal transforms Principal Component Analysis and Karhunen&ndash;Loeve Transform. The decomposition is called 3D Frequency-Ordered Hierarchical KLT (3D-FOHKLT). It is separable, and its calculation is based on the one-dimensional Frequency-Ordered Hierarchical KLT (1D-FOHKLT) applied on a sequence of matrices. The transform matrix is the product of n sparse matrices, symmetrical at the point of their main diagonal. In particular, for the case in which the angles which define the transform coefficients for the couples of matrices in each hierarchical level of 1D-FOHKLT are equal to &pi;/4, the transform coincides with this of the frequency-ordered 1D Walsh&ndash;Hadamard. Compared to the hierarchical decompositions of Tucker (H-Tucker) and the Tensor-Train (TT), the offered approach does not ensure full decorrelation between its components, but is close to the maximum. On the other hand, the evaluation of the computational complexity (CC) of the new decomposition proves that it is lower than that of the above-mentioned similar approaches. In correspondence with the comparison results for H-Tucker and TT, the CC decreases fast together with the increase of the hierarchical levels&rsquo; number, n. An additional advantage of 3D-FOHKLT is that it is based on the use of operations of low complexity, while the similar famous decompositions need large numbers of iterations to achieve the coveted accuracy.

]]>Symmetry doi: 10.3390/sym12101604

Authors: Shu-Jung Chen Yung-Chuan Wu

When using a MEMS sensor to measure the vacuum of a medium, the transition flow between the viscous flow and molar flow is usually used to describe the gas convection due to the physical principle, which is difficult to study through analysis and simulation. In this study, the description of gas flow under different pressures in a CMOS-MEMS vacuum sensors has been incorporated into a new behavioral ANSYS model. The proposed model was built and the characteristic parameters in the model were obtained based on a CMOS-MEMS thermopile patterned with circular symmetry and an embedded heater as a heat source. It contains a characteristic length to describe the effective distance of heat dissipation to the silicon substrate, and the corresponding transition pressure to describe the symmetrical phenomenon of gas heat conduction. The macro-model is based on the description of the physical characteristics of heat transfer and the characteristic parameters of the CMOS-MEMS vacuum sensor. The characteristic length of 49 &mu;m and the corresponding transition pressure of 2396 mTorr for the thermoelectric-type vacuum sensor were extracted and verified successfully. The results show that the average error for the prediction of vacuum sensing by the macro-model we proposed is about 1.11%. This approach provides more applications for vacuum analysis. It can reduce the complexity of simulation and analysis and provide better simulation effects, including gas conduction mechanisms.

]]>Symmetry doi: 10.3390/sym12101603

Authors: Keiji Nakatsugawa Motoo Ohaga Toshiyuki Fujii Toyoki Matsuyama Satoshi Tanda

The well known Nakano&ndash;Nishijima&ndash;Gell-Mann (NNG) formula relates certain quantum numbers of elementary particles to their charge number. This equation, which phenomenologically introduces the quantum numbers Iz (isospin), S (strangeness), etc., is constructed using group theory with real numbers R. But, using a discrete Galois field Fp instead of R and assuring the fundamental invariance laws such as unitarity, Lorentz invariance, and gauge invariance, we derive the NNG formula deductively from Meson (two quarks) and Baryon (three quarks) representations in a unified way. Moreover, we show that quark confinement ascribes to the inevitable fractionality caused by coprimeness between half-integer (1/2) of isospin and number of composite particles (e.g., three).

]]>Symmetry doi: 10.3390/sym12101602

Authors: Buntam Permpoonsinsup Surin

Moisture is one of the most important factors impacting the talc pellet process. In this study, a hybrid model (HM) based on the combination of intelligent algorithms, self-organizing map (SOM), the adaptive neuron fuzzy inference system (ANFIS) and metaheuristic optimizations, genetic algorithm (GA) and particle swarm optimization (PSO) is introduced, namely, HM-GA and HM-PSO. The main purpose is to predict the moisture in the talc pellet process related to symmetry in the aspect of real-world application problem. In the combination process, SOM classifies the suitable input data. The GA and PSO, as the training algorithms of ANFIS, are investigated to compare the prediction skill. Five factors, including talc powder, water, temperature, feed speed, and air flow of 52 experiment cases designed by central composite design (CCD), are the training set data. Three different measures evaluate the capacity of moisture prediction. The comparison results show that the HM-PSO can provide the smallest difference between train and test datasets under the condition of the moisture being less than 5%. As a result, the HM-PSO model achieves the best result in predicting the moisture for the talc pellet process with R = 0.9539, RMSE = 1.0693, and AAD = 0.393, compared to others.

]]>Symmetry doi: 10.3390/sym12101598

Authors: Howard S. Cohl Roberto S. Costas-Santos

For the associated Legendre and Ferrers functions of the first and second kind, we obtain new multi-derivative and multi-integral representation formulas. The multi-integral representation formulas that we derive for these functions generalize some classical multi-integration formulas. As a result of the determination of these formulae, we compute some interesting special values and integral representations for certain particular combinations of the degree and order, including the case where there is symmetry and antisymmetry for the degree and order parameters. As a consequence of our analysis, we obtain some new results for the associated Legendre function of the second kind, including parameter values for which this function is identically zero.

]]>Symmetry doi: 10.3390/sym12101599

Authors: Henryk A. Witek Johanna Langner

We present a complete set of closed-form formulas for the ZZ polynomials of five classes of composite Kekul&eacute;an benzenoids that can be obtained by overlapping two parallelograms: generalized ribbons Rb, parallelograms M, vertically overlapping parallelograms MvM, horizontally overlapping parallelograms MhM, and intersecting parallelograms MxM. All formulas have the form of multiple sums over binomial coefficients. Three of the formulas are given with a proof based on the interface theory of benzenoids, while the remaining two formulas are presented as conjectures verified via extensive numerical tests. Both of the conjectured formulas have the form of a 2&times;2 determinant bearing close structural resemblance to analogous formulas for the number of Kekul&eacute; structures derived from the John-Sachs theory of Kekul&eacute; structures.

]]>Symmetry doi: 10.3390/sym12101600

Authors: Simon Gluzman

We discuss and apply various direct extrapolation methods for calculation of the critical points and indices from the perturbative expansions my means of Pad&eacute;-techniques and their various post-Pad&eacute; extensions by means of root and factor approximants. Factor approximants are applied to finding critical points. Roots are employed within the context of finding critical index. Additive self-similar approximants are discussed and DLog additive recursive approximants are introduced as their generalization. They are applied to the problem of interpolation. Several examples of interpolation are considered.

]]>Symmetry doi: 10.3390/sym12101601

Authors: Rahimi Eassa Elrefaei

In Requirement Engineering, software requirements are classified into two main categories: Functional Requirement (FR) and Non-Functional Requirement (NFR). FR describes user and system goals. NFR includes all constraints on services and functions. Deeper classification of those two categories facilitates the software development process. There are many techniques for classifying FR; some of them are Machine Learning (ML) techniques, and others are traditional. To date, the classification accuracy has not been satisfactory. In this paper, we introduce a new ensemble ML technique for classifying FR statements to improve their accuracy and availability. This technique combines different ML models and uses enhanced accuracy as a weight in the weighted ensemble voting approach. The five combined models are Na&iuml;ve Bayes, Support Vector Machine (SVM), Decision Tree, Logistic Regression, and Support Vector Classification (SVC). The technique was implemented, trained, and tested using a collected dataset. The accuracy of classifying FR was 99.45%, and the required time was 0.7 s.

]]>Symmetry doi: 10.3390/sym12101597

Authors: Alan Mendes Marotta Vinicius Mariano Gonçalves Carlos Andrey Maia

Tropical Algebra is used to model the dynamics of Timed Event Graphs (TEG), a particular class of Timed Discrete-Event System (TDES) in which we are interested only in synchronization and delay phenomena. Whenever this TEG has control inputs, we can use them to control the synchronization of the system to achieve some objective. Thus, this paper formulates a framework based on tropical algebra and lexicographic optimization to synchronize a TEG when dealing with many synchronization objectives that are ranked in previous priority order. We call this kind of problem the Tropical Lexicographic Synchronization Optimization (TLSO). This work develops a solution to this problem, based on Tropical Fractional Linear Programming (TFLP) and lexicographic optimization concepts. In this way, the basics of tropical algebra are determined, including essential terms to this paper, such as left and right residuations, and the following stages of the solution to the TLSO problem are explained. Therefore, this work presents a general framework based on structured algebraic models with application to TEG synchronization. By synchronization, we mean balancing and organizing events chronologically in order to achieve the desired goal. So, we are dealing with concepts closely related to symmetry ones. An illustrative numerical example is presented, which demonstrates the implementation of the proposed algorithms. The acquired results confirm the efficiency of the proposed methodology. Codes used for implementing the algorithms are listed in the appendix section of the article.

]]>Symmetry doi: 10.3390/sym12101596

Authors: V. R. Shaginyan A. Z. Msezane G. S. Japaridze V. A. Stephanovich

In this review, we consider the time reversal T and particle-antiparticle C symmetries that, being most fundamental, can be violated at microscopic level by a weak interaction. The notable example here is from condensed matter, where strongly correlated Fermi systems like heavy-fermion metals and high Tc superconductors exhibit C and T symmetries violation due to so-called non-Fermi liquid (NFL) behavior. In these systems, tunneling differential conductivity (or resistivity) is a very sensitive tool to experimentally test the above symmetry break. When a strongly correlated Fermi system turns out to be near the topological fermion condensation quantum phase transition (FCQPT), it exhibits the NFL properties, so that the C symmetry breaks down, making the differential tunneling conductivity to be an asymmetric function of the bias voltage V. This asymmetry does not take place in normal metals, where Landau Fermi liquid (LFL) theory holds. Under the application of magnetic field, a heavy fermion metal transits to the LFL state, and &sigma;(V) becomes symmetric function of V. These findings are in good agreement with experimental observations. We suggest that the same topological FCQPT underlies the baryon asymmetry in the Universe. We demonstrate that the most fundamental features of the nature are defined by its topological and symmetry properties.

]]>Symmetry doi: 10.3390/sym12101595

Authors: Mikulas Huba Pavol Bistak Damir Vrancic Katarina Zakova

This paper analyzes the first-order and first-order time-delayed systems control approaches, focusing mainly on unstable systems. First, it discusses asymmetries between the disturbance observer-based (DOB) control with decoupled tracking and the disturbance rejection responses, stressing applications to stable and unstable plants. The paper analyzes some DOB-based control solutions for unstable systems which do not use internal closed-loop stabilization. The novelty of the paper is thorough study accompanied with a comprehensive explanation of the differences between two distinct approaches: the transfer-function- and the closed-loop-based feedforward control approach from the point of view of control constraints. It is clearly illustrated that the main cause of instability of DOB-based approaches, applied to unstable systems, is given by their effort to impose on the system the unstable dynamics of the chosen nominal process model. It is also shown that the closed-loop stability of the DOB-based control, applied to the unstable systems, can be restored by using the supervising reference model control (RMC). The main novelty of the proposed approach is that its eliminates the mentioned stability problems while maintaining the full functionality of the chosen control structures. RMC has so far only been implemented for generating a setpoint feedforward signal. However, by generalization of this approach for disturbance rejection, the methodology of DOB design, based on nominal models, can be extended to the control of unstable systems. Without the use of disturbance reference models, the interactions of the master stabilizer with disturbance compensation cannot be eliminated. Without the internal stabilization, the stable transients can only be achieved by designing controllers based on stable models, instead of unstable ones. The existing modifications of DOB-based schemes for unstable plants, proposed in some references, are shown to lead to traditional Proportional-Integrative (PI) control, thus losing all the advantages over the PI controllers. In all the considered structures, the role of integrating models is also emphasized.

]]>Symmetry doi: 10.3390/sym12101594

Authors: Samih M. Mostafa Abdelrahman S. Eladimy Safwat Hamad Hirofumi Amano

In most scientific studies such as data analysis, the existence of missing data is a critical problem, and selecting the appropriate approach to deal with missing data is a challenge. In this paper, the authors perform a fair comparative study of some practical imputation methods used for handling missing values against two proposed imputation algorithms. The proposed algorithms depend on the Bayesian Ridge technique under two different feature selection conditions. The proposed algorithms differ from the existing approaches in that they cumulate the imputed features; those imputed features will be incorporated within the Bayesian Ridge equation for predicting the missing values in the next incomplete selected feature. The authors applied the proposed algorithms on eight datasets with different amount of missing values created from different missingness mechanisms. The performance was measured in terms of imputation time, root-mean-square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). The results showed that the performance varies depending on missing values percentage, size of the dataset, and the missingness mechanism. In addition, the performance of the proposed methods is slightly better.

]]>Symmetry doi: 10.3390/sym12101593

Authors: Patricio Ramírez-Correa Catalina Ramírez-Rivas Jorge Alfaro-Pérez Ari Melo-Mariano

The explanation of behaviors concerning telemedicine acceptance is an evolving area of study. This topic is currently more critical than ever, given that the COVID-19 pandemic is making resources scarcer within the health industry. The objective of this study is to determine which model, the Theory of Planned Behavior or the Technology Acceptance Model, provides greater explanatory power for the adoption of telemedicine addressing outlier-associated bias. We carried out an online survey of patients. The data obtained through the survey were analyzed using both consistent partial least squares path modeling (PLSc) and robust PLSc. The latter used a robust estimator designed for elliptically symmetric unimodal distribution. Both estimation techniques led to similar results, without inconsistencies in interpretation. In short, the results indicate that the Theory of Planned Behavior Model provides a significant explanatory power. Furthermore, the findings show that attitude has the most substantial direct effect on behavioral intention to use telemedicine systems.

]]>Symmetry doi: 10.3390/sym12101592

Authors: Jong-Hyun Kim Jung Lee Sun-Jeong Kim

In this paper, we propose a method to efficiently control the path of non-playable characters (NPC) in an interactive virtual environment such as a game or virtual reality (VR) by calculating a weight map and path similarity based on the user&rsquo;s path. Our method automatically constructs a navigation mesh that provides a new route to the NPC by referring to the user&rsquo;s trajectory. Our method finds more paths that users usually go through as time passes, and the number of users increases. Accordingly, the paths that NPCs can traverse automatically are updated adaptively to the virtual environment. In addition, NPC agents can move smartly by assigning high weights to the user&rsquo;s preferred paths. We tested the usefulness of the proposed method through several example scenarios in an interactive environment such as a video game or VR, and this method can be easily applied to various types of navigation based on the interactive environment.

]]>Symmetry doi: 10.3390/sym12101591

Authors: Wan Nor Nabila Nadia Wan Zuki Zhibin Du Muhammad Kamran Jamil Roslan Hasni

Let G be a simple, connected and undirected graph. The atom-bond connectivity index (ABC(G)) and Randić index (R(G)) are the two most well known topological indices. Recently, Ali and Du (2017) introduced the difference between atom-bond connectivity and Randić indices, denoted as ABC&minus;R index. In this paper, we determine the fourth, the fifth and the sixth maximum chemical trees values of ABC&minus;R for chemical trees, and characterize the corresponding extremal graphs. We also obtain an upper bound for ABC&minus;R index of such trees with given number of pendant vertices. The role of symmetry has great importance in different areas of graph theory especially in chemical graph theory.

]]>Symmetry doi: 10.3390/sym12101589

Authors: Zeyuan Hu Eung-Joo Lee

Traditional convolution neural networks have achieved great success in human action recognition. However, it is challenging to establish effective associations between different human bone nodes to capture detailed information. In this paper, we propose a dual attention-guided multiscale dynamic aggregate graph convolution neural network (DAG-GCN) for skeleton-based human action recognition. Our goal is to explore the best correlation and determine high-level semantic features. First, a multiscale dynamic aggregate GCN module is used to capture important semantic information and to establish dependence relationships for different bone nodes. Second, the higher level semantic feature is further refined, and the semantic relevance is emphasized through a dual attention guidance module. In addition, we exploit the relationship of joints hierarchically and the spatial temporal correlations through two modules. Experiments with the DAG-GCN method result in good performance on the NTU-60-RGB+D and NTU-120-RGB+D datasets. The accuracy is 95.76% and 90.01%, respectively, for the cross (X)-View and X-Subon the NTU60dataset.

]]>Symmetry doi: 10.3390/sym12101590

Authors: Georg Junker

Hamiltonians describing the relativistic quantum dynamics of a particle with an arbitrary but fixed spin are shown to exhibit a supersymmetric structure when the even and odd elements of the Hamiltonian commute. Here, the supercharges transform between energy eigenstates of positive and negative energy. For such supersymmetric Hamiltonians, an exact Foldy&ndash;Wouthuysen transformation exists which brings it into a block-diagonal form separating the positive and negative energy subspaces. The relativistic dynamics of a charged particle in a magnetic field are considered for the case of a scalar (spin-zero) boson obeying the Klein&ndash;Gordon equation, a Dirac (spin one-half) fermion and a vector (spin-one) boson characterised by the Proca equation. In the latter case, supersymmetry implies for the Land&eacute; g-factor g=2.

]]>Symmetry doi: 10.3390/sym12101588

Authors: Tabinda Nahid Parvez Alam Junesang Choi

The truncated exponential polynomials em(x) (1), their extensions, and certain newly-introduced polynomials which combine the truncated exponential polynomials with other known polynomials have been investigated and applied in various ways. In this paper, by incorporating the Appell-type Changhee polynomials Chn*(x) (10) and the truncated exponential polynomials in a natural way, we aim to introduce so-called truncated-exponential-based Appell-type Changhee polynomials eCn*(x) in Definition 1. Then, we investigate certain properties and identities for these new polynomials such as explicit representation, addition formulas, recurrence relations, differential and integral formulas, and some related inequalities. We also present some integral inequalities involving these polynomials eCn*(x). Further we discuss zero distributions of these polynomials by observing their graphs drawn by Mathematica. Lastly some open questions are suggested.

]]>Symmetry doi: 10.3390/sym12101587

Authors: Oscar Danilo Montoya Walter Gil-González Alexander Molina-Cabrera

In this study, the voltage stability margin for direct current (DC) networks in the presence of constant power loads is analyzed using a proposed convex mathematical reformulation. This convex model is developed by employing a second-order cone programming (SOCP) optimization that transforms the non-linear non-convex original formulation by reformulating the power balance constraint. The main advantage of the SOCP model is that the optimal global solution of a problem can be obtained by transforming hyperbolic constraints into norm constraints. Two test systems are considered to validate the proposed SOCP model. Both systems have been reported in specialized literature with 6 and 69 nodes. Three comparative methods are considered: (a) the Newton-Raphson approximation based on the determinants of the Jacobian matrices, (b) semidefinite programming models, and (c) the exact non-linear formulation. All the numerical simulations are conducted using the MATLAB and GAMS software. The effectiveness of the proposed SOCP model in addressing the voltage stability problem in DC grids is verified by comparing the objective function values and processing time.

]]>Symmetry doi: 10.3390/sym12101586

Authors: Yury Stepanyants

The asymptotic approach is suggested for the description of interacting surface and internal oceanic solitary waves. This approach allows one to describe stationary moving symmetric wave patterns consisting of two plane solitary waves of equal amplitudes moving at an angle to each other. The results obtained within the approximate asymptotic theory are validated by comparison with the exact two-soliton solution of the Kadomtsev&ndash;Petviashvili equation (KP2-equation). The suggested approach is equally applicable to a wide class of non-integrable equations too. As an example, the asymptotic theory is applied to the description of wave patterns in the 2D Benjamin&ndash;Ono equation describing internal waves in the infinitely deep ocean containing a relatively thin one of the layers.

]]>Symmetry doi: 10.3390/sym12101582

Authors: Saeed Kosari Yongsheng Rao Huiqin Jiang Xinyue Liu Pu Wu Zehui Shao

Fuzzy graph models enjoy the ubiquity of being in natural and human-made structures, namely dynamic process in physical, biological and social systems. As a result of inconsistent and indeterminate information inherent in real-life problems which are often uncertain, it is highly difficult for an expert to model those problems based on a fuzzy graph (FG). Vague graph structure (VGS) can deal with the uncertainty associated with the inconsistent and indeterminate information of any real-world problem, where fuzzy graphs may fail to reveal satisfactory results. Likewise, VGSs are very useful tools for the study of different domains of computer science such as networking, capturing the image, clustering, and also other issues like bioscience, medical science, and traffic plan. The limitations of past definitions in fuzzy graphs have led us to present new definitions in VGSs. Operations are conveniently used in many combinatorial applications. In various situations, they present a suitable construction means; therefore, in this research, three new operations on VGSs, namely, maximal product, rejection, residue product were presented, and some results concerning their degrees and total degrees were introduced. Irregularity definitions have been of high significance in the network heterogeneity study, which have implications in networks found across biology, ecology and economy; so special concepts of irregular VGSs with several key properties were explained. Today one of the most important applications of decision making is in medical science for diagnosing the patient&rsquo;s disease. Hence, we recommend an application of VGS in medical diagnosis.

]]>Symmetry doi: 10.3390/sym12101585

Authors: Masoomeh Zeinalnezhad Abdoulmohammad Gholamzadeh Chofreh Feybi Ariani Goni Jiří Jaromír Klemeš

Reliability-Centred Maintenance (RCM) is a strategic process to improve the maintenance planning of companies which contributes to sustainable production. This method has been applied by numerous industries to achieve an efficient maintenance process, but many have not fully completed their goals. The reason for this failure is that RCM implementation is complex, and organisations need to have adequate preparations before they implement it. In the pre-implementation phase, it is necessary to know the number of Critical Success Factors (CSFs) as a critical measure for implementing the RCM method successfully. Therefore, it is important for practitioners to apply a symmetric mechanism involving fuzzy systems to achieve the desired RCM implementation. There are a limited number of studies that have observed these factors regarding the characteristics of oil and gas companies, especially in the pre-implementation phase. Addressing RCM pre-implementation issues is of high importance from the economic perspective of sustainability for oil and gas organisations. The objective of this study is to investigate significant items in RCM pre-implementation through a combination of quantitative and qualitative analyses. The Nominal Group Technique (NGT) method is applied by gaining the opinion of experts to determine the factors and prioritising them using mathematical modelling. A group of related experts from the oil and gas industry were initially interviewed and surveyed to determine the critical success factors. These identified factors were then analysed using quantitative analysis to identify the important degrees and scored using Fuzzy Analytic Network Process (FANP). Fifteen major factors affecting the criticality of successful RCM implementation have been identified and prioritised, based on their weights. The model proposed in this study could be used as a guideline for assessing CSFs in other countries. To apply the proposed model in different contexts, it needs to be modified according to the needs, policies, and perspectives of each country.

]]>Symmetry doi: 10.3390/sym12101584

Authors: Wolfgang Schreiner William Steingartner Valerie Novitzká

We present a categorical formalization of a variant of first-order logic. Unlike other texts on this topic, the goal of this paper is to give a very transparent and self-contained account without requiring more background than basic logic and set theory. Our focus is to show how the semantics of first-order formulas can be derived from their usual deduction rules. For understanding the core ideas, it is not necessary to investigate the internal term structure of atomic formulas, thus we abstract atomic formulas to (syntactically opaque) relations; in this sense, our variant of first-order logic is &ldquo;relational&rdquo;. While the derived semantics is based on categorical principles (even the duality that arises from a symmetry between two ways of looking at something where there is no reason to choose one over the other), it is nevertheless &ldquo;constructive&rdquo; in that it describes explicit computations of the truth values of formulas. We demonstrate this by modeling the categorical semantics in the RISCAL (RISC Algorithm Language) system which allows us to validate the core propositions by automatically checking them in finite models.

]]>Symmetry doi: 10.3390/sym12101583

Authors: Ángel Luis Perales Gómez Lorenzo Fernández Maimó Alberto Huertas Celdrán Félix J. García Clemente

Industrial Control Systems (ICSs) are widely used in critical infrastructures to support the essential services of society. Therefore, their protection against terrorist activities, natural disasters, and cyber threats is critical. Diverse cyber attack detection systems have been proposed over the years, in which each proposal has applied different steps and methods. However, there is a significant gap in the literature regarding methodologies to detect cyber attacks in ICS scenarios. The lack of such methodologies prevents researchers from being able to accurately compare proposals and results. In this work, we present a Methodology for Anomaly Detection in Industrial Control Systems (MADICS) to detect cyber attacks in ICS scenarios, which is intended to provide a guideline for future works in the field. MADICS is based on a semi-supervised anomaly detection paradigm and makes use of deep learning algorithms to model ICS behaviors. It consists of five main steps, focused on pre-processing the dataset to be used with the machine learning and deep learning algorithms; performing feature filtering to remove those features that do not meet the requirements; feature extraction processes to obtain higher order features; selecting, fine-tuning, and training the most appropriate model; and validating the model performance. In order to validate MADICS, we used the popular Secure Water Treatment (SWaT) dataset, which was collected from a fully operational water treatment plant. The experiments demonstrate that, using MADICS, we can achieve a state-of-the-art precision of 0.984 (as well as a recall of 0.750 and F1-score of 0.851), which is above the average of other works, proving that the proposed methodology is suitable for use in real ICS scenarios.

]]>Symmetry doi: 10.3390/sym12101581

Authors: Oscar J. Pellicer-Valero José D. Martín-Guerrero Margarita I. Cigarán-Méndez Carmen Écija-Gallardo César Fernández-de-las-Peñas Esperanza Navarro-Pardo

A better understanding of the connection between risk factors associated with pain and function may assist therapists in optimizing therapeutic programs. This study applied mathematical modeling to analyze the relationship of psychological, psychophysical, and motor variables with pain, function, and symptom severity using Bayesian linear regressions (BLR) and self-organizing maps (SOMs) in carpal tunnel syndrome (CTS). The novelty of this work was a transfer of the symmetry mathematical background to a neuropathic pain condition, whose symptoms can be either unilateral or bilateral. Duration of symptoms, pain intensity, function, symptom severity, depressive levels, pinch tip grip force, and pressure pain thresholds (PPTs) over the ulnar, radial, and median nerve trunks, the cervical spine, the carpal tunnel, and the tibialis anterior were collected in 208 women suffering from CTS. The first BLR model revealed that symptom severity, PPTs over the radial nerve, and function had significant correlations with pain intensity. The second BLR showed that symptom severity, depressive levels, pain intensity, and years with pain were associated with function. The third model demonstrated that pain intensity and function were associated with symptom severity. The SOMs visualized these correlations among variables, i.e., clinical, psychophysical, and physical, and identified a subgroup of women with CTS exhibiting worse clinical features, higher pressure sensitivity, and lower pinch tip grip force. Therefore, the application of mathematical modeling identified some interactions among the intensity of pain, function, and symptom severity in women with CTS.

]]>Symmetry doi: 10.3390/sym12101580

Authors: Dawid Warchoł Tomasz Kapuściński

The paper presents a method for the recognition of human actions based on skeletal data. A novel Bone Pair Descriptor is proposed, which encodes the angular relations between pairs of bones. Its features are combined with Distance Descriptor, previously used for hand posture recognition, which describes relationships between distances of skeletal joints. Five different time series classification methods are tested. The selection of features, input joints, and bones is performed. The experiments are conducted using person-independent validation tests and a challenging, publicly available dataset of human actions. The proposed method is compared with other approaches found in the literature achieving relatively good results.

]]>Symmetry doi: 10.3390/sym12101579

Authors: Krzysztof Żamojć Karolina Streńska Dariusz Wyrzykowski Lech Chmurzyński Joanna Makowska

In the following paper, we present the results of our studies on the interactions of the A&beta;1-42 peptide and its three short fragments, namely A&beta;5-16 (RHDSGYEVHHQK; HZ1), A&beta;8-13 (SGYEVH; HZ2), and A&beta;8-12 (SGYEV; HZ3) with selected painkillers (ibuprofen and aspirin) and compounds of natural origin (anabasine and epinephrine). Steady-state fluorescence spectroscopy was used to study the binding properties of the selected systems. Additionally, based on molecular dynamics (MD) calculations supported by NMR-derived restrains, we have proposed the most likely area of the interactions of A&beta;1-42 and A&beta;5-16 peptides with the investigated compounds. The influence of symmetrically oriented side chains of amino acid residues present in the first part of the A&beta;1-42 sequence on the stability of the resulting complexes has been discussed. Finally, the changes in the peptide structures on account of complex formation were analyzed.

]]>Symmetry doi: 10.3390/sym12091578

Authors: Krystian Jobczyk

The natural transformation constitutes one of the most important entity of category theory and it introduces a piece of sophisticated dynamism to the categorial structures. Each natural transformation forms a unique mapping between the so-called functors, which live between categories. In the most simple contexts, natural transformations may be recognized by commutativity of diagrams, which determine them. In fact, the natural transformation does not form any single mapping, but a pair of two components, which&ndash;together with the commutativity condition itself&ndash;introduces a kind of a symmetry to the functor diagrams. Meanwhile, the general form of the natural transformation may be predicted by means the so-called Yoneda&rsquo;s lemma in each scenario based on two-valued logic. Meanwhile, the situation may be radically different if we deal with multi-diagrams (instead of the single ones) and if we exchange the two-valued scenario for a multi-valued or fuzzy one. Due to this background&ndash;the paper introduces a new concept of multi-fuzzy natural transformation. Its definition exploits the notion of fuzzy natural transformation. Moreover, a multi-fuzzy Yoneda&rsquo;s lemma is formulated and proved. Finally, some references of these constructions to coding theory are elucidated in last parts of the paper.

]]>Symmetry doi: 10.3390/sym12091574

Authors: Aurélien Bailly-Reyre Hung T. Diep

We study in this paper the dynamics of molecules leading to the formation of nematic and smectic phases using a mobile 6-state Potts spin model with Monte Carlo simulation. Each Potts state represents a molecular orientation. We show that, with the choice of an appropriate microscopic Hamiltonian describing the interaction between individual molecules modeled by 6-state Potts spins, we obtain the structure of the smectic phase by cooling the molecules from the isotropic phase to low temperatures: molecules are ordered in independent equidistant layers. The isotropic-smectic phase transition is found to have a first-order character. The nematic phase is also obtained with the choice of another microscopic Hamiltonian. The isotropic-nematic phase transition is a second-order one. The real-time dynamics of the molecules leading to the liquid-crystal ordering in each case is shown by a video.

]]>Symmetry doi: 10.3390/sym12091577

Authors: Andrea Jahodova Berkova Radek Nemec

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.

]]>Symmetry doi: 10.3390/sym12091576

Authors: Gianmarco Baldini José L. Hernandez-Ramos Slawomir Nowak Ricardo Neisse Mateusz Nowak

It has been proven in research literature that the analysis of encrypted traffic with statistical analysis and machine learning can reveal the type of activities performed by a user accessing the network, thus leading to privacy risks. In particular, different types of traffic (e.g., skype, web access) can be identified by extracting time based features and using them in a classifier. Such privacy attacks are asymmetric because a limited amount of resources (e.g., machine learning algorithms) can extract information from encrypted traffic generated by cryptographic systems implemented with a significant amount of resources. To mitigate privacy risks, studies in research literature have proposed a number of techniques, but in most cases only a single technique is applied, which can lead to limited effectiveness. This paper proposes a mitigation approach for privacy risks related to the analysis of encrypted traffic which is based on the integration of three main components: (1) A machine learning component which proactively analyzes the encrypted traffic in the network to identify potential privacy threats and evaluate the effectiveness of various mitigation techniques (e.g., obfuscation), (2) a policy based component where policies are used to enforce privacy mitigation solutions in the network and (3) a network node profile component based on the Manufacturer Usage Description (MUD) standard to enable changes in the network nodes in the cases where the first two components are not effective in mitigating the privacy risks. This paper describes the different components and how they interact in a potential deployment scenario. The approach is evaluated on the public dataset ISCXVPN2016 and the results show that the privacy threat can be mitigated significantly by removing completely the identification of specific types of traffic or by decreasing the probability of their identification as in the case of VOIP by 50%, Chat by 40% and Browsing by 33%, thus reducing significantly the privacy risk.

]]>Symmetry doi: 10.3390/sym12091575

Authors: Konan-Marcelin Kouamé Hamid Mcheick Hicham Ajami

In this paper, we introduce a new kind of Service Level Agreement(SLA) Template to better control dynamically quality of medical monitoring platform service. Our approach is based on Health care system and Health Information Technology (HIT) research area, specifically the field of telemonitoring system for patients who suffer from chronic obstructive pulmonary disease (COPD). According to WHO statistics, COPD is the third leading cause of death worldwide. To this end, several solutions or platforms exist today to monitor COPD. Most of these platforms manage large volume of patient data. This can bring about quality and lost data problems. To address these issues, control mechanisms must be proposed and designed to improve the quality of service (QoS) on these platforms. A platform with continuously monitored QoS can save patients&rsquo; lives and reduce data quality risk. In this article, we propose an ontology that uses SLAs data from COPD monitoring platforms with dynamic data from a patient context. We dynamically calculate the number of patient data incidents and the number of service request incidents from two dynamic contexts: SLA and the patient context. If the number of incidents is higher than what is expected in the SLA, then alerts are sent to the interface parties in real time. Finally, the contribution of this article is the proposed virtual SLA template to better control SLA violation and improve quality of medical monitoring platforms services.

]]>Symmetry doi: 10.3390/sym12091573

Authors: Tanmoy Paul

We provide various aspects of second rank antisymmetric Kalb&ndash;Ramond (KR) field in modified theories of gravity. The KR field energy density is found to decrease with the expansion of our universe at a faster rate in comparison to radiation and matter components. Thus as the universe evolves and cools down, the contribution of the KR field on the evolutionary process reduces significantly, and at present it almost does not affect the universe evolution. However the KR field has a significant contribution during early universe; in particular, it affects the beginning of inflation as well as increases the amount of primordial gravitational radiation and hence enlarges the value of tensor-to-scalar ratio in respect to the case when the KR field is absent. In regard to the KR field couplings, it turns out that in four dimensional higher curvature inflationary model the couplings of the KR field to other matter fields is given by 1/MPl (where MPl is known as the &ldquo;reduced Planck mass&rdquo; defined by MPl=18&pi;G with G is the &ldquo;Newton&rsquo;s constant&rdquo;) i.e., same as the usual gravity&ndash;matter coupling; however in the context of higher dimensional higher curvature model the KR couplings get an additional suppression over 1/MPl. Thus in comparison to the four dimensional model, the higher curvature braneworld scenario gives a better explanation of why the present universe carries practically no footprint of the Kalb&ndash;Ramond field. The higher curvature term in the higher dimensional gravitational action acts as a suitable stabilizing agent in the dynamical stabilization mechanism of the extra dimensional modulus field from the perspective of effective on-brane theory. Based on the evolution of KR field, one intriguing question can be&mdash;&ldquo;sitting in present day universe, how do we confirm the existence of the Kalb&ndash;Ramond field which has considerably low energy density (with respect to the other components) in our present universe but has a significant impact during early universe?&rdquo; We try to answer this question by the phenomena &ldquo;cosmological quantum entanglement&rdquo; which indeed carries the information of early universe. Finally, we briefly discuss some future perspectives of Kalb&ndash;Ramond cosmology at the end of the paper.

]]>Symmetry doi: 10.3390/sym12091571

Authors: Cornelia Dobrescu

The variety of viscoelastic systems and structures, for the most part, is studied analytically, with significant results. As a result of analytical, numerical and experimental research, which was conducted on a larger variety of linear viscoelastic systems and structures. We analyzed the dynamic behavior for the viscoelastic composite materials, anti-vibration viscous-elastic systems consisting of discrete physical devices, road structures consisting of natural soil structures with mineral aggregates and asphalt mixes, and mixed mechanic systems of insulation of the industrial vibrations consisting of elastic and viscous devices. In this context, the compound rheological model can be schematized as being V&minus;(E|V) type of the Newton Voigt&ndash;Kelvin model with inertial excited mass, applicable to linear viscoelastic materials.

]]>Symmetry doi: 10.3390/sym12091572

Authors: Chen Wang Jinbao Chen Shan Jia Heng Chen

Reusable launch vehicles (RLVs) are a solution for effective and economic transportation in future aerospace exploration. However, RLVs are limited to being used under simple landing conditions (small landing velocity and angle) due to their poor adaptability and the high rocket acceleration of current landing systems. In this paper, an adaptive RLV landing system with semi-active control is proposed. The proposed landing system can adjust the damping forces of primary strut dampers through semi-actively controlled currents in accordance with practical landing conditions. A landing dynamic model of the proposed landing system is built. According to the dynamic model, an light and effective RLV landing system is parametrically designed based on the response surface methodology. Dynamic simulations validate the proposed landing system under landing conditions including the highest rocket acceleration and the greatest damper compressions. The simulation results show that the proposed landing system with semi-active control has better landing performance than current landing systems that use passive liquid or liquid&ndash;honeycomb dampers. Additionally, the flexibility and friction of the structure are discussed in the simulations. Compared to rigid models, flexible models decrease rocket acceleration by 51% and 54% at the touch down moments under these two landing conditions, respectively. The friction increases rocket acceleration by less than 1%. However, both flexibility and friction have little influence on the distance between the rocket and ground, or the compression strokes of the dampers.

]]>Symmetry doi: 10.3390/sym12091570

Authors: Sakorn Mekruksavanich Anuchit Jitpattanakul Phichai Youplao Preecha Yupapin

The creation of the Internet of Things (IoT), along with the latest developments in wearable technology, has provided new opportunities in human activity recognition (HAR). The modern smartwatch offers the potential for data from sensors to be relayed to novel IoT platforms, which allow the constant tracking and monitoring of human movement and behavior. Recently, traditional activity recognition techniques have done research in advance by choosing machine learning methods such as artificial neural network, decision tree, support vector machine, and naive Bayes. Nonetheless, these conventional machine learning techniques depend inevitably on heuristically handcrafted feature extraction, in which human domain knowledge is normally limited. This work proposes a hybrid deep learning model called CNN-LSTM that employed Long Short-Term Memory (LSTM) networks for activity recognition with the Convolution Neural Network (CNN). The study makes use of HAR involving smartwatches to categorize hand movements. Using the study based on the Wireless Sensor Data Mining (WISDM) public benchmark dataset, the recognition abilities of the deep learning model can be accessed. The accuracy, precision, recall, and F-measure statistics are employed using the evaluation metrics to assess the recognition abilities of LSTM models proposed. The findings indicate that this hybrid deep learning model offers better performance than its rivals, where the achievement of 96.2% accuracy, while the f-measure is 96.3%, is obtained. The results show that the proposed CNN-LSTM can support an improvement of the performance of activity recognition.

]]>Symmetry doi: 10.3390/sym12091569

Authors: Juhaina Awawdeh Shahbari Wajeeh Daher Nimer Baya’a Otman Jaber

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&rsquo; 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.

]]>Symmetry doi: 10.3390/sym12091568

Authors: Tae Ho Cho

Generally, simulation models are constructed to replicate and predict the behavior of real systems that currently exist or are expected to exist in the future. Once a simulation model is implemented, the model can be connected to a real system for which the model has been built through sensors or networks so that important activities in the real system can be monitored indirectly through the model. This article proposes a modeling formalism BM-DEVS (Behavior Monitor-DEVS) that defines simulation models capable of monitoring the desired behavior patterns within the models so that the target system&rsquo;s behavior can be monitored indirectly. In BM-DEVS, an extension of classic Discrete Event System Specification (DEVS), the behavior to be monitored is expressed as a set of temporal logic (TL) production rules within a multi-component model that consists of multiple component models to be monitored. An inference engine module for reasoning with the TL rules is designed based on the abstract simulator that carries out instructions in the BM-DEVS models to perform the simulation process. The major application of BM-DEVS is in the design and implementation of the context-aware architecture needed for various intelligent systems as a core constituent. Essentially all systems where some form of behavior monitoring is required are candidate applications of BM-DEVS. This research is motivated by the view that there exists symmetry between the real-world and the cyber world, in that the problems in both environments should be expressed with the same basic constituents of time and space; this naturally leads to adopting spatiotemporal variables composed of simulation models and developing a problem solver that exploits these variables.

]]>Symmetry doi: 10.3390/sym12091567

Authors: Iram Noreen

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates C2 continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage.

]]>Symmetry doi: 10.3390/sym12091566

Authors: Zeinab Shahbazi Debapriya Hazra Sejoon Park Yung Cheol Byun

With the spread of COVID-19, the &ldquo;untact&rdquo; culture in South Korea is expanding and customers are increasingly seeking for online services. A recommendation system serves as a decision-making indicator that helps users by suggesting items to be purchased in the future by exploring the symmetry between multiple user activity characteristics. A plethora of approaches are employed by the scientific community to design recommendation systems, including collaborative filtering, stereotyping, and content-based filtering, etc. The current paradigm of recommendation systems favors collaborative filtering due to its significant potential to closely capture the interest of a user as compared to other approaches. The collaborative filtering harnesses features like user-profile details, visited pages, and click information to determine the interest of a user, thereby recommending the items that are related to the user&rsquo;s interest. The existing collaborative filtering approaches exploit implicit and explicit features and report either good classification or prediction outcome. These systems fail to exhibit good results for both measures at the same time. We believe that avoiding the recommendation of those items that have already been purchased could contribute to overcoming the said issue. In this study, we present a collaborative filtering-based algorithm to tackle big data of user with symmetric purchasing order and repetitive purchased products. The proposed algorithm relies on combining extreme gradient boosting machine learning architecture with word2vec mechanism to explore the purchased products based on the click patterns of users. Our algorithm improves the accuracy of predicting the relevant products to be recommended to the customers that are likely to be bought. The results are evaluated on the dataset that contains click-based features of users from an online shopping mall in Jeju Island, South Korea. We have evaluated Mean Absolute Error, Mean Square Error, and Root Mean Square Error for our proposed methodology and also other machine learning algorithms. Our proposed model generated the least error rate and enhanced the prediction accuracy of the recommendation system compared to other traditional approaches.

]]>Symmetry doi: 10.3390/sym12091565

Authors: Yingke Lei Da Li Haichuan Zhang Xin Li

Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over the past decade. Among the associated techniques, wireless fingerprint positioning has garnered much interest due to its compatibility with existing hardware. At present, with the widespread deployment of long-term evolution (LTE) networks and the uniqueness of wireless information fingerprints, fingerprint positioning based on LTE networks is the mainstream method for outdoor positioning. However, in order to improve its accuracy, this method needs to collect enough data at a large number of reference points, which is a labor-intensive task. In this paper, experimental data are collected at different reference points and then converted into wavelet feature maps. Then, a Deep Convolutional Generative Adversarial Network (DCGAN) is leveraged to generate a symmetric fingerprint database. Localization is then carried out by the proposed Deep Residual Network (Resnet), which is capable of learning reliable features from a fingerprint image database. To further increase the robustness of the positioning system, a variety of data enhancement methods are used. Finally, we experimentally demonstrate that the generated symmetric fingerprint database and proposed Resnet reduce the manpower required for fingerprint database collection and improve the accuracy of the outdoor positioning system.

]]>Symmetry doi: 10.3390/sym12091564

Authors: Xuchen Deng Shaojian Qu

Cross-docking is a new logistics model. The location planning of the crossover center is one of the important issues in logistics management. The location of the cross-docking center is not only a technical issue, but also a management issue. This is a decision made by senior leaders after considering various factors. Therefore, considering the decision-making method, a multicriteria group decision-making method based on an interval multi-granularity language model is proposed. It is suitable for non-static frameworks where the decision-making environment changes at any time during the process. Due to the uncertainty of the location information of the cross-docking center, experts can use their favorite language tag set to provide preferences, so a multi-granular interval fuzzy language model is used to enable experts to reliably provide preference values. At the same time, taking into account the formula threshold for decision-making, after a limited round of discussions, decision-making experts, site selection criteria, and site alternatives can be changed arbitrarily so that when the final opinion is reached, the consensus of experts reaches this threshold. Finally, through the numerical calculation of the site selection center, it is found that the experts will reach a higher level of consensus when joining the experts who change their status. The validity of the method is verified, and the feasibility and applicability of the proposed method are shown.

]]>Symmetry doi: 10.3390/sym12091563

Authors: Yukun Dong Li Zhang Shanchen Pang Wenjing Yin Mengying Wu Meng Wu Haojie Li

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired.

]]>Symmetry doi: 10.3390/sym12091562

Authors: Jianzhang Wu Arun Kumar Sangaiah Wei Gao

The ontology sparse vector learning algorithm is essentially a dimensionality reduction trick, i.e., the key components in the p-dimensional vector are taken out, and the remaining components are set to zero, so as to obtain the key information in a certain ontology application background. In the early stage of ontology data processing, the goal of the algorithm is to find the location of key components through the learning of some ontology sample points, if the relevant concepts and structure information of each ontology vertex with p-dimensional vectors are expressed. The ontology sparse vector itself contains a certain structure, such as the symmetry between components and the binding relationship between certain components, and the algorithm can also be used to dig out the correlation and decisive components between the components. In this paper, the graph structure is used to express these components and their interrelationships, and the optimal solution is obtained by using spectral graph theory and graph optimization techniques. The essence of the proposed ontology learning algorithm is to find the decisive vertices in the graph G&beta;. Finally, two experiments show that the given ontology learning algorithm is effective in similarity calculation and ontology mapping in some specific engineering fields.

]]>Symmetry doi: 10.3390/sym12091561

Authors: Changli Li Shiqiang Tang Jingwen Yan Teng Zhou

Sometimes it is very difficult to obtain high-quality images because of the limitations of image-capturing devices and the environment. Gamma correction (GC) is widely used for image enhancement. However, traditional GC perhaps cannot preserve image details and may even reduce local contrast within high-illuminance regions. Therefore, we first define two couples of quasi-symmetric correction functions (QCFs) to solve these problems. Moreover, we propose a novel low-light image enhancement method based on proposed QCFs by fusion, which combines a globally-enhanced image by QCFs and a locally-enhanced image by contrast-limited adaptive histogram equalization (CLAHE). A large number of experimental results showed that our method could significantly enhance the detail and improve the contrast of low-light images. Our method also has a better performance than other state-of-the-art methods in both subjective and objective assessments.

]]>Symmetry doi: 10.3390/sym12091560

Authors: Elia Reyes M. Ángeles Castro Antonio Sirvent Francisco Rodríguez

In this work, we obtain exact solutions and continuous numerical approximations for mixed problems of coupled systems of diffusion equations with delay. Using the method of separation of variables, and based on an explicit expression for the solution of the separated vector initial-value delay problem, we obtain exact infinite series solutions that can be truncated to provide analytical&ndash;numerical solutions with prescribed accuracy in bounded domains. Although usually implicit in particular applications, the method of separation of variables is deeply correlated with symmetry ideas.

]]>Symmetry doi: 10.3390/sym12091559

Authors: Soumyodipta Karmakar Kairat Myrzakulov Surajit Chattopadhyay Ratbay Myrzakulov

The present study reports a reconstruction scheme for f(R) gravity with the scale factor a(t)&prop;(t*&minus;t)2c2 describing the pre-bounce ekpyrotic contraction, where t* is the big crunch time. The reconstructed f(R) is used to derive expressions for density and pressure contributions, and the equation of state parameter resulting from this reconstruction is found to behave like &ldquo;quintom&rdquo;. It has also been observed that the reconstructed f(R) has satisfied a sufficient condition for a realistic model. In the subsequent phase, the reconstructed f(R) is applied to the model of the chameleon scalar field, and the scalar field ϕ and the potential V(ϕ) are tested for quasi-exponential expansion. It has been observed that although the reconstructed f(R) satisfies one of the sufficient conditions for realistic model, the quasi-exponential expansion is not available due to this reconstruction. Finally, the consequences of pre-bounce ekpyrotic inflation in f(R) gravity are compared to the background solution for f(R) matter bounce.

]]>Symmetry doi: 10.3390/sym12091558

Authors: Khaled Bataineh

Singular knots and links have projections involving some usual crossings and some four-valent rigid vertices. Such vertices are symmetric in the sense that no strand overpasses the other. In this research we introduce stuck knots and links to represent physical knots and links with projections involving some stuck crossings, where the physical strands get stuck together showing which strand overpasses the other at a stuck crossing. We introduce the basic elements of the theory and we give some isotopy invariants of such knots including invariants which capture the chirality (mirror imaging) of such objects. We also introduce another natural class of stuck knots, which we call relatively stuck knots, where each stuck crossing has a stuckness factor that indicates to the value of stuckness at that crossing. Amazingly, a generalized version of Jones polynomial makes an invariant of such quantized knots and links. We give applications of stuck knots and links and their invariants in modeling and understanding bonded RNA foldings, and we explore the topology of such objects with invariants involving multiplicities at the bonds. Other perspectives are also discussed.

]]>Symmetry doi: 10.3390/sym12091557

Authors: Kalaivani Chandran Swathi Sundari Sundaramoorthy Florentin Smarandache Saeid Jafari

In this paper, we develop the notion of the basis for a smooth neutrosophic topology in a more natural way. As a sequel, we define the notion of symmetric neutrosophic quasi-coincident neighborhood systems and prove some interesting results that fit with the classical ones, to establish the consistency of theory developed. Finally, we define and discuss the concept of product topology, in this context, using the definition of basis.

]]>Symmetry doi: 10.3390/sym12091556

Authors: Myunghoon Jeon Namgi Kim Yehoon Jang Byoung-Dai Lee

With the recent advancements in cloud computing technology, the number of cloud-based services has been gradually increasing. Symmetrically, users are asking for quality of experience (QoE) to be maintained or improved. To do this, it has become necessary to manage network resources more efficiently inside the cloud. Many theoretical studies for improving the users&rsquo; QoE have been proposed. However, there are few practical solutions due to the lack of symmetry between implementation and theoretical researches. Hence, in this study, we propose a ranking table-based network resource allocation method that dynamically allocates network resources per service flow based on flow information periodically collected from a software defined network (SDN). It dynamically identifies the size of the data transmission for each service flow on the SDN and differentially allocates network resources to each service flow based on this size. As a result, it maintains the maximum QoE for the user by increasing the network utilization. The experimental results show that the proposed method achieves 29.4% higher network efficiency than the general Open Shortest Path First (OSPF) method on average.

]]>Symmetry doi: 10.3390/sym12091555

Authors: Ahmed Mohammed Alghamdi Fathy Elbouraey Eassa Maher Ali Khamakhem Abdullah Saad AL-Malaise AL-Ghamdi Ahmed S. Alfakeeh Abdullah S. Alshahrani Ala A. Alarood

The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware&rsquo;s ability as well as the parallelism in the application by integrating more than one programming model. One of the dual-programming model combinations is Message Passing Interface (MPI) + OpenACC, which has several features including increased system parallelism, support for different platforms with more performance, better productivity, and less programming effort. Several testing tools target parallel applications built by using programming models, but more effort is needed, especially for high-level Graphics Processing Unit (GPU)-related programming models. Owing to the integration of different programming models, errors will be more frequent and unpredictable. Testing techniques are required to detect these errors, especially runtime errors resulting from the integration of MPI and OpenACC; studying their behavior is also important, especially some OpenACC runtime errors that cannot be detected by any compiler. In this paper, we enhance the capabilities of ACC_TEST to test the programs built by using the dual-programming models MPI + OpenACC and detect their related errors. Our tool integrated both static and dynamic testing techniques to create ACC_TEST and allowed us to benefit from the advantages of both techniques reducing overheads, enhancing system execution time, and covering a wide range of errors. Finally, ACC_TEST is a parallel testing tool that creates testing threads based on the number of application threads for detecting runtime errors.

]]>Symmetry doi: 10.3390/sym12091554

Authors: Veronica Ilea Diana Otrocol

Following the idea of T. Wongyat and W. Sintunavarat, we obtain some existence and uniqueness results for the solution of an integral equation with supremum. The paper ends with the study of Gronwall-type theorems, comparison theorems and a result regarding a Ulam&ndash;Hyers stability result for the corresponding fixed point problem.

]]>Symmetry doi: 10.3390/sym12091553

Authors: Harun Yasar Zeynep Hilal Kilimci

Exchange rate forecasting has been an important topic for investors, researchers, and analysts. In this study, financial sentiment analysis (FSA) and time series analysis (TSA) are proposed to form a predicting model for US Dollar/Turkish Lira exchange rate. For this purpose, the proposed hybrid model is constructed in three stages: obtaining and modeling text data for FSA, obtaining and modeling numerical data for TSA, and blending two models like a symmetry. To our knowledge, this is the first study in the literature that uses social media platforms as a source for FSA and blends them with TSA methods. To perform FSA, word embedding methods Word2vec, GloVe, fastText, and deep learning models such as CNN, RNN, LSTM are used. To the best of our knowledge, this study is the first attempt in terms of performing the FSA by using the combinations of deep learning models with word embedding methods for both Turkish and English texts. For TSA, simple exponential smoothing, Holt&ndash;Winters, Holt&rsquo;s linear, and ARIMA models are employed. Finally, with the usage of the proposed model, any user who wants to make a US Dollar/Turkish Lira exchange rate forecast will be able to make a more consistent and strong exchange rate forecast.

]]>Symmetry doi: 10.3390/sym12091552

Authors: Chunhe Shi Chengdong Wu Yuan Gao

The traffic block port monitors and manages the road traffic by shooting and recording the motor vehicles. However, due to the complex factors such as shooting angle, light condition, environmental background, etc., the recognition rate of license plate is not high enough. High light and low light under complex lighting conditions are symmetry problems. This paper analyzes and solves the low light problem in detail, an image adaptive enhancement algorithm under low light conditions is proposed in the paper. The algorithm mainly includes four modules, among which, the fast image classification module uses the deep and separable convolutional neural network to classify low-light images into low-light images by day and low-light images by night, greatly reducing the computation burden on the basis of ensuring the classification accuracy. The image enhancement module inputs the classified images into two different image enhancement algorithms and adopts the idea of dividing and ruling; the image quality evaluation module adopts a weighted comprehensive evaluation index. The final experiment shows that the comprehensive evaluation indexes are all greater than 0.83, which can improve the subsequent recognition of vehicle face and license plate.

]]>Symmetry doi: 10.3390/sym12091551

Authors: Bartłomiej Kizielewicz Wojciech Sałabun

Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet identification of preferences makes it impossible to determine the preferences for new alternatives. In this work, we propose a new approach to identifying a multi-criteria decision model to address this challenge. Our proposal is based on stochastic optimization techniques and the characteristic objects method (COMET). An extensive work comparing the use of hill-climbing, simulated annealing, and particle swarm optimization algorithms are presented in this paper. The paper also contains preliminary studies on initial conditions. Finally, our approach has been demonstrated using a simple numerical example.

]]>Symmetry doi: 10.3390/sym12091550

Authors: Jan L. Cieśliński Dzianis Zhalukevich

Scators form a vector space endowed with a non-distributive product, in the hyperbolic case, have physical applications related to some deformations of special relativity (breaking the Lorentz symmetry) while the elliptic case leads to new examples of hypercomplex numbers and related notions of holomorphicity. Until now, only a few particular cases of scator holomorphic functions have been found. In this paper we obtain all solutions of the generalized Cauchy&ndash;Riemann system which describes analogues of holomorphic functions in the (1+2)-dimensional scator space.

]]>Symmetry doi: 10.3390/sym12091549

Authors: Wojciech Sałabun Jarosław Wątróbski Andrii Shekhovtsov

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors&rsquo; approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods.

]]>Symmetry doi: 10.3390/sym12091548

Authors: Abdul Razzaq Abdul Ghaffar Md. Gulzarul Hasan Zubair Ashraf Mohammad Faisal Khan

Fuzzy goal programming (FGP) is applied to solve fuzzy multi-objective optimization problems. In FGP, the weights are associated with fuzzy goals for the preference among them. However, the hierarchy within the fuzzy goals depends on several uncertain criteria, decided by experts, so the preference relations are not always easy to associate with weight. Therefore, the preference relations are provided by the decision-makers in terms of linguistic relationships, i.e., goal A is slightly or moderately or significantly more important than goal B. Due to the vagueness and ambiguity associated with the linguistic preference relations, intuitionistic fuzzy sets (IFSs) are most efficient and suitable to handle them. Thus, in this paper, a new fuzzy goal programming with intuitionistic fuzzy preference relations (FGP-IFPR) approach is proposed. In the proposed FGP-IFPR model, an achievement function has been developed via the convex combination of the sum of individual grades of fuzzy objectives and amount of the score function of IFPRs among the fuzzy goals. As an extension, we presented the linear and non-linear, namely, exponential and hyperbolic functions for the intuitionistic fuzzy preference relations (IFPRs). A study has been made to compare and analyze the three FGP-IFPR models with intuitionistic fuzzy linear, exponential, and hyperbolic membership and non-membership functions. For solving all three FGP-IFPR models, the solution approach is developed that established the corresponding crisp formulations, and the optimal solution are obtained. The validations of the proposed FGP-IFPR models have been presented with an experimental investigation of a numerical problem and a banking financial statement problem. A newly developed distance measure is applied to compare the efficiency of proposed models. The minimum value of the distance function represents a better and efficient model. Finally, it has been found that for the first illustrative problem considered, the exponential FGP-IFPR model performs best, whereas for the second problem, the hyperbolic FGP-IFPR model performs best and the linear FGP-IFPR model shows worst in both cases.

]]>Symmetry doi: 10.3390/sym12091547

Authors: Stephen C. Anco Bao Wang

A geometrical formulation for adjoint-symmetries as one-forms is studied for general partial differential equations (PDEs), which provides a dual counterpart of the geometrical meaning of symmetries as tangent vector fields on the solution space of a PDE. Two applications of this formulation are presented. Additionally, for systems of evolution equations, adjoint-symmetries are shown to have another geometrical formulation given by one-forms that are invariant under the flow generated by the system on the solution space. This result is generalized to systems of evolution equations with spatial constraints, where adjoint-symmetry one-forms are shown to be invariant up to a functional multiplier of a normal one-form associated with the constraint equations. All of the results are applicable to the PDE systems of interest in applied mathematics and mathematical physics.

]]>Symmetry doi: 10.3390/sym12091546

Authors: Antonino Amoddeo

A continuum model for tumor invasion in a two-dimensional spatial domain based on the interaction of the urokinase plasminogen activation system with a model for cancer cell dynamics is proposed. The arising system of partial differential equations is numerically solved using the finite element method. We simulated a portion of biological tissue imposing no flux boundary conditions. We monitored the cancer cell dynamics, as well the degradation of an extra cellular matrix representative, vitronectin, and the evolution of a specific degrading enzyme, plasmin, inside the biological tissue. The computations were parameterized as a function of the indirect cell proliferation induced by a plasminogen activator inhibitor binding to vitronectin and of the indirect plasmin deactivation due to the plasminogen activator inhibitor binding to the urokinase plasminogen activator. Their role during the cancer dynamical evolution was identified, together with a possible marker helping the mapping of the cancer invasive front. Our results indicate that indirect cancer cell proliferation biases the speed of the tumor invasive front as well as the heterogeneity of the cancer cell clustering and networking, as it ultimately acts on the proteolytic activity supporting cancer formation. Because of the initial conditions imposed, the numerical solutions of the model show a symmetrical dynamical evolution of heterogeneities inside the simulated domain. Moreover, an increase of up to about 12% in the invasion speed was observed, increasing the rate of indirect cancer cell proliferation, while increasing the plasmin deactivation rate inhibits heterogeneities and networking. As cancer cell proliferation causes vitronectin consumption and plasmin formation, the intensities of the concentration maps of both vitronectin and plasmin are superimposable to the cancer cell concentration maps. The qualitative imprinting that cancer cells leave on the extra cellular matrix during the time evolution as well their activity area is identified, framing the numerical results in the context of a methodology aimed at diagnostic and therapeutic improvement.

]]>Symmetry doi: 10.3390/sym12091545

Authors: Yunwen Tao Linyao Zhang Wenli Zou Elfi Kraka

Seventeen singlet excited states of ethylene have been calculated via time-dependent density functional theory (TDDFT) with the CAM-B3LYP functional and the geometries of 11 excited states were optimized successfully. The local vibrational mode theory was employed to examine the intrinsic C=C/C&ndash;H bond strengths and their change upon excitation. The natural transition orbital (NTO) analysis was used to further analyze the C=C/C&ndash;H bond strength change in excited states versus the ground state. For the first time, three excited states including &pi;y&prime; &rarr; 3s, &pi;y&prime; &rarr; 3py and &pi;y&prime; &rarr; 3pz were identified with stronger C=C ethylene double bonds than in the ground state.

]]>Symmetry doi: 10.3390/sym12091544

Authors: Sultan T. Alanazi Mohammed Anbar Shouki A. Ebad Shankar Karuppayah Hadeer A. Al-Ani

The adoption of health information systems provides many potential healthcare benefits. The government of the Kingdom of Saudi Arabia has subsidized this field. However, like those of other less developed countries, organizations in the Kingdom of Saudi Arabia struggle to secure their health information systems. This issue may stem from a lack of awareness regarding information security. To date, most related studies have not considered all of the factors affecting information security compliance behavior (ISCB), which include psychological traits, cultural and religious beliefs, and legal concerns. This paper aims to investigate the usefulness of a theory-based model and determine the predictors of ISCB among healthcare workers at government hospitals in the Kingdom of Saudi Arabia. The study investigated 433 health workers in Arar, the capital of the Northern Borders Province in the Kingdom of Saudi Arabia. Two phases involved in this study were the hypothetical model formulation and identification of ISCB predictors. The results suggest that moderating and non-common factors (e.g., religion and morality) impact ISCB, while demographic characteristics (e.g., age, marital status, and work experience) do not. All published instruments and theories were embedded to determine the most acceptable theories for Saudi culture. The theory-based model of ISCB establishes the main domains of theory for this study, which were religion/morality, self-efficacy, legal/punishment, personality traits, cost of compliance/noncompliance, subjective norms, information security policy, general information security, and technology awareness. Predictors of ISCB indicate that general information security, followed by self-efficacy and religion/morality, is the most influential factor on ISCB among healthcare workers in the Kingdom of Saudi Arabia. This study is considered as the first to present the symmetry between theory and actual descriptive results, which were not investigated before.

]]>Symmetry doi: 10.3390/sym12091543

Authors: Lorenzo Gavassino Marco Antonelli Brynmor Haskell

The formulation of a universal theory for bulk viscosity and heat conduction represents a theoretical challenge for our understanding of relativistic fluid dynamics. Recently, it was shown that the multifluid variational approach championed by Carter and collaborators has the potential to be a general and natural framework to derive (hyperbolic) hydrodynamic equations for relativistic dissipative systems. Furthermore, it also allows keeping direct contact with non-equilibrium thermodynamics, providing a clear microscopic interpretation of the elements of the theory. To provide an example of its universal applicability, in this paper we derive the fundamental equations of the radiation hydrodynamics directly in the context of Carter&rsquo;s multifluid theory. This operation unveils a novel set of thermodynamic constraints that must be respected by any microscopic model. Then, we prove that the radiation hydrodynamics becomes a multifluid model for bulk viscosity or heat conduction in some appropriate physical limits.

]]>Symmetry doi: 10.3390/sym12091542

Authors: Susmit Bagchi

Generally, the linear topological spaces successfully generate Tychonoff product topology in lower dimensions. This paper proposes the construction and analysis of a multidimensional topological space based on the Cartesian product of complex and real spaces in continua. The geometry of the resulting space includes a real plane with planar rotational symmetry. The basis of topological space contains cylindrical open sets. The projection of a cylindrically symmetric continuous function in the topological space onto a complex planar subspace maintains surjectivity. The proposed construction shows that there are two projective topological subspaces admitting non-uniform scaling, where the complex subspace scales at a higher order than the real subspace generating a quasinormed space. Furthermore, the space can be equipped with commutative and finite translations on complex and real subspaces. The complex subspace containing the origin of real subspace supports associativity under finite translation and multiplication operations in a combination. The analysis of the formation of a multidimensional topological group in the space requires first-order translation in complex subspace, where the identity element is located on real plane in the space. Moreover, the complex translation of identity element is restricted within the corresponding real plane. The topological projections support additive group structures in real one-dimensional as well as two-dimensional complex subspaces. Furthermore, a multiplicative group is formed in the real projective space. The topological properties, such as the compactness and homeomorphism of subspaces under various combinations of projections and translations, are analyzed. It is considered that the complex subspace is holomorphic in nature.

]]>Symmetry doi: 10.3390/sym12091541

Authors: Andrii Shekhovtsov Joanna Kołodziejczyk Wojciech Sałabun

A significant challenge in the current trend in decision-making methods is the problem&rsquo;s class in which the decision-maker makes decisions based on partially incomplete data. Classic methods of multicriteria decision analysis are used to analyze alternatives described by using numerical values. At the same time, fuzzy set modifications are usually used to include uncertain data in the decision-making process. However, data incompleteness is something else. In this paper, we show two approaches to identify fuzzy models with partially incomplete data. The monolithic approach assumes creating one model that requires many queries to the expert. In the structured approach, the problem is decomposed into several interrelated models. The main aim of the work is to compare their accuracy empirically and to determine the sensitivity of the obtained model to the used criteria. For this purpose, a study case will be presented. In order to compare the proposed approaches and analyze the significance of the decision criteria, we use two ranking similarity coefficients, i.e., symmetric rw and asymmetric WS. In this work, the limitations of each approach are presented, and the results show great similarity despite the use of two structurally different approaches. Finally, we show an example of calculations performed for alternatives with partially incomplete data.

]]>Symmetry doi: 10.3390/sym12091540

Authors: Urszula Bednarz Małgorzata Wołowiec-Musiał

In this paper, we introduce a new kind of generalized Fibonacci polynomials in the distance sense. We give a direct formula, a generating function and matrix generators for these polynomials. Moreover, we present a graph interpretation of these polynomials, their connections with Pascal&rsquo;s triangle and we prove some identities for them.

]]>Symmetry doi: 10.3390/sym12091539

Authors: Aleksandr I. Kozhanov

We study the solvability of nonlinear inverse problems of determining the low order coefficients in the second order hyperbolic equation. The overdetermination condition is specified as an integral condition with final data. Existence and uniqueness theorems for regular solutions are proved (i.e., for solutions having all weak derivatives in the sense of Sobolev, occuring in the equation).

]]>Symmetry doi: 10.3390/sym12091538

Authors: Fusun Yalcin

Multivariate statistical methods are widely used in several disciplines of fundamental sciences. In the present study, the data analysis of the chemical analysis of the sands of Moonlight Beach in the Kemer region was examined using multivariate statistical methods. This study consists of three parts. The multivariate statistical analysis tests were described in the first part, then the pollution indexes were studied in the second part. Finally, the distribution maps of the chemical analyses and pollution indexes were generated using the obtained data. The heavy metals were mostly observed in location K1, while they were sorted as follows based on their concentrations: Mg &gt; Fe &gt; Al &gt; Ti &gt; Sr &gt; Mn &gt; Cr &gt; Ni &gt; Zn &gt; Zr &gt; Cu &gt; Rb. Also, strong positive correlations were found between Si, Fe, Al, K, Ti, P. According to the results of factor analysis, it was found that four factors explained 83.5% of the total variance. On the other hand, the coefficient of determination (R2) was calculated as 63.6% in the regression model. Each unit increase in the value of Ti leads to an increase of 0.022 units in the value of Si. Potential Ecological Risk Index analysis results (RI &lt; 150) revealed that the study area had no risk. However, the locations around Moonlight Beach are under risk in terms of Enrichment Factor and Contamination Factor values. The index values of heavy metals in the anomaly maps and their densities were found to be successful; and higher densities were observed based on heavy metal anomalies.

]]>Symmetry doi: 10.3390/sym12091537

Authors: Lingling Han Xiuyun Guo

In this paper, we mainly count the number of subgroup chains of a finite nilpotent group. We derive a recursive formula that reduces the counting problem to that of finite p-groups. As applications of our main result, the classification problem of distinct fuzzy subgroups of finite abelian groups is reduced to that of finite abelian p-groups. In particular, an explicit recursive formula for the number of distinct fuzzy subgroups of a finite abelian group whose Sylow subgroups are cyclic groups or elementary abelian groups is given.

]]>Symmetry doi: 10.3390/sym12091536

Authors: Ashraf Alhujailli Waldemar Karwowski Thomas T.H. Wan Peter Hancock

The primary objective of this study was to investigate the effects of cyberbullying through social exclusion and verbal harassment on emotional, stress, and coping responses. Twenty-nine undergraduate students (16 females aged 18.25 &plusmn; 0.58 years and 13 males aged 18.46 &plusmn; 1.13 years) volunteered for the study. All volunteers participated in two experiments that stimulated cyberbullying through social exclusion or verbal harassment. In the first experiment, the effects of cyberbullying through social exclusion were investigated using a virtual ball-tossing game known as Cyberball. In the second experiment, the influence of cyberbullying through verbal harassment was tested using a hypothetical scenario together with reading of online comments. Emotional, stress, and coping responses were measured via the Positive Affect and Negative Affect Scale, the Dundee Stress State Questionnaire, and the Coping Inventory for Task Stress, respectively. The results demonstrated that social exclusion and verbal harassment induced a negative emotional state. We also found that verbal harassment through the use of impolite language increased engagement, and increased worry compared with social exclusion effects.

]]>Symmetry doi: 10.3390/sym12091535

Authors: Jaroslav Frnda Jan Nedoma Radek Martinek Michael Fridrich

Quality of service (QoS) and quality of experience (QoE) are two major concepts for the quality evaluation of video services. QoS analyzes the technical performance of a network transmission chain (e.g., utilization or packet loss rate). On the other hand, subjective evaluation (QoE) relies on the observer&rsquo;s opinion, so it cannot provide output in a form of score immediately (extensive time requirements). Although several well-known methods for objective evaluation exist (trying to adopt psychological principles of the human visual system via mathematical models), each of them has its own rating scale without an existing symmetric conversion to a standardized subjective output like MOS (mean opinion score), typically represented by a five-point rating scale. This makes it difficult for network operators to recognize when they have to apply resource reservation control mechanisms. For this reason, we propose an application (classifier) that derivates the subjective end-user quality perception based on a score of objective assessment and selected parameters of each video sequence. Our model integrates the unique benefits of unsupervised learning and clustering techniques such as overfitting avoidance or small dataset requirements. In fact, most of the published papers are based on regression models or supervised clustering. In this article, we also investigate the possibility of a graphical SOM (self-organizing map) representation called a U-matrix as a feature selection method.

]]>Symmetry doi: 10.3390/sym12091534

Authors: Yehonatan Knoll

Cold dark-matter, as a solution to the so-called dark-matter problem, suffers from a major internal conflict: In order to dodge direct detection for so long, it must have an unobservably small (non gravitational) interaction with mundane matter, and yet it manages to &lsquo;conspire&rsquo; with it such that, in single galaxies, its distribution can be inferred from that of mundane matter via the MOND phenomenology. This conflict is avoided if the missing, transparent component of the energy-momentum tensor is due to variations in some electromagnetic &lsquo;zero point field&rsquo; (ZPF) which is sourced by mundane matter and contains both its advanced and retarded fields. The existence of a ZPF thus modulated by mundane matter, follows from a proper solution to the self-force problem of classical electrodynamics (CED), recently proposed by the author, which renders CED compatible with the statistical predictions of QM. The possibility that &lsquo;dark matter&rsquo; is yet another, hitherto ignored facet of good-old classical electrodynamics, therefore seems no less plausible than it being a highly exotic and conspirative new form of matter. Tests for deciding between the two are proposed.

]]>Symmetry doi: 10.3390/sym12091533

Authors: Jussi Lindgren Jukka Liukkonen

We provide a natural derivation and interpretation for the uncertainty principle in quantum mechanics from the stochastic optimal control approach. We show that, in particular, the stochastic approach to quantum mechanics allows one to understand the uncertainty principle through the &ldquo;thermodynamic equilibrium&rdquo;. A stochastic process with a gradient structure is key in terms of understanding the uncertainty principle and such a framework comes naturally from the stochastic optimal control approach to quantum mechanics. The symmetry of the system is manifested in certain non-vanishing and invariant covariances between the four-position and the four-momentum. In terms of interpretation, the results allow one to understand the uncertainty principle through the lens of scientific realism, in accordance with empirical evidence, contesting the original interpretation given by Heisenberg.

]]>Symmetry doi: 10.3390/sym12091532

Authors: Abdulhakim A. Albabtain Mansour Shrahili Lolwa Alshagrawi Mohamed Kayid

A novel methodology for modelling time to failure of systems under a degradation process is proposed. Considering the method degradation may have influenced the failure of the system under the setup of the model several implied lifetime distributions are outlined. Hazard rate and mean residual lifetime of the model are obtained and a numerical situation is delineated to calculate their amounts. The problem of modelling the amount of degradation at the failure time is also considered. Two monotonic aging properties of the model is secured and a characterization property of the symmetric degradation models is established.

]]>Symmetry doi: 10.3390/sym12091530

Authors: Mohd Asyraf Zulkifley Siti Raihanah Abdani Nuraisyah Hani Zulkifley

COVID-19 is a disease that can be spread easily with minimal physical contact. Currently, the World Health Organization (WHO) has endorsed the reverse transcription-polymerase chain reaction swab test as a diagnostic tool to confirm COVID-19 cases. This test requires at least a day for the results to come out depending on the available facilities. Many countries have adopted a targeted approach in screening potential patients due to the cost. However, there is a need for a fast and accurate screening test to complement this targeted approach, so that the potential virus carriers can be quarantined as early as possible. The X-ray is a good screening modality; it is quick at capturing, cheap, and widely available, even in third world countries. Therefore, a deep learning approach has been proposed to automate the screening process by introducing LightCovidNet, a lightweight deep learning model that is suitable for the mobile platform. It is important to have a lightweight model so that it can be used all over the world even on a standard mobile phone. The model has been trained with additional synthetic data that were generated from the conditional deep convolutional generative adversarial network. LightCovidNet consists of three components, which are entry, middle, and exit flows. The middle flow comprises five units of feed-forward convolutional neural networks that are built using separable convolution operators. The exit flow is designed to improve the multi-scale capability of the network through a simplified spatial pyramid pooling module. It is a symmetrical architecture with three parallel pooling branches that enable the network to learn multi-scale features, which is suitable for cases wherein the X-ray images were captured from all over the world independently. Besides, the usage of separable convolution has managed to reduce the memory usage without affecting the classification accuracy. The proposed method managed to get the best mean accuracy of 0.9697 with a low memory requirement of just 841,771 parameters. Moreover, the symmetrical spatial pyramid pooling module is the most crucial component; the absence of this module will reduce the screening accuracy to just 0.9237. Hence, the developed model is suitable to be implemented for mass COVID-19 screening.

]]>Symmetry doi: 10.3390/sym12091531

Authors: Junqiang Li Jingyi Yi Yingmei Zhao

Relationship between innovation subsidies and corporate strategic choices has been extensively studied. Public innovation subsidies are by no means a certain value, existing in the form of an effective range instead. This means that the public innovation subsidies existing within the reasonable range can achieve the same incentive effect. So, what is the reasonable range or the effective boundaries of public innovation subsidies to promote enterprises that adopt cooperation strategies? There is no definite answer. Based on classical game theory, a stochastic evolutionary game model is proposed in this paper, which takes into account the influence of random disturbance on the strategy evolution process. An effective boundary of public innovation subsidy is provided as the main contribution based on a mature game scenario. A set of experimental data is subsequently selected as the sample for numerical simulation and result verification. The results showed that the probability of noncooperation within the effective value range will successfully converge to zero, which also means that the agents will adopt a collaborative cooperation strategy. The regulation effect of the combination of multiple variables is also discussed.

]]>Symmetry doi: 10.3390/sym12091529

Authors: Tsai Lin Wen

Several structural design problems that involve continuous and discrete variables are very challenging because of the combinatorial and non-convex characteristics of the problems. Although the deterministic optimization approach theoretically guarantees to find the global optimum, it usually leads to a significant burden in computational time. This article studies the deterministic approach for globally solving mixed&ndash;discrete structural optimization problems. An improved method that symmetrically reduces the number of constraints for linearly expressing signomial terms with pure discrete variables is applied to significantly enhance the computational efficiency of obtaining the exact global optimum of the mixed&ndash;discrete structural design problem. Numerical experiments of solving the stepped cantilever beam design problem and the pressure vessel design problem are conducted to show the efficiency and effectiveness of the presented approach. Compared with existing methods, this study introduces fewer convex terms and constraints for transforming the mixed&ndash;discrete structural problem and uses much less computational time for solving the reformulated problem to global optimality.

]]>Symmetry doi: 10.3390/sym12091528

Authors: Zhende Zhu Xiangcheng Que Zihao Niu Wenbin Lu

Because of its special structure, the anisotropic properties of columnar jointed rock mass (CJRM) are complicated, which brings difficulty to engineering construction. To comprehensively study the anisotropic characteristics of CJRM, uniaxial compression tests were conducted on artificial CJRM specimens. Quadrangular, pentagonal and hexagonal prism CJRM models were introduced, and the dip direction of the columnar joints was considered. Based on the test results and the structural features of the three CJRM models, the deformation and strength characteristics of CJRM specimens were analyzed and compared. The failure modes and mechanisms of artificial specimens with different dip directions were summarized in accordance with the failure processes and final appearances. Subsequently, the anisotropic degrees of the three CJRM models in the horizontal plane were classified, and their anisotropic characteristics were described. Finally, a simple empirical expression was adopted to estimate the strength and deformation of the CJRM, and the derived equations were used in the Baihetan Hydropower Station project. The calculated values are in good agreement with the existing research results, which reflects the engineering application value of the derived empirical equations.

]]>Symmetry doi: 10.3390/sym12091527

Authors: Sayantan Choudhury

The out-of-time-ordered correlation (OTOC) function is an important new probe in quantum field theory which is treated as a significant measure of random quantum correlations. In this paper, using for the first time the slogan &ldquo;Cosmology meets Condensed Matter Physics&rdquo;, we demonstrate a formalism to compute the Cosmological OTOC during the stochastic particle production during inflation and reheating following the canonical quantization technique. In this computation, two dynamical time scales are involved&mdash;out of them, at one time scale, the cosmological perturbation variable, and for the other, the canonically conjugate momentum, is defined, which is the strict requirement to define the time scale-separated quantum operators for OTOC and is perfectly consistent with the general definition of OTOC. Most importantly, using the present formalism, not only one can study the quantum correlation during stochastic inflation and reheating, but can also study quantum correlation for any random events in Cosmology. Next, using the late time exponential decay of cosmological OTOC with respect to the dynamical time scale of our universe which is associated with the canonically conjugate momentum operator in this formalism, we study the phenomenon of quantum chaos by computing the expression for the Lyapunov spectrum. Furthermore, using the well known Maldacena Shenker Stanford (MSS) bound on the Lyapunov exponent, &lambda;&le;2&pi;/&beta;, we propose a lower bound on the equilibrium temperature, T=1/&beta;, at the very late time scale of the universe. On the other hand, with respect to the other time scale with which the perturbation variable is associated, we find decreasing, but not exponentially decaying, behaviour, which quantifies the random quantum correlation function out-of-equilibrium. We have also studied the classical limit of the OTOC and checked the consistency with the large time limiting behaviour of the correlation. Finally, we prove that the normalized version of OTOC is completely independent of the choice of the preferred definition of the cosmological perturbation variable.

]]>Symmetry doi: 10.3390/sym12091526

Authors: Md Manjurul Ahsan Tasfiq E. Alam Theodore Trafalis Pedro Huebner

The limitations and high false-negative rates (30%) of COVID-19 test kits have been a prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and performing the tests require extensive resources and time. Recent studies show that radiological images like chest X-rays can offer a more efficient solution and faster initial screening of COVID-19 patients. In this study, we develop a COVID-19 diagnosis model using Multilayer Perceptron and Convolutional Neural Network (MLP-CNN) for mixed-data (numerical/categorical and image data). The model predicts and differentiates between COVID-19 and non-COVID-19 patients, such that early diagnosis of the virus can be initiated, leading to timely isolation and treatments to stop further spread of the disease. We also explore the benefits of using numerical/categorical data in association with chest X-ray images for screening COVID-19 patients considering both balanced and imbalanced datasets. Three different optimization algorithms are used and tested:adaptive learning rate optimization algorithm (Adam), stochastic gradient descent (Sgd), and root mean square propagation (Rmsprop). Preliminary computational results show that, on a balanced dataset, a model trained with Adam can distinguish between COVID-19 and non-COVID-19 patients with a higher accuracy of 96.3%. On the imbalanced dataset, the model trained with Rmsprop outperformed all other models by achieving an accuracy of 95.38%. Additionally, our proposed model outperformed selected existing deep learning models (considering only chest X-ray or CT scan images) by producing an overall average accuracy of 94.6% ± 3.42%.

]]>Symmetry doi: 10.3390/sym12091525

Authors: Nikita E. Barabanov Abraham A. Ungar

We derive a large set of binary operations that are algebraically isomorphic to the binary operation of the Beltrami&ndash;Klein ball model of hyperbolic geometry, known as the Einstein addition. We prove that each of these operations gives rise to a gyrocommutative gyrogroup isomorphic to Einstein gyrogroup, and satisfies a number of nice properties of the Einstein addition. We also prove that a set of cogyrolines for the Einstein addition is the same as a set of gyrolines of another binary operation. This operation is found directly and it turns out to be commutative. The same results are obtained for the binary operation of the Beltrami&ndash;Poincare disk model, known as M&ouml;bius addition. We find a canonical representation of metric tensors of binary operations isomorphic to the Einstein addition, and a canonical representation of metric tensors defined by cogyrolines of these operations. Finally, we derive a formula for the Gaussian curvature of spaces with canonical metric tensors. We obtain necessary and sufficient conditions for the Gaussian curvature to be equal to zero.

]]>Symmetry doi: 10.3390/sym12091524

Authors: Zhenliang Zhou Zhongsheng Tan Qiang Liu Jinpeng Zhao Zikai Dong

The water around thenear-sea tunnels is supplied infinitely, and mechanical characteristics of the lining and movement joint are inevitably affected by waterproof methods. The research on the mechanical characteristics of the waterproof system is immature. As a case study of the Gongbei tunnel, a scale model was established in this study, and the stratum, pipe curtain, grouting circle, lining, waterproof board, and movement joint were simulated based on the similarity theories. By changing the externally applied water pressure and drainage discharge, the variation and distribution of the water pressure and strain on the lining with the fully wrapped waterproof (FWW) method, the lining with the partially wrapped waterproof (PWW) method, and the movement joint were investigated. Furthermore, several suggestions on the selection of the waterproof method were presented. The results indicate that the PWW method can reduce the water pressure and strain on the lining under the drained state. Under the state of free drainage, the strain on the lining with the PWW method may get a discount of about 30%. More attention could be paid to the waterproof of the movement joints in the construction process, especially the invert. The research results may offer some valuable insights into the waterproof design of similar near-sea tunnels.

]]>Symmetry doi: 10.3390/sym12091523

Authors: Vladimir I. Semenov

Up to now, it is unknown an existence of blow up solutions in the Cauchy problem for Navier&ndash;Stokes equations in space. The first important property of hypothetical blow up solutions was found by J. Leray in 1934. It is connected with norms in Lp(R3),p&gt;3. However, there are important solutions in L2(R3) because the second power of this norm can be interpreted as a kinetic energy of the fluid flow. It gives a new possibility to study an influence of kinetic energy changing on solution properties. There are offered new tools in this way. In particular, inequalities with an invariant form are considered as elements of latent symmetry.

]]>Symmetry doi: 10.3390/sym12091522

Authors: Darjan Smajla Olivera M. Knezevic Dragan M. Mirkov Nejc Šarabon

Rate of force/torque development scaling factor (RFD-SF/RTD-SF) was recently introduced as a tool to quantify the neuromuscular quickness, and it could have potential for interlimb asymmetry identification. Moreover, positive relationships in RFD-SF ability among different muscle groups were shown, but not in the lower extremity. The first aim of our study was to use RTD-SF for interlimb asymmetry identification. The second aim was to determine associations between plantar flexors (PF) and knee extensors (KE). Forty young healthy athletes (14.8 &plusmn; 1.2 years) performed explosive isometric contractions to a span of torque levels for PF and KE. From rapid isometric contractions, the RTD-SF and linearity (r2) of the regression line were calculated. Using RTD-SF we identified 10% (PF) and 15% (KE) of subjects with contralateral asymmetries (&gt;15% criterion). The results revealed significant positive moderate correlation in RTD-SF between PF and KE (r = 0.401, p &lt; 0.05). We supported that RTD-SF can be a useful tool for interlimb asymmetry identification. Future research about observed asymmetry in rapid submaximal contractions deserves more attention, as most of the functional sport specific activities put high demands on rapid force production. Our study as first confirmed positive associations in RTD-SF ability between muscle groups in lower limbs.

]]>Symmetry doi: 10.3390/sym12091521

Authors: Cheng-Chi Wang Chih-Jer Lin

Dual-directional coupled aerodynamic bearing (DCAB) systems have received considerable attention over the past few years. These systems are primarily used to solve air lubrication problems in high-precision mechanisms and equipment that run at a high rotational speed and require high rigidity and precision. DCABs have the advantages of axial and radial thrust and provide high rigidity, dual-directional support, and high load-carrying capacity. In DCAB systems, the nonlinearity of the air film pressure and dynamic problems, such as critical speed, unbalanced air supply, or poor design, can cause the instability of the rotor-bearing system and phenomena such as nonperiodic or chaotic motion under certain parameters or conditions. Therefore, to investigate what conditions lead to nonperiodic phenomena and to avoid irregular vibration, the properties and performance of the DCAB system were explored in detail by using three numerical methods for verifying the accuracy of the numerical results. The rotor behavior was also studied by analyzing the spectral response, the bifurcation phenomenon, Poincar&eacute; maps, and the maximum Lyapunov exponent. The numerical results indicate that chaos occurs in the DCAB system for specific ranges of the rotor mass and bearing number. For example, when the rotor mass (mr) is 5.7 kg, chaotic regions where the maximum Lyapunov exponents are greater than 0 occur at bearing number ranges of 3.96&ndash;3.98 and 4.63&ndash;5.02. The coupling effect of the rotor mass and bearing number was also determined. This effect can provide an important guideline for avoiding an unstable state.

]]>Symmetry doi: 10.3390/sym12091520

Authors: Omar Bazighifan Marianna Ruggieri Shyam Sundar Santra Andrea Scapellato

In this work, we consider a type of second-order functional differential equations and establish qualitative properties of their solutions. These new results complement and improve a number of results reported in the literature. Finally, we provide an example that illustrates our results.

]]>Symmetry doi: 10.3390/sym12091519

Authors: Fabio Scardigli

Mass thresholds, lifetimes, entropy and heat capacity for micro black holes close to their late Schwarzschild phase are computed using two different generalized uncertainty principles, in the framework of models with extra spatial dimensions. Emissions of both photons and gravitons (in the bulk) are taken into account. Results are discussed and compared.

]]>Symmetry doi: 10.3390/sym12091518

Authors: Mutti-Ur Rehman Jehad Alzabut Muhammad Fazeel Anwar

This article presents a stability analysis of linear time invariant systems arising in system theory. The computation of upper bounds of structured singular values confer the stability analysis, robustness and performance of feedback systems in system theory. The computation of the bounds of structured singular values of Toeplitz and symmetric Toeplitz matrices for linear time invariant systems is presented by means of low rank ordinary differential equations (ODE&rsquo;s) based methodology. The proposed methodology is based upon the inner-outer algorithm. The inner algorithm constructs and solves a gradient system of ODE&rsquo;s while the outer algorithm adjusts the perturbation level with fast Newton&rsquo;s iteration. The comparison of bounds of structured singular values approximated by low rank ODE&rsquo;s based methodology results tighter bounds when compared with well-known MATLAB routine mussv, available in MATLAB control toolbox.

]]>Symmetry doi: 10.3390/sym12091516

Authors: Patrik Milán Veres Krisztina Éva Gabányi Sándor Frey

We present high-resolution radio interferometric imaging observations of the radio source NVSS J182659+343113 (hereafter J1826+3431), the proposed radio counterpart of the &gamma;-ray source, 3EG J1824+3441 detected by the Energetic Gamma Ray Experiment Telescope (EGRET) on board the Compton Gamma Ray Observatory satellite. We analyzed eight epochs of archival multi-frequency very long baseline interferometry data. We imaged the asymmetric core&ndash;jet structure of the source, and detected apparent superluminal motion in the jet. At the highest observing frequency, 15.3 GHz, the core shows high brightness temperature indicating Doppler boosting. Additionally, the radio features undergo substantial flux density variability. These findings strengthen the previous claim of the association of the blazar J1826+3431 with the possible &gamma;-ray source, 3EG J1824+3441.

]]>Symmetry doi: 10.3390/sym12091517

Authors: Yiren Chen

Recently, periodic traveling waves, which include periodically symmetric traveling waves of nonlinear equations, have received great attention. This article uses some bifurcations of the traveling wave system to investigate the explicit periodic wave solutions with parameter &alpha; and their asymptotic property for the modified Fornberg&ndash;Whitham equation. Furthermore, when &alpha; tends to given parametric values, the elliptic periodic wave solutions become the other three types of nonlinear wave solutions, which include the trigonometric periodic blow-up solution, the hyperbolic smooth solitary wave solution, and the hyperbolic blow-up solution.

]]>Symmetry doi: 10.3390/sym12091515

Authors: Hyeongboo Baek Kilho Lee

Zero-laxity (ZL) and contention-free (CF) policies have received considerable attention owing to their simplicity and applicability to real-time systems equipped with symmetry multiprocessors. Recently, the ZL policy for mixed-criticality (MC) systems has been proposed and studied, but the applicability to and performance of the CF policy for MC systems have not been investigated yet. In this paper, we propose the CF policy (as a scheduling policy) for MC symmetry multiprocessor systems, referred to as the MC systems tailored CF policy (MC-CF), and a schedulability analysis in support thereof. We define the notion of contention-free slots for two different criticalities (of MC systems) of tasks, propose a technique to limit the amount to be utilized for each task by defining an upper bound, and subsequently explain the way in which the contention-free slots are systematically utilized to improve the schedulability of MC symmetry multiprocessor systems. Following this, we develop a deadline analysis (DA) for MC-CF. Using our experimental results under various environmental settings, we demonstrate that MC-CF can significantly improve the schedulability of fixed-priority scheduling.

]]>Symmetry doi: 10.3390/sym12091513

Authors: Liaquat Ali Lund Zurni Omar Sumera Dero Ilyas Khan Dumitru Baleanu Kottakkaran Sooppy Nisar

In this analysis, we aim to examine the heat transfer and flow characteristics of a copper-aluminum/water hybrid nanofluid in the presence of viscous dissipation, magnetohydrodynamic (MHD), and porous medium effect over the shrinking sheet. The governing equations of the fluid model have been acquired by employment of the model of Tiwari and Das, with additional properties of the hybrid nanofluid. The system of partial differential equations (PDEs) has been converted into ordinary differential equations (ODEs) by adopting the exponential similarity transformation. Similarity transformation is an essential class of phenomenon where the symmetry of the scale helps to reduce the number of independent variables. Note that ODE solutions demonstrate the PDEs symmetrical behavior for the velocity and temperature profiles. With BVP4C solver in the MATLAB program, the system of resulting equations has been solved. We have compared the present results with the published results and found in excellent agreements. The findings of the analysis are also displayed and discussed in depth graphically and numerically. It is discovered that two solutions occur in definite ranges of suction and magnetic parameters. Dual (no) similarity solutions can be found in the range of Sc&le;S&nbsp;and&nbsp;Mc&le;M (Sc&gt;S&nbsp;and&nbsp;Mc&gt;M). By performing stability analysis, the smallest values of eigenvalue are obtained, suggesting that a stable solution is the first one. Furthermore, the graph of the smallest eigenvalue shows symmetrical behavior. By enhancing the Eckert number values the temperature of the fluid is raised.

]]>Symmetry doi: 10.3390/sym12091514

Authors: Ji Hoon Ryoo Seohee Park Seongeun Kim Hyun Suk Ryoo

Fuzzy clustering has been broadly applied to classify data into K clusters by assigning membership probabilities of each data point close to K centroids. Such a function has been applied into characterizing the clusters associated with a statistical model such as structural equation modeling. The characteristics identified by the statistical model further define the clusters as heterogeneous groups selected from a population. Recently, such statistical model has been formulated as fuzzy clusterwise generalized structured component analysis (fuzzy clusterwise GSCA). The same as in fuzzy clustering, the clusters are enumerated to infer the population and its parameters within the fuzzy clusterwise GSCA. However, the identification of clusters in fuzzy clustering is a difficult task because of the data-dependence of classification indexes, which is known as a cluster validity problem. We examined the cluster validity problem within the fuzzy clusterwise GSCA framework and proposed a new criterion for selecting the most optimal number of clusters using both fit indexes of the GSCA and the fuzzy validity indexes in fuzzy clustering. The criterion, named the FIT-FHV method combining a fit index, FIT, from GSCA and a cluster validation measure, FHV, from fuzzy clustering, performed better than any other indices used in fuzzy clusterwise GSCA.

]]>Symmetry doi: 10.3390/sym12091512

Authors: Tetyana Nestorenko Mangirdas Morkunas Jana Peliova Artiom Volkov Tomas Balezentis Dalia Streimkiene

The present study deals with the modification of Wilson&rsquo;s formulation by taking into account changes in the supply chain represented by the parameters of the model, namely varying delivery costs and price of goods stored. The four different models are presented. The proposed models avoid the main drawbacks of Wilson&rsquo;s formulation&mdash;the constant price and reordering time&mdash;and discuss the case where varying parameters are used alongside discounting. The proposed models render lower costs under particular settings.

]]>Symmetry doi: 10.3390/sym12091510

Authors: Shiow-Luan Wang Erdenetuya Batbileg

International networking offers a teacher/learner an additional platform for promoting self-learning, as well as another way of generating social benefits by attracting more people for discussion and sharing. In this study, Taiwan is used as the instructional center to study international networking for innovative teaching efficiency, and Mongolia is the research object. A strategy inventory for language learning (SILL) questionnaire was used to estimate how often Mongolian students employ specific strategies for language learning. This assessment allows teachers to determine their students&rsquo; profiles and strategies, thereby enabling them to design suitable approaches for teaching English. The SILL answers were analyzed in SPSS, and a descriptive statistics procedure was applied. In the SILL results, standard deviations were calculated using the SPSS statistical package. The SPSS general linear model was used to conduct an analysis of variance with gender and strategic ability as the independent variables. The results provided the Cronbach&rsquo;s alpha, which indicates the correlation of a set of items that measure the same constructs, providing an average correlation of all items. The result of the Cronbach&rsquo;s alpha was 0.741, which was acceptable. The analysis also provided the Kaiser&ndash;Meyer&ndash;Olkin (KMO) measure of sampling adequacy, with a value of 0.667, which meant that the degree of common variance was minimal. Innovative teaching and learning via international networking in English were verified through a reliability analysis. This produced values of 5% for &alpha; and a 95% confidence index, with the learner&rsquo;s effectiveness greater than 81%. Among the six indicators&mdash;Memory, Cognitive, Compensation, Metacognitive, Affective, and Social. Memory and Cognitive levels were the highest, but remained behind the confidence level. The results showed that essential features can provide enhanced opportunities for teachers and students to teach and learn English. Therefore, this research suggests using IT in English classes motivates students to learn in class and to make the learning process more interesting and productive.

]]>Symmetry doi: 10.3390/sym12091511

Authors: Fenglei Wang Hao Zhou Shuohao Li Jun Lei Jun Zhang

Fine-grained image classification has seen a great improvement benefiting from the advantages of deep learning techniques. Most fine-grained image classification methods focus on extracting discriminative features and combining the global features with the local ones. However, the accuracy is limited due to the inter-class similarity and the inner-class divergence as well as the lack of enough labelled images to train a deep network which can generalize to fine-grained classes. To deal with these problems, we develop an algorithm which combines Maximizing the Mutual Information (MMI) with the Learning Attention (LA). We make use of MMI to distill knowledge from the image pairs which contain the same object. Meanwhile we take advantage of the LA mechanism to find the salient region of the image to enhance the information distillation. Our model can extract more discriminative semantic features and improve the performance on fine-grained image classification. Our model has a symmetric structure, in which the paired images are inputted into the same network to extract the local and global features for the subsequent MMI and LA modules. We train the model by maximizing the mutual information and minimizing the cross-entropy stage by stage alternatively. Experiments show that our model can improve the performance of the fine-grained image classification effectively.

]]>Symmetry doi: 10.3390/sym12091509

Authors: Kazuhiko Sawada

The asymmetry of the cerebral sulcal morphology is particularly obvious in higher primates. The sulcal asymmetry in macaque monkeys, a genus of the Old World monkeys, in our previous studies and others is summarized, and its evolutionary significance is speculated. Cynomolgus macaques displayed fetal sulcation and gyration symmetrically, and the sulcal asymmetry appeared after adolescence. Population-level rightward asymmetry was revealed in the length of arcuate sulcus (ars) and the surface area of superior temporal sulcus (sts) in adult macaques. When compared to other nonhuman primates, the superior postcentral sulcus (spcs) was left-lateralized in chimpanzees, opposite of the direction of asymmetry in the ars, anatomically-identical to the spcs, in macaques. This may be associated with handedness: either right-handedness in chimpanzees or left-handedness/ambidexterity in macaques. The rightward asymmetry in the sts surface area was seen in macaques, and it was similar to humans. However, no left/right side differences were identified in the sts morphology among great apes, which suggests the evolutionary discontinuity of the sts asymmetry. The diversity of the cortical lateralization among primate species suggests that the sulcal asymmetry reflects the species-related specialization of the cortical morphology and function, which is facilitated by evolutionary expansion in higher primates.

]]>Symmetry doi: 10.3390/sym12091508

Authors: Huidong Wang Yao Zhang Jinli Yao

In the multi-attribute decision making (MADM) process, the attribute values are sometimes provided by experts or the public in the form of words. To model the linguistic evaluation more accurately, this paper proposes the q-rung orthopair shadowed set (q-ROSS) to represent attribute values and extends the VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) method to solve MADM problems in the q-ROSS context. First, we propose the q-ROSS to express evaluation information. Some basic operation rules and distance measures are investigated accordingly. When the amount of data is large, the left and right endpoints of the collected interval numbers will obey symmetric normal distribution. Secondly, based on the normal distribution assumption, the collected data intervals are mapped to shadowed sets through a data processing approach. Furthermore, we extend the VIKOR model to tackle the MADM problem where the evaluation values are expressed by q-rung orthopair shadowed numbers. A location selection problem verifies the practicability of our method, and the effectiveness and superiority of the presented approach are reflected through comparative analysis.

]]>Symmetry doi: 10.3390/sym12091507

Authors: Xiuming Chen Qingying Qiu Chao Yang Peien Feng

Symmetry has been widely and deeply researched in basic science, and many mature results have been obtained so far. However, the widespread existence of symmetry in applied science is not in direct proportion to the attention it has received. Through a large number of examples studies, almost all mechanical structures are found to have symmetry, and most of them have the characteristics of point group symmetry. Therefore, the concept of point group symmetry in crystallography was extended to the field of machinery and adjusted according to the mechanical structures. First of all, the classification of mechanical point group symmetry is proposed, and how point group symmetry is applied in machinery is illustrated with examples. Then, the requirements of symmetry are analyzed and compared. Furthermore, the data mining software RapidMiner is used to mine the association rules between requirements and symmetry. Based on the mining results, the four selection principles of point group symmetry are summarized to provide ideas for structure design. Finally, a new type of gear pump with radial force balancing is invented by comprehensively using the mining results and selection principles.

]]>Symmetry doi: 10.3390/sym12091506

Authors: Anastasiia Kozachuk Dmitri Melikhov

We analyze constraints on the anomalous Wtb couplings from B-physics experiments, performing a correlated analysis and allowing all anomalous couplings to differ simultaneously from their Standard Model (SM) values. The B-physics observables allow one to probe three linear combinations out of the four anomalous couplings, which parameterize the Wtb vertex under the assumption that the SM symmetries remain the symmetries of the effective theory. The constraints in this work are obtained by taking into account the following B-physics observables: the B¯0−B0 oscillations, the leptonic B→μ+μ− decays, the inclusive radiative B→Xsγ decays, and the differential branching fractions in the semileptonic inclusive B→Xsμ+μ− and exclusive B→(K,K*)μ+μ− decays at small q2, with q the momentum of the μ+μ− pair. We find that the SM values of the anomalous couplings belong to the 95% CL allowed region obtained this way, but lie beyond the 68% allowed region. We also report that the distributions of the anomalous couplings obtained within our scenario differ from the results of the 1D scenario, when only one of the couplings is allowed to deviate from its SM value.

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