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Symmetry, Volume 10, Issue 4 (April 2018)

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Cover Story (view full-size image) We study the spin-orbital splitting of the angular momentum for nonparaxial electromagnetic fields. [...] Read more.
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Open AccessFeature PaperArticle Palmprint and Palmvein Recognition Based on DCNN and A New Large-Scale Contactless Palmvein Dataset
Symmetry 2018, 10(4), 78; doi:10.3390/sym10040078
Received: 7 March 2018 / Revised: 18 March 2018 / Accepted: 19 March 2018 / Published: 21 March 2018
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Abstract
Among the members of biometric identifiers, the palmprint and the palmvein have received significant attention due to their stability, uniqueness, and non-intrusiveness. In this paper, we investigate the problem of palmprint/palmvein recognition and propose a Deep Convolutional Neural Network (DCNN) based scheme, namely
[...] Read more.
Among the members of biometric identifiers, the palmprint and the palmvein have received significant attention due to their stability, uniqueness, and non-intrusiveness. In this paper, we investigate the problem of palmprint/palmvein recognition and propose a Deep Convolutional Neural Network (DCNN) based scheme, namely P a l m R CNN (short for palmprint/palmvein recognition using CNNs). The effectiveness and efficiency of P a l m R CNN have been verified through extensive experiments conducted on benchmark datasets. In addition, though substantial effort has been devoted to palmvein recognition, it is still quite difficult for the researchers to know the potential discriminating capability of the contactless palmvein. One of the root reasons is that a large-scale and publicly available dataset comprising high-quality, contactless palmvein images is still lacking. To this end, a user-friendly acquisition device for collecting high quality contactless palmvein images is at first designed and developed in this work. Then, a large-scale palmvein image dataset is established, comprising 12,000 images acquired from 600 different palms in two separate collection sessions. The collected dataset now is publicly available. Full article
(This article belongs to the Special Issue Deep Learning-Based Biometric Technologies)
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Open AccessArticle Oversampling Techniques for Bankruptcy Prediction: Novel Features from a Transaction Dataset
Symmetry 2018, 10(4), 79; doi:10.3390/sym10040079
Received: 27 February 2018 / Revised: 20 March 2018 / Accepted: 21 March 2018 / Published: 22 March 2018
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Abstract
In recent years, weakened by the fall of economic growth, many enterprises fell into the crisis caused by financial difficulties. Bankruptcy prediction, a machine learning model, is a great utility for financial institutions, fund managers, lenders, governments, and economic stakeholders. Due to the
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In recent years, weakened by the fall of economic growth, many enterprises fell into the crisis caused by financial difficulties. Bankruptcy prediction, a machine learning model, is a great utility for financial institutions, fund managers, lenders, governments, and economic stakeholders. Due to the number of bankrupt companies compared to that of non-bankrupt companies, bankruptcy prediction faces the problem of imbalanced data. This study first presents the bankruptcy prediction framework. Then, five oversampling techniques are used to deal with imbalance problems on the experimental dataset which were collected from Korean companies in two years from 2016 to 2017. Experimental results show that using oversampling techniques to balance the dataset in the training stage can enhance the performance of the bankruptcy prediction. The best overall Area Under the Curve (AUC) of this framework can reach 84.2%. Next, the study extracts more features by combining the financial dataset with transaction dataset to increase the performance for bankruptcy prediction and achieves 84.4% AUC. Full article
(This article belongs to the Special Issue Novel Machine Learning Approaches for Intelligent Big Data)
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Open AccessFeature PaperArticle Spontaneous Symmetry Breaking and Higgs Mode: Comparing Gross-Pitaevskii and Nonlinear Klein-Gordon Equations
Symmetry 2018, 10(4), 80; doi:10.3390/sym10040080
Received: 3 March 2018 / Revised: 18 March 2018 / Accepted: 19 March 2018 / Published: 23 March 2018
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Abstract
We discuss the mechanism of spontaneous symmetry breaking and the elementary excitations for a weakly-interacting Bose gas at a finite temperature. We consider both the non-relativistic case, described by the Gross-Pitaevskii equation, and the relativistic one, described by the cubic nonlinear Klein-Gordon equation.
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We discuss the mechanism of spontaneous symmetry breaking and the elementary excitations for a weakly-interacting Bose gas at a finite temperature. We consider both the non-relativistic case, described by the Gross-Pitaevskii equation, and the relativistic one, described by the cubic nonlinear Klein-Gordon equation. We analyze similarities and differences in the two equations and, in particular, in the phase and amplitude modes (i.e., Goldstone and Higgs modes) of the bosonic matter field. We show that the coupling between phase and amplitude modes gives rise to a single gapless Bogoliubov spectrum in the non-relativistic case. Instead, in the relativistic case the spectrum has two branches: one is gapless and the other is gapped. In the non-relativistic limit we find that the relativistic spectrum reduces to the Bogoliubov one. Finally, as an application of the above analysis, we consider the Bose-Hubbard model close to the superfluid-Mott quantum phase transition and we investigate the elementary excitations of its effective action, which contains both non-relativistic and relativistic terms. Full article
(This article belongs to the Special Issue Broken Symmetry)
Open AccessArticle Multicriteria Decision Making Based on Generalized Maclaurin Symmetric Means with Multi-Hesitant Fuzzy Linguistic Information
Symmetry 2018, 10(4), 81; doi:10.3390/sym10040081
Received: 26 February 2018 / Revised: 18 March 2018 / Accepted: 21 March 2018 / Published: 26 March 2018
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Abstract
In multicriteria decision making (MCDM), multi-hesitant fuzzy linguistic term sets (MHFLTSs) can eliminate the limitations of hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs), and emphasize the importance of a repeated linguistic term (LT). Meanwhile, there is usually an
[...] Read more.
In multicriteria decision making (MCDM), multi-hesitant fuzzy linguistic term sets (MHFLTSs) can eliminate the limitations of hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs), and emphasize the importance of a repeated linguistic term (LT). Meanwhile, there is usually an interrelation between criteria. The Maclaurin symmetric mean (MSM) operator can capture the interrelationships among multi-input arguments. The purpose of this paper is to integrate MHFLTSs with MSM operators and to solve MCDM problems. Firstly, we develop the generalized MSM operator for MHFLTSs (MHFLGMSM), the generalized geometric MSM operator for MHFLTSs (MHFLGGMSM), the weighted generalized MSM operator for MHFLTSs (WMHFLGMSM) and the weighted generalized geometric MSM operator for MHFLTSs (WMHFLGGMSM), respectively. Then, we discuss their properties and some special cases. Further, we present a novel method to deal with MCDM problems with the MHFLTSs based on the proposed MSM operators. Finally, an illustrative example about how to select the best third-party logistics service provider is supplied to demonstrate the practicality and reliability of the proposed approaches in comparison with some existing approaches. Full article
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Open AccessArticle The Landau-Lifshitz Equation, the NLS, and the Magnetic Rogue Wave as a By-Product of Two Colliding Regular “Positons”
Symmetry 2018, 10(4), 82; doi:10.3390/sym10040082
Received: 16 February 2018 / Revised: 18 March 2018 / Accepted: 19 March 2018 / Published: 27 March 2018
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Abstract
In this article we present a new method for construction of exact solutions of the Landau-Lifshitz-Gilbert equation (LLG) for ferromagnetic nanowires. The method is based on the established relationship between the LLG and the nonlinear Schrödinger equation (NLS), and is aimed at resolving
[...] Read more.
In this article we present a new method for construction of exact solutions of the Landau-Lifshitz-Gilbert equation (LLG) for ferromagnetic nanowires. The method is based on the established relationship between the LLG and the nonlinear Schrödinger equation (NLS), and is aimed at resolving an old problem: how to produce multiple-rogue wave solutions of NLS using just the Darboux-type transformations. The solutions of this type—known as P-breathers—have been proven to exist by Dubard and Matveev, but their technique heavily relied on using the solutions of yet another nonlinear equation, the Kadomtsev-Petviashvili I equation (KP-I), and its relationship with NLS. We have shown that in fact one doesn’t have to use KP-I but can instead reach the same results just with NLS solutions, but only if they are dressed via the binary Darboux transformation. In particular, our approach allows us to construct all the Dubard-Matveev P-breathers. Furthermore, the new method can lead to some completely new, previously unknown solutions. One particular solution that we have constructed describes two “positon”-like waves, colliding with each other and in the process producing a new, short-lived rogue wave. We called this unusual solution (in which a rogue wave is begotten after the impact of two solitons) the “impacton”. Full article
(This article belongs to the Special Issue Symmetry: Anniversary Feature Papers 2018)
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Open AccessArticle Multimedia System for Real-Time Photorealistic Nonground Modeling of 3D Dynamic Environment for Remote Control System
Symmetry 2018, 10(4), 83; doi:10.3390/sym10040083
Received: 31 January 2018 / Revised: 8 March 2018 / Accepted: 26 March 2018 / Published: 28 March 2018
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Abstract
Nowadays, unmanned ground vehicles (UGVs) are widely used for many applications. UGVs have sensors including multi-channel laser sensors, two-dimensional (2D) cameras, Global Positioning System receivers, and inertial measurement units (GPS–IMU). Multi-channel laser sensors and 2D cameras are installed to collect information regarding the
[...] Read more.
Nowadays, unmanned ground vehicles (UGVs) are widely used for many applications. UGVs have sensors including multi-channel laser sensors, two-dimensional (2D) cameras, Global Positioning System receivers, and inertial measurement units (GPS–IMU). Multi-channel laser sensors and 2D cameras are installed to collect information regarding the environment surrounding the vehicle. Moreover, the GPS–IMU system is used to determine the position, acceleration, and velocity of the vehicle. This paper proposes a fast and effective method for modeling nonground scenes using multiple types of sensor data captured through a remote-controlled robot. The multi-channel laser sensor returns a point cloud in each frame. We separated the point clouds into ground and nonground areas before modeling the three-dimensional (3D) scenes. The ground part was used to create a dynamic triangular mesh based on the height map and vehicle position. The modeling of nonground parts in dynamic environments including moving objects is more challenging than modeling of ground parts. In the first step, we applied our object segmentation algorithm to divide nonground points into separate objects. Next, an object tracking algorithm was implemented to detect dynamic objects. Subsequently, nonground objects other than large dynamic ones, such as cars, were separated into two groups: surface objects and non-surface objects. We employed colored particles to model the non-surface objects. To model the surface and large dynamic objects, we used two dynamic projection panels to generate 3D meshes. In addition, we applied two processes to optimize the modeling result. First, we removed any trace of the moving objects, and collected the points on the dynamic objects in previous frames. Next, these points were merged with the nonground points in the current frame. We also applied slide window and near point projection techniques to fill the holes in the meshes. Finally, we applied texture mapping using 2D images captured using three cameras installed in the front of the robot. The results of the experiments prove that our nonground modeling method can be used to model photorealistic and real-time 3D scenes around a remote-controlled robot. Full article
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Open AccessArticle Ephemeral-Secret-Leakage Secure ID-Based Three-Party Authenticated Key Agreement Protocol for Mobile Distributed Computing Environments
Symmetry 2018, 10(4), 84; doi:10.3390/sym10040084
Received: 25 January 2018 / Revised: 9 March 2018 / Accepted: 13 March 2018 / Published: 28 March 2018
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Abstract
A three-party Authenticated Key Agreement (AKA) protocol in the distributed computing environment is a client that requests services from an application server through an authentication server. The authentication server is responsible for authenticating the participating entities and helping them to construct a common
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A three-party Authenticated Key Agreement (AKA) protocol in the distributed computing environment is a client that requests services from an application server through an authentication server. The authentication server is responsible for authenticating the participating entities and helping them to construct a common session key. Adopting the Key Transfer Authentication Protocol (KTAP) in such an environment, the authentication server is able to monitor the communication messages to prevent and trace network crime. However, the session key in the KTAP setting is created only by the authentication server and is vulnerable to the resilience of key control. On the other hand, with the rapid growth of network technologies, mobile devices are widely used by people to access servers in the Internet. Many AKA protocols for mobile devices have been proposed, however, most protocols are vulnerable to Ephemeral Secret Leakage (ESL) attacks which compromise the private keys of clients and the session key by an adversary from eavesdropped messages. This paper proposes a novel ESL-secure ID-based three-party AKA protocol for mobile distributed computing environments based on ESL-secure ID-based Authenticated Key Exchange (ID-AKE) protocol. The proposed protocol solves the key control problem in KTAP while retaining the advantages of preventing and tracing network crime in KTAP and also resists ESL attacks. The AVISPA tool simulation results confirm the correctness of the protocol security analysis. Furthermore, we present a parallel version of the proposed ESL-secure ID-based three-party AKA protocol that is communication-efficient. Full article
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Open AccessArticle Generalized Interval Neutrosophic Choquet Aggregation Operators and Their Applications
Symmetry 2018, 10(4), 85; doi:10.3390/sym10040085
Received: 14 March 2018 / Revised: 26 March 2018 / Accepted: 26 March 2018 / Published: 28 March 2018
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Abstract
The interval neutrosophic set (INS) is a subclass of the neutrosophic set (NS) and a generalization of the interval-valued intuitionistic fuzzy set (IVIFS), which can be used in real engineering and scientific applications. This paper aims at developing new generalized Choquet aggregation operators
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The interval neutrosophic set (INS) is a subclass of the neutrosophic set (NS) and a generalization of the interval-valued intuitionistic fuzzy set (IVIFS), which can be used in real engineering and scientific applications. This paper aims at developing new generalized Choquet aggregation operators for INSs, including the generalized interval neutrosophic Choquet ordered averaging (G-INCOA) operator and generalized interval neutrosophic Choquet ordered geometric (G-INCOG) operator. The main advantages of the proposed operators can be described as follows: (i) during decision-making or analyzing process, the positive interaction, negative interaction or non-interaction among attributes can be considered by the G-INCOA and G-INCOG operators; (ii) each generalized Choquet aggregation operator presents a unique comprehensive framework for INSs, which comprises a bunch of existing interval neutrosophic aggregation operators; (iii) new multi-attribute decision making (MADM) approaches for INSs are established based on these operators, and decision makers may determine the value of λ by different MADM problems or their preferences, which makes the decision-making process more flexible; (iv) a new clustering algorithm for INSs are introduced based on the G-INCOA and G-INCOG operators, which proves that they have the potential to be applied to many new fields in the future. Full article
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Open AccessArticle A Symmetric Particle-Based Simulation Scheme towards Large Scale Diffuse Fluids
Symmetry 2018, 10(4), 86; doi:10.3390/sym10040086
Received: 28 February 2018 / Revised: 25 March 2018 / Accepted: 27 March 2018 / Published: 29 March 2018
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Abstract
We present a symmetric particle simulation scheme for diffuse fluids based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) model. In our method, the generation of diffuse particles is determined by the entropy of fluid particles, and it is calculated by the velocity difference
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We present a symmetric particle simulation scheme for diffuse fluids based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) model. In our method, the generation of diffuse particles is determined by the entropy of fluid particles, and it is calculated by the velocity difference and kinetic energy. Diffuse particles are generated near the qualified diffuse particle emitters whose diffuse material generation rate is greater than zero. Our method fits the laws of physics better, as it abandons the common practice of adding diffuse materials at the crest empirically. The coupling between diffuse materials and fluid is a post-processing step achieved by the velocity field, which enables the avoiding of the time-consuming process of cross finding neighbors. The influence weights of the fluid particles are assigned based on the degree of coupling. Therefore, it improved the accuracy of the diffuse particle position and made the simulation results more realistic. The approach is appropriate for large scale diffuse fluid, as it can be easily integrated in existing SPH simulation methods and the computational overhead is negligible. Full article
(This article belongs to the Special Issue Symmetry in Cooperative Applications III)
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Open AccessArticle Dense Fully Convolutional Segmentation of the Optic Disc and Cup in Colour Fundus for Glaucoma Diagnosis
Symmetry 2018, 10(4), 87; doi:10.3390/sym10040087
Received: 11 February 2018 / Revised: 8 March 2018 / Accepted: 28 March 2018 / Published: 30 March 2018
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Abstract
Glaucoma is a group of eye diseases which can cause vision loss by damaging the optic nerve. Early glaucoma detection is key to preventing vision loss yet there is a lack of noticeable early symptoms. Colour fundus photography allows the optic disc (OD)
[...] Read more.
Glaucoma is a group of eye diseases which can cause vision loss by damaging the optic nerve. Early glaucoma detection is key to preventing vision loss yet there is a lack of noticeable early symptoms. Colour fundus photography allows the optic disc (OD) to be examined to diagnose glaucoma. Typically, this is done by measuring the vertical cup-to-disc ratio (CDR); however, glaucoma is characterised by thinning of the rim asymmetrically in the inferior-superior-temporal-nasal regions in increasing order. Automatic delineation of the OD features has potential to improve glaucoma management by allowing for this asymmetry to be considered in the measurements. Here, we propose a new deep-learning-based method to segment the OD and optic cup (OC). The core of the proposed method is DenseNet with a fully-convolutional network, whose symmetric U-shaped architecture allows pixel-wise classification. The predicted OD and OC boundaries are then used to estimate the CDR on two axes for glaucoma diagnosis. We assess the proposed method’s performance using a large retinal colour fundus dataset, outperforming state-of-the-art segmentation methods. Furthermore, we generalise our method to segment four fundus datasets from different devices without further training, outperforming the state-of-the-art on two and achieving comparable results on the remaining two. Full article
(This article belongs to the Special Issue Advances in Medical Image Segmentation)
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Open AccessFeature PaperArticle Spin-Orbital Momentum Decomposition and Helicity Exchange in a Set of Non-Null Knotted Electromagnetic Fields
Symmetry 2018, 10(4), 88; doi:10.3390/sym10040088
Received: 9 March 2018 / Revised: 23 March 2018 / Accepted: 27 March 2018 / Published: 30 March 2018
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Abstract
We calculate analytically the spin-orbital decomposition of the angular momentum using completely nonparaxial fields that have a certain degree of linkage of electric and magnetic lines. The split of the angular momentum into spin-orbital components is worked out for non-null knotted electromagnetic fields.
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We calculate analytically the spin-orbital decomposition of the angular momentum using completely nonparaxial fields that have a certain degree of linkage of electric and magnetic lines. The split of the angular momentum into spin-orbital components is worked out for non-null knotted electromagnetic fields. The relation between magnetic and electric helicities and spin-orbital decomposition of the angular momentum is considered. We demonstrate that even if the total angular momentum and the values of the spin and orbital momentum are the same, the behavior of the local angular momentum density is rather different. By taking cases with constant and non-constant electric and magnetic helicities, we show that the total angular momentum density presents different characteristics during time evolution. Full article
(This article belongs to the Special Issue Symmetry in Electromagnetism)
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Open AccessArticle Automatic Generation of Dynamic Skin Deformation for Animated Characters
Symmetry 2018, 10(4), 89; doi:10.3390/sym10040089
Received: 15 December 2017 / Revised: 25 March 2018 / Accepted: 26 March 2018 / Published: 31 March 2018
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Abstract
Since non-automatic rigging requires heavy human involvements, and various automatic rigging algorithms are less efficient in terms of computational efficiency, especially for current curve-based skin deformation methods, identifying the iso-parametric curves and creating the animation skeleton requires tedious and time-consuming manual work. Although
[...] Read more.
Since non-automatic rigging requires heavy human involvements, and various automatic rigging algorithms are less efficient in terms of computational efficiency, especially for current curve-based skin deformation methods, identifying the iso-parametric curves and creating the animation skeleton requires tedious and time-consuming manual work. Although several automatic rigging methods have been developed, but they do not aim at curve-based models. To tackle this issue, this paper proposes a new rigging algorithm for automatic generation of dynamic skin deformation to quickly identify iso-parametric curves and create an animation skeleton in a few milliseconds, which can be seamlessly used in curve-based skin deformation methods to make the rigging process fast enough for highly efficient computer animation applications. Full article
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Open AccessArticle Anti-3D Weapon Model Detection for Safe 3D Printing Based on Convolutional Neural Networks and D2 Shape Distribution
Symmetry 2018, 10(4), 90; doi:10.3390/sym10040090
Received: 28 February 2018 / Revised: 21 March 2018 / Accepted: 29 March 2018 / Published: 31 March 2018
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Abstract
With the development of 3D printing, weapons are easily printed without any restriction from the production managers. Therefore, anti-3D weapon model detection is necessary issue in safe 3D printing to prevent the printing of 3D weapon models. In this paper, we would like
[...] Read more.
With the development of 3D printing, weapons are easily printed without any restriction from the production managers. Therefore, anti-3D weapon model detection is necessary issue in safe 3D printing to prevent the printing of 3D weapon models. In this paper, we would like to propose an anti-3D weapon model detection algorithm to prevent the printing of anti-3D weapon models for safe 3D printing based on the D2 shape distribution and an improved convolutional neural networks (CNNs). The purpose of the proposed algorithm is to detect anti-3D weapon models when they are used in 3D printing. The D2 shape distribution is computed from random points on the surface of a 3D weapon model and their geometric features in order to construct a D2 vector. The D2 vector is then trained by improved CNNs. The CNNs are used to detect anti-3D weapon models for safe 3D printing by training D2 vectors which have been constructed from the D2 shape distribution of 3D weapon models. Experiments with 3D weapon models proved that the D2 shape distribution of 3D weapon models in the same class is the same. Training and testing results also verified that the accuracy of the proposed algorithm is higher than the conventional works. The proposed algorithm is applied in a small application, and it could detect anti-3D weapon models for safe 3D printing. Full article
(This article belongs to the Special Issue Information Technology and Its Applications 2018)
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Open AccessArticle An Extended Step-Wise Weight Assessment Ratio Analysis with Symmetric Interval Type-2 Fuzzy Sets for Determining the Subjective Weights of Criteria in Multi-Criteria Decision-Making Problems
Symmetry 2018, 10(4), 91; doi:10.3390/sym10040091
Received: 19 March 2018 / Revised: 28 March 2018 / Accepted: 30 March 2018 / Published: 31 March 2018
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Abstract
Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights
[...] Read more.
Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers’ preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information. Full article
(This article belongs to the Special Issue Solution Models based on Symmetric and Asymmetric Information)
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Open AccessFeature PaperArticle Applying Genetic Programming with Similar Bug Fix Information to Automatic Fault Repair
Symmetry 2018, 10(4), 92; doi:10.3390/sym10040092
Received: 19 February 2018 / Revised: 25 March 2018 / Accepted: 28 March 2018 / Published: 2 April 2018
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Abstract
Owing to the high complexity of recent software products, developers cannot avoid major/minor mistakes, and software bugs are generated during the software development process. When developers manually modify a program source code using bug descriptions to fix bugs, their daily workloads and costs
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Owing to the high complexity of recent software products, developers cannot avoid major/minor mistakes, and software bugs are generated during the software development process. When developers manually modify a program source code using bug descriptions to fix bugs, their daily workloads and costs increase. Therefore, we need a way to reduce their workloads and costs. In this paper, we propose a novel automatic fault repair method by using similar bug fix information based on genetic programming (GP). First, we searched for similar buggy source codes related to the new given buggy code, and then we searched for a fixed the buggy code related to the most similar source code. Next, we transformed the fixed code into abstract syntax trees for applying GP and generated the candidate program patches. In this step, we verified the candidate patches by using a fitness function based on given test cases to determine whether the patch was valid or not. Finally, we produced program patches to fix the new given buggy code. Full article
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Open AccessArticle Big Data Analysis for Personalized Health Activities: Machine Learning Processing for Automatic Keyword Extraction Approach
Symmetry 2018, 10(4), 93; doi:10.3390/sym10040093
Received: 14 February 2018 / Revised: 29 March 2018 / Accepted: 30 March 2018 / Published: 2 April 2018
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Abstract
The obese population is increasing rapidly due to the change of lifestyle and diet habits. Obesity can cause various complications and is becoming a social disease. Nonetheless, many obese patients are unaware of the medical treatments that are right for them. Although a
[...] Read more.
The obese population is increasing rapidly due to the change of lifestyle and diet habits. Obesity can cause various complications and is becoming a social disease. Nonetheless, many obese patients are unaware of the medical treatments that are right for them. Although a variety of online and offline obesity management services have been introduced, they are still not enough to attract the attention of users and are not much of help to solve the problem. Obesity healthcare and personalized health activities are the important factors. Since obesity is related to lifestyle habits, eating habits, and interests, I concluded that the big data analysis of these factors could deduce the problem. Therefore, I collected big data by applying the machine learning and crawling method to the unstructured citizen health data in Korea and the search data of Naver, which is a Korean portal company, and Google for keyword analysis for personalized health activities. It visualized the big data using text mining and word cloud. This study collected and analyzed the data concerning the interests related to obesity, change of interest on obesity, and treatment articles. The analysis showed a wide range of seasonal factors according to spring, summer, fall, and winter. It also visualized and completed the process of extracting the keywords appropriate for treatment of abdominal obesity and lower body obesity. The keyword big data analysis technique for personalized health activities proposed in this paper is based on individual’s interests, level of interest, and body type. Also, the user interface (UI) that visualizes the big data compatible with Android and Apple iOS. The users can see the data on the app screen. Many graphs and pictures can be seen via menu, and the significant data values are visualized through machine learning. Therefore, I expect that the big data analysis using various keywords specific to a person will result in measures for personalized treatment and health activities. Full article
(This article belongs to the Special Issue Novel Machine Learning Approaches for Intelligent Big Data)
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Open AccessArticle Fluid-Solid Boundary Handling Using Pairwise Interaction Model for Non-Newtonian Fluid
Symmetry 2018, 10(4), 94; doi:10.3390/sym10040094
Received: 28 February 2018 / Revised: 29 March 2018 / Accepted: 31 March 2018 / Published: 3 April 2018
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Abstract
In order to simulate fluid-solid boundary interaction for non-Newtonian Smoothed Particle Hydrodynamics (SPH) fluids, we present a steady and realistic fluid-solid boundary handling method using symmetrical interaction forces. Firstly, we use the improved SPH method to model the non-Newtonian fluid. Secondly, the density
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In order to simulate fluid-solid boundary interaction for non-Newtonian Smoothed Particle Hydrodynamics (SPH) fluids, we present a steady and realistic fluid-solid boundary handling method using symmetrical interaction forces. Firstly, we use the improved SPH method to model the non-Newtonian fluid. Secondly, the density of boundary particle is created into the calculation of fluid-solid interaction forces. Besides, we apply friction conditions to constrain the fluid particles at the boundary. Finally, we apply the predictive-corrective scheme to correct the density deviation and improve boundary computing efficiency. The experiment confirms the feasibility for the interaction between non-Newtonian fluid and solid objects with this method. At the same time, it reflects the viscous characteristics and ensures the physical properties of non-Newtonian fluid. In addition, compared to existing methods, this method is more stable and easier to implement. Full article
(This article belongs to the Special Issue Symmetry in Cooperative Applications III)
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Open AccessArticle Cooperative Secret Sharing Using QR Codes and Symmetric Keys
Symmetry 2018, 10(4), 95; doi:10.3390/sym10040095
Received: 28 February 2018 / Revised: 30 March 2018 / Accepted: 3 April 2018 / Published: 4 April 2018
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Abstract
Secret sharing is an information security technique where a dealer divides a secret into a collection of shares and distributes these to members of a group. The secret will only be revealed when a predefined number of group members cooperate to recover the
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Secret sharing is an information security technique where a dealer divides a secret into a collection of shares and distributes these to members of a group. The secret will only be revealed when a predefined number of group members cooperate to recover the secret. The purpose of this study is to investigate a method of distributing shares by embedding them into cover Quick Response (QR) codes in a secure manner using cryptographic keys. The advantage of this approach is that the shares can be disseminated over public channels, as anyone who scans the QR codes will only obtain public information. Only authorized individuals who are in possession of the required keys will be able to recover the shares. This also means that when group members cooperate to recover a secret, the group can determine the presence of an illegitimate participant if the person does not produce a valid share. This study proposes a protocol for accomplishing this and discusses the underlying security of the protocol. Full article
(This article belongs to the Special Issue Symmetry in Cooperative Applications III)
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Open AccessArticle A Novel Multimodal Biometrics Recognition Model Based on Stacked ELM and CCA Methods
Symmetry 2018, 10(4), 96; doi:10.3390/sym10040096
Received: 11 February 2018 / Revised: 26 March 2018 / Accepted: 28 March 2018 / Published: 4 April 2018
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Abstract
Multimodal biometrics combine a variety of biological features to have a significant impact on identification performance, which is a newly developed trend in biometrics identification technology. This study proposes a novel multimodal biometrics recognition model based on the stacked extreme learning machines (ELMs)
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Multimodal biometrics combine a variety of biological features to have a significant impact on identification performance, which is a newly developed trend in biometrics identification technology. This study proposes a novel multimodal biometrics recognition model based on the stacked extreme learning machines (ELMs) and canonical correlation analysis (CCA) methods. The model, which has a symmetric structure, is found to have high potential for multimodal biometrics. The model works as follows. First, it learns the hidden-layer representation of biological images using extreme learning machines layer by layer. Second, the canonical correlation analysis method is applied to map the representation to a feature space, which is used to reconstruct the multimodal image feature representation. Third, the reconstructed features are used as the input of a classifier for supervised training and output. To verify the validity and efficiency of the method, we adopt it for new hybrid datasets obtained from typical face image datasets and finger-vein image datasets. Our experimental results demonstrate that our model performs better than traditional methods. Full article
(This article belongs to the Special Issue Deep Learning-Based Biometric Technologies)
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Open AccessArticle A Watermarking Method for 3D Printing Based on Menger Curvature and K-Mean Clustering
Symmetry 2018, 10(4), 97; doi:10.3390/sym10040097
Received: 14 March 2018 / Revised: 27 March 2018 / Accepted: 3 April 2018 / Published: 4 April 2018
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Abstract
Nowadays, 3D printing is widely used in many areas of life. This leads to 3D printing models often being used illegally without any payment to the original providers. Therefore, providers need a solution to identify and protect the copyright of 3D printing. This
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Nowadays, 3D printing is widely used in many areas of life. This leads to 3D printing models often being used illegally without any payment to the original providers. Therefore, providers need a solution to identify and protect the copyright of 3D printing. This paper presents a novel watermarking method for the copyright protection of 3D printing based on the Menger facet curvature and K-mean clustering. The facets of the 3D printing model are classified into groups based on the value of Menger curvature and the K-mean clustering, and the mean Menger curvature of each group will then be computed for embedding the watermark data. The watermark data are embedded into the groups of facets by changing the mean Menger curvature of each group according to the bit of watermark data. In each group, we select a facet that has the Menger curvature closest to the changed mean Menger curvature, and we then transform the vertices of the selected facet according to the changed Menger curvature for the watermarked 3D printing model generation. Watermark data are extracted from 3D-printed objects, which are printed from the watermarked 3D printing models by the 3D printer. Experimental results after embedding the watermark verified that the proposed method is invisible and robust to geometric attacks such as rotation, scaling and translation. In experiments with an XYZ Printing Pro 3D printer and 3D scanner, the accuracy and performance of the proposed method was higher than the two previous methods in the 3D printing watermarking domain. The proposed method provides a better solution for the copyright protection of 3D printing. Full article
(This article belongs to the Special Issue Information Technology and Its Applications 2018)
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Open AccessArticle How to Address the Data Quality Issues in Regression Models: A Guided Process for Data Cleaning
Symmetry 2018, 10(4), 99; doi:10.3390/sym10040099
Received: 9 March 2018 / Revised: 28 March 2018 / Accepted: 30 March 2018 / Published: 6 April 2018
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Abstract
Today, data availability has gone from scarce to superabundant. Technologies like IoT, trends in social media and the capabilities of smart-phones are producing and digitizing lots of data that was previously unavailable. This massive increase of data creates opportunities to gain new business
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Today, data availability has gone from scarce to superabundant. Technologies like IoT, trends in social media and the capabilities of smart-phones are producing and digitizing lots of data that was previously unavailable. This massive increase of data creates opportunities to gain new business models, but also demands new techniques and methods of data quality in knowledge discovery, especially when the data comes from different sources (e.g., sensors, social networks, cameras, etc.). The data quality process of the data set proposes conclusions about the information they contain. This is increasingly done with the aid of data cleaning approaches. Therefore, guaranteeing a high data quality is considered as the primary goal of the data scientist. In this paper, we propose a process for data cleaning in regression models (DC-RM). The proposed data cleaning process is evaluated through a real datasets coming from the UCI Repository of Machine Learning Databases. With the aim of assessing the data cleaning process, the dataset that is cleaned by DC-RM was used to train the same regression models proposed by the authors of UCI datasets. The results achieved by the trained models with the dataset produced by DC-RM are better than or equal to that presented by the datasets’ authors. Full article
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Open AccessArticle Nonclassical Symmetries of a Power Law Harry Dym Equation
Symmetry 2018, 10(4), 100; doi:10.3390/sym10040100
Received: 31 January 2018 / Revised: 3 April 2018 / Accepted: 4 April 2018 / Published: 6 April 2018
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Abstract
It is generally known that classical point and potential Lie symmetries of differential equations can be different. In a recent paper, we were able to show for a class of nonlinear diffusion equation that the nonclassical potential symmetries possess all nonclassical symmetries of
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It is generally known that classical point and potential Lie symmetries of differential equations can be different. In a recent paper, we were able to show for a class of nonlinear diffusion equation that the nonclassical potential symmetries possess all nonclassical symmetries of the original equation. We question whether this is true for the power law Harry Dym equation. In this paper, we show that the nonclassical symmetries of the power law Harry Dym equation and an equivalent system still possess special separate symmetries. However, we will show that we can extend the nonclassical method so that all nonclassical symmetries of the original power law Harry Dym equation can be obtained through the equivalent system. Full article
Open AccessArticle A Framework for Circular Multilevel Systems in the Frequency Domain
Symmetry 2018, 10(4), 101; doi:10.3390/sym10040101
Received: 9 February 2018 / Revised: 29 March 2018 / Accepted: 31 March 2018 / Published: 8 April 2018
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Abstract
In this paper, we will construct a new multilevel system in the Fourier domain using the harmonic wavelet. The main advantages of harmonic wavelet are that its frequency spectrum is confined exactly to an octave band, and its simple definition just as Haar
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In this paper, we will construct a new multilevel system in the Fourier domain using the harmonic wavelet. The main advantages of harmonic wavelet are that its frequency spectrum is confined exactly to an octave band, and its simple definition just as Haar wavelet. The constructed multilevel system has the circular shape, which forms a partition of the frequency domain by shifting and scaling the basic wavelet functions. To possess the circular shape, a new type of sampling grid, the circular-polar grid (CPG), is defined and also the corresponding modified Fourier transform. The CPG consists of equal space along rays, where different rays are equally angled. The main difference between the classic polar grid and CPG is the even sampling on polar coordinates. Another obvious difference is that the modified Fourier transform has a circular shape in the frequency domain while the polar transform has a square shape. The proposed sampling grid and the new defined Fourier transform constitute a completely Fourier transform system, more importantly, the harmonic wavelet based multilevel system defined on the proposed sampling grid is more suitable for the distribution of general images in the Fourier domain. Full article
(This article belongs to the Special Issue Symmetry and Complexity)
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Open AccessFeature PaperArticle Recomputing Causality Assignments on Lumped Process Models When Adding New Simplification Assumptions
Symmetry 2018, 10(4), 102; doi:10.3390/sym10040102
Received: 16 March 2018 / Revised: 3 April 2018 / Accepted: 5 April 2018 / Published: 9 April 2018
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Abstract
This paper presents a new algorithm for the resolution of over-constrained lumped process systems, where partial differential equations of a continuous time and space model of the system are reduced into ordinary differential equations with a finite number of parameters and where the
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This paper presents a new algorithm for the resolution of over-constrained lumped process systems, where partial differential equations of a continuous time and space model of the system are reduced into ordinary differential equations with a finite number of parameters and where the model equations outnumber the unknown model variables. Our proposal is aimed at the study and improvement of the algorithm proposed by Hangos-Szerkenyi-Tuza. This new algorithm improves the computational cost and solves some of the internal problems of the aforementioned algorithm in its original formulation. The proposed algorithm is based on parameter relaxation that can be modified easily. It retains the necessary information of the lumped process system to reduce the time cost after introducing changes during the system formulation. It also allows adjustment of the system formulations that change its differential index between simulations. Full article
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Open AccessArticle Study on an Adaptive Co-Evolutionary ACO Algorithm for Complex Optimization Problems
Symmetry 2018, 10(4), 104; doi:10.3390/sym10040104
Received: 24 March 2018 / Revised: 7 April 2018 / Accepted: 9 April 2018 / Published: 11 April 2018
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Abstract
The ant colony optimization (ACO) algorithm has the characteristics of positive feedback, essential parallelism, and global convergence, but it has the shortcomings of premature convergence and slow convergence speed. The co-evolutionary algorithm (CEA) emphasizes the existing interaction among different sub-populations, but it is
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The ant colony optimization (ACO) algorithm has the characteristics of positive feedback, essential parallelism, and global convergence, but it has the shortcomings of premature convergence and slow convergence speed. The co-evolutionary algorithm (CEA) emphasizes the existing interaction among different sub-populations, but it is overly formal, and does not form a very strict and unified definition. Therefore, a new adaptive co-evolutionary ant colony optimization (SCEACO) algorithm based on the complementary advantages and hybrid mechanism is proposed in this paper. Firstly, the pheromone update formula is improved and the pheromone range of the ACO algorithm is limited in order to achieve the adaptive update of the pheromone. The elitist strategy and co-evolutionary idea are used for reference, the symbiotic mechanism and hybrid mechanism are introduced to better utilize the advantages of the CEA and ACO. Then the multi-objective optimization problem is divided into several sub-problems, each sub-problem corresponds to one population. Each ant colony is divided into multiple sub-populations in a common search space, and each sub-population performs the search activity and pheromone updating strategy. The elitist strategy is used to retain the elitist individuals within the population and the min-max ant strategy is used to set pheromone concentration for each path. Next, the selection, crossover, and mutation operations of individuals are introduced to adaptively adjust the parameters and implement the information sharing of the population and the co-evolution. Finally, the gate assignment problem of a hub airport is selected to verify the optimization performance of the SCEACO algorithm. The experiment results show that the SCEACO algorithm can effectively solve the gate assignment problem of a hub airport and obtain the effective assignment result. The SCEACO algorithm improves the convergence speed, and enhances the local search ability and global search capability. Full article
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Open AccessFeature PaperArticle Pre-Rationalized Parametric Designing of Roof Shells Formed by Repetitive Modules of Catalan Surfaces
Symmetry 2018, 10(4), 105; doi:10.3390/sym10040105
Received: 13 February 2018 / Revised: 6 April 2018 / Accepted: 8 April 2018 / Published: 11 April 2018
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Abstract
The aim of the study is to develop an original, methodical, and practical approach to the early stages of parametric design of roof shells formed by repetitive modules of Catalan surfaces. It is presented on the example of designing the roof shells compound
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The aim of the study is to develop an original, methodical, and practical approach to the early stages of parametric design of roof shells formed by repetitive modules of Catalan surfaces. It is presented on the example of designing the roof shells compound of four concrete elements. The designing process proposed by us consists in linking geometric shaping of roofs’ models with their structural analysis and optimization. Contrary to other methods, which use optimization process in order to find free roof forms, we apply it in order to explore and improve design alternatives. It is realized with the application of designing tools working in Rhinoceros 3D software. The flexible scripts elaborated by us, in order to achieve roofs’ models of regular and symmetrical shapes, are converted into simulation models to perform structural analysis. It is mainly focused on how the roof shells perform dependently on their geometric characteristics. The simulation enables one to evaluate various roof shells’ shapes, as well as to select an optimal design solution. The proposed approach to the conceptual design process may drive the designing to achieve geometric and structural forms which not only follow the design intentions but also target better results. Full article
(This article belongs to the Special Issue Civil Engineering and Symmetry)
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Open AccessFeature PaperArticle Neutrosophic Association Rule Mining Algorithm for Big Data Analysis
Symmetry 2018, 10(4), 106; doi:10.3390/sym10040106
Received: 5 March 2018 / Revised: 29 March 2018 / Accepted: 9 April 2018 / Published: 11 April 2018
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Abstract
Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process,
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Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process, which is indented to determine interesting associations between items and to establish a set of association rules whose support is greater than a specific threshold. The classical association rules can only be extracted from binary data where an item exists in a transaction, but it fails to deal effectively with quantitative attributes, through decreasing the quality of generated association rules due to sharp boundary problems. In order to overcome the drawbacks of classical association rule mining, we propose in this research a new neutrosophic association rule algorithm. The algorithm uses a new approach for generating association rules by dealing with membership, indeterminacy, and non-membership functions of items, conducting to an efficient decision-making system by considering all vague association rules. To prove the validity of the method, we compare the fuzzy mining and the neutrosophic mining. The results show that the proposed approach increases the number of generated association rules. Full article
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Open AccessArticle Deep Learning-Based Image Segmentation for Al-La Alloy Microscopic Images
Symmetry 2018, 10(4), 107; doi:10.3390/sym10040107
Received: 24 March 2018 / Revised: 2 April 2018 / Accepted: 3 April 2018 / Published: 13 April 2018
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Abstract
Quantitative analysis through image processing is a key step to gain information regarding the microstructure of materials. In this paper, we develop a deep learning-based method to address the task of image segmentation for microscopic images using an Al–La alloy. Our work makes
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Quantitative analysis through image processing is a key step to gain information regarding the microstructure of materials. In this paper, we develop a deep learning-based method to address the task of image segmentation for microscopic images using an Al–La alloy. Our work makes three key contributions. (1) We train a deep convolutional neural network based on DeepLab to achieve image segmentation and have significant results. (2) We adopt a local processing method based on symmetric overlap-tile strategy which makes it possible to analyze the microscopic images with high resolution. Additionally, it achieves seamless segmentation. (3) We apply symmetric rectification to enhance the accuracy of results with 3D information. Experimental results showed that our method outperforms existing segmentation methods. Full article
(This article belongs to the Special Issue Symmetry in Cooperative Applications III)
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Open AccessArticle Age Estimation Robust to Optical and Motion Blurring by Deep Residual CNN
Symmetry 2018, 10(4), 108; doi:10.3390/sym10040108
Received: 9 March 2018 / Revised: 9 April 2018 / Accepted: 10 April 2018 / Published: 13 April 2018
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Abstract
Recently, real-time human age estimation based on facial images has been applied in various areas. Underneath this phenomenon lies an awareness that age estimation plays an important role in applying big data to target marketing for age groups, product demand surveys, consumer trend
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Recently, real-time human age estimation based on facial images has been applied in various areas. Underneath this phenomenon lies an awareness that age estimation plays an important role in applying big data to target marketing for age groups, product demand surveys, consumer trend analysis, etc. However, in a real-world environment, various optical and motion blurring effects can occur. Such effects usually cause a problem in fully capturing facial features such as wrinkles, which are essential to age estimation, thereby degrading accuracy. Most of the previous studies on age estimation were conducted for input images almost free from blurring effect. To overcome this limitation, we propose the use of a deep ResNet-152 convolutional neural network for age estimation, which is robust to various optical and motion blurring effects of visible light camera sensors. We performed experiments with various optical and motion blurred images created from the park aging mind laboratory (PAL) and craniofacial longitudinal morphological face database (MORPH) databases, which are publicly available. According to the results, the proposed method exhibited better age estimation performance than the previous methods. Full article
(This article belongs to the Special Issue Deep Learning-Based Biometric Technologies)
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Open AccessArticle TPVR: User Interaction of Third Person Virtual Reality for New Presence and Experience
Symmetry 2018, 10(4), 109; doi:10.3390/sym10040109
Received: 5 March 2018 / Revised: 10 April 2018 / Accepted: 11 April 2018 / Published: 14 April 2018
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Abstract
This study proposes the interaction of third-person virtual reality (TPVR) to provide users with a new presence and experience during immersive virtual reality (VR). The proposed TPVR interaction consists of the ability to directly control the virtual environment and objects by utilizing the
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This study proposes the interaction of third-person virtual reality (TPVR) to provide users with a new presence and experience during immersive virtual reality (VR). The proposed TPVR interaction consists of the ability to directly control the virtual environment and objects by utilizing the hands. For this purpose, this study defines the interaction of TPVR from three types: moving inside the virtual environment, selecting virtual objects and using a menu interface that includes a variety of functions and behaviors. Then, it designs its own experimental application that is able to systematically compare and analyze the proposed interaction against traditional first-person perspective VR. Finally, it examines whether the proposed interaction provides new presence and experience to users by conducting survey experiments. Through this process, this study was able to confirm not only that TPVR interaction can provide a sufficient presence, even in comparison with the first-person viewpoint, but also that it causes less VR sickness and offers a differentiated VR experience, suggesting that the proposed interaction can provide an alternative method for utilizing VR technology in a greater variety of fields. Full article
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Open AccessArticle Enhancing Data Transfer Performance Utilizing a DTN between Cloud Service Providers
Symmetry 2018, 10(4), 110; doi:10.3390/sym10040110
Received: 30 March 2018 / Revised: 9 April 2018 / Accepted: 12 April 2018 / Published: 16 April 2018
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Abstract
The rapid transfer of massive data in the cloud environment is required to prepare for unexpected situations like disaster recovery. With regard to this requirement, we propose a new approach to transferring cloud virtual machine images rapidly in the cloud environment utilizing dedicated
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The rapid transfer of massive data in the cloud environment is required to prepare for unexpected situations like disaster recovery. With regard to this requirement, we propose a new approach to transferring cloud virtual machine images rapidly in the cloud environment utilizing dedicated Data Transfer Nodes (DTNs). The overall procedure is composed of local/remote copy processes and a DTN-to-DTN transfer process. These processes are coordinated and executed based on a fork system call in the proposed algorithm. In addition, we especially focus on the local copy process between a cloud controller and DTNs and improve data transfer performance through the well-tuned mount techniques in Network File System (NFS)-based connections. Several experiments have been performed considering the combination of synchronous/asynchronous modes and the network buffer size. We show the results of throughput in all the experiment cases and compare them. Consequently, the best throughput in write operations has been obtained in the case of an NFS server in a DTN and an NFS client in a cloud controller running entirely in the asynchronous mode. Full article
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Open AccessFeature PaperArticle New Similarity Solutions of a Generalized Variable-Coefficient Gardner Equation with Forcing Term
Symmetry 2018, 10(4), 112; doi:10.3390/sym10040112
Received: 2 April 2018 / Revised: 11 April 2018 / Accepted: 12 April 2018 / Published: 16 April 2018
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Abstract
The compatibility method is used for a generalized variable-coefficient Gardner equation (GVGE) with a forcing term. By the compatibility of the considered equation and a non-classical symmetry of a given form, four types of symmetry are obtained. Then, by solving the characteristic equations
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The compatibility method is used for a generalized variable-coefficient Gardner equation (GVGE) with a forcing term. By the compatibility of the considered equation and a non-classical symmetry of a given form, four types of symmetry are obtained. Then, by solving the characteristic equations of symmetry, the GVGE is reduced to variable coefficients ordinary differential equations, and rich varieties of new similarity solutions are presented. Our results show that the compatibility method can be employed for variable coefficients nonlinear evolution equations with forcing terms. Full article
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Open AccessArticle Application of Sliding Nest Window Control Chart in Data Stream Anomaly Detection
Symmetry 2018, 10(4), 113; doi:10.3390/sym10040113
Received: 9 April 2018 / Revised: 9 April 2018 / Accepted: 12 April 2018 / Published: 17 April 2018
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Abstract
Since data stream anomaly detection algorithms based on sliding windows are sensitive to the abnormal deviation of individual interference data, this paper presents a sliding nest window chart anomaly detection based on the data stream (SNWCAD-DS) by employing the concept of the sliding
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Since data stream anomaly detection algorithms based on sliding windows are sensitive to the abnormal deviation of individual interference data, this paper presents a sliding nest window chart anomaly detection based on the data stream (SNWCAD-DS) by employing the concept of the sliding window and control chart. By nesting a small sliding window in a large sliding window and analyzing the deviation distance between the small window and the large sliding window, the algorithm increases the out-of-bounds detection ratio and classifies the conceptual drift data stream online. The designed algorithm is simulated on the industrial data stream of drilling engineering. The proposed algorithm SNWCAD is compared with Automatic Outlier Detection for Data Streams (A-ODDS) and Distance-Based Outline Detection for Data Stream (DBOD-DS). The experimental results show that the new algorithm can obtain higher detection accuracy than the compared algorithms. Furthermore, it can shield the influence of individual interference data and satisfy actual engineering needs. Full article
(This article belongs to the Special Issue Information Technology and Its Applications 2018)
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Open AccessArticle Understanding Review Expertise of Developers: A Reviewer Recommendation Approach Based on Latent Dirichlet Allocation
Symmetry 2018, 10(4), 114; doi:10.3390/sym10040114
Received: 21 March 2018 / Revised: 11 April 2018 / Accepted: 16 April 2018 / Published: 17 April 2018
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Abstract
The code reviewer assignment problem affects the reviewing time of a source code change. To effectively perform the code review process of a software project, the code reviewer assignment problem must be dealt with. Reviewer recommendation can reduce the time required for finding
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The code reviewer assignment problem affects the reviewing time of a source code change. To effectively perform the code review process of a software project, the code reviewer assignment problem must be dealt with. Reviewer recommendation can reduce the time required for finding appropriate reviewers for a given source code change. In this paper, we propose a reviewer recommendation approach based on latent Dirichlet allocation (LDA). The proposed reviewer recommendation approach consists of a review expertise generation phase and a reviewer recommendation phase. The review expertise generation phase generates the review expertise of developers for topics of source code changes from the review history of a software project. The reviewer recommendation phase computes the review scores of the developers according to the topic distribution of a given source code change and the review expertise of the developers. In an empirical evaluation of five open source projects, we confirm that the proposed reviewer recommendation approach obtains better average top-10 accuracy than existing reviewer recommendation approaches. Full article
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Open AccessArticle New Multiple Attribute Decision Making Method Based on DEMATEL and TOPSIS for Multi-Valued Interval Neutrosophic Sets
Symmetry 2018, 10(4), 115; doi:10.3390/sym10040115
Received: 20 March 2018 / Revised: 9 April 2018 / Accepted: 10 April 2018 / Published: 17 April 2018
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Abstract
Interval neutrosophic fuzzy decision making is an important part of decision making under uncertainty, which is based on preference order. In this study, a new multi-valued interval neutrosophic fuzzy multiple attribute decision making method has been developed by integrating the DEMATEL (decision making
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Interval neutrosophic fuzzy decision making is an important part of decision making under uncertainty, which is based on preference order. In this study, a new multi-valued interval neutrosophic fuzzy multiple attribute decision making method has been developed by integrating the DEMATEL (decision making trial and evaluation laboratory) method and the TOPSIS (the technique for order preference by similarity to an ideal solution) method. Evaluation values are given in the form of multi-valued interval neutrosophic fuzzy values. By using DEMATEL, dependencies among attributes can be modeled, and attribute weights are determined. The normalized Euclidean distance and the normalized Hamming distance between multi-valued interval neutrosophic fuzzy values are defined. Alternatives are ranked by using the TOPSIS method based on the distance measures. The truck selection problem in the logistics industry is presented to illustrate the feasibility and practical advantages of the proposed method. Some comparisons of the new method with other methods are also made. Full article
Open AccessArticle An Extension of Neutrosophic AHP–SWOT Analysis for Strategic Planning and Decision-Making
Symmetry 2018, 10(4), 116; doi:10.3390/sym10040116
Received: 2 March 2018 / Revised: 10 April 2018 / Accepted: 12 April 2018 / Published: 17 April 2018
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Abstract
Every organization seeks to set strategies for its development and growth and to do this, it must take into account the factors that affect its success or failure. The most widely used technique in strategic planning is SWOT analysis. SWOT examines strengths (S),
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Every organization seeks to set strategies for its development and growth and to do this, it must take into account the factors that affect its success or failure. The most widely used technique in strategic planning is SWOT analysis. SWOT examines strengths (S), weaknesses (W), opportunities (O) and threats (T), to select and implement the best strategy to achieve organizational goals. The chosen strategy should harness the advantages of strengths and opportunities, handle weaknesses, and avoid or mitigate threats. SWOT analysis does not quantify factors (i.e., strengths, weaknesses, opportunities and threats) and it fails to rank available alternatives. To overcome this drawback, we integrated it with the analytic hierarchy process (AHP). The AHP is able to determine both quantitative and the qualitative elements by weighting and ranking them via comparison matrices. Due to the vague and inconsistent information that exists in the real world, we applied the proposed model in a neutrosophic environment. A real case study of Starbucks Company was presented to validate our model. Full article
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Open AccessArticle Human Bodily Asymmetry Relates to Behavioral Lateralization and May not Reliably Reflect Developmental Instability
Symmetry 2018, 10(4), 117; doi:10.3390/sym10040117
Received: 23 January 2018 / Revised: 7 March 2018 / Accepted: 12 April 2018 / Published: 18 April 2018
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Abstract
(1) Background: The link between behavioral lateralization and bodily asymmetry in humans is studied to investigate the reliability of fluctuating asymmetry as a measure of developmental instability; (2) Methods: Morphological asymmetries of arms and legs, obtained from 3D body scans, were correlated with
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(1) Background: The link between behavioral lateralization and bodily asymmetry in humans is studied to investigate the reliability of fluctuating asymmetry as a measure of developmental instability; (2) Methods: Morphological asymmetries of arms and legs, obtained from 3D body scans, were correlated with different measures of behavioral lateralization; (3) Results: Observed associations were in the directions expected, showing that more asymmetric use of the body increases asymmetry, especially in the arms, and more symmetric body use appears to have a symmetrizing effect; and (4) Conclusions: The results presented here question the suitability of human bodily asymmetry in arms and legs—or at least part of them—as a measure of developmental instability. There is a need for future research that identifies regions of the body that are not affected by behavioral lateralization and can reliably reflect developmental instability. Full article
(This article belongs to the Special Issue Applications Based on Symmetrical Characteristics of the Human Body)
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Open AccessArticle A Simple Method for Measuring the Bilateral Symmetry of Leaves
Symmetry 2018, 10(4), 118; doi:10.3390/sym10040118
Received: 21 March 2018 / Revised: 14 April 2018 / Accepted: 16 April 2018 / Published: 18 April 2018
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Abstract
Many plant leaves exhibit bilateral symmetry, but such symmetry has rarely been measured because of the lack of practical methods. We propose a simple method for achieving the above objective. A leaf is divided into left and right sides, and several equally-sized strips
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Many plant leaves exhibit bilateral symmetry, but such symmetry has rarely been measured because of the lack of practical methods. We propose a simple method for achieving the above objective. A leaf is divided into left and right sides, and several equally-sized strips are generated to intersect each side of that leaf to generate pairwise left and right sub-regions. A standardized index (SI) for measuring bilateral symmetry is built based on the left–right areal differences of those sub-regions. The leaves of 10 species of plants were sampled for testing the method’s validity. Based on the experimental data, we compared the root-mean-squared error (RMSE), SI, and areal ratio (AR) of the left side to the right side of the leaf. The SI measures the bilateral symmetry of plant leaves well, and it is better than the RMSE and AR for eliminating the effect of leaf size on the goodness of fit. The SI proposed here is the best indicator for evaluating the degree of bilateral symmetry and can be potentially used for comparing the difference in the bilateral symmetry of leaves of different plants. Full article
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Open AccessArticle A Novel Skin Lesion Detection Approach Using Neutrosophic Clustering and Adaptive Region Growing in Dermoscopy Images
Symmetry 2018, 10(4), 119; doi:10.3390/sym10040119
Received: 26 March 2018 / Revised: 9 April 2018 / Accepted: 14 April 2018 / Published: 18 April 2018
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Abstract
This paper proposes novel skin lesion detection based on neutrosophic clustering and adaptive region growing algorithms applied to dermoscopic images, called NCARG. First, the dermoscopic images are mapped into a neutrosophic set domain using the shearlet transform results for the images. The images
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This paper proposes novel skin lesion detection based on neutrosophic clustering and adaptive region growing algorithms applied to dermoscopic images, called NCARG. First, the dermoscopic images are mapped into a neutrosophic set domain using the shearlet transform results for the images. The images are described via three memberships: true, indeterminate, and false memberships. An indeterminate filter is then defined in the neutrosophic set for reducing the indeterminacy of the images. A neutrosophic c-means clustering algorithm is applied to segment the dermoscopic images. With the clustering results, skin lesions are identified precisely using an adaptive region growing method. To evaluate the performance of this algorithm, a public data set (ISIC 2017) is employed to train and test the proposed method. Fifty images are randomly selected for training and 500 images for testing. Several metrics are measured for quantitatively evaluating the performance of NCARG. The results establish that the proposed approach has the ability to detect a lesion with high accuracy, 95.3% average value, compared to the obtained average accuracy, 80.6%, found when employing the neutrosophic similarity score and level set (NSSLS) segmentation approach. Full article
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Open AccessArticle Symmetry Reduction and Numerical Solution of Von K a ´ rm a ´ n Swirling Viscous Flow
Symmetry 2018, 10(4), 120; doi:10.3390/sym10040120
Received: 28 February 2018 / Revised: 29 March 2018 / Accepted: 8 April 2018 / Published: 19 April 2018
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Abstract
In this paper, the numerical solutions of von K a´ rm a´ n swirling viscous flow are obtained based on the effective combination of the symmetry method and the Runge-Kutta method. Firstly, the multi-parameter symmetry of von K a´ rm
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In this paper, the numerical solutions of von K a ´ rm a ´ n swirling viscous flow are obtained based on the effective combination of the symmetry method and the Runge-Kutta method. Firstly, the multi-parameter symmetry of von K a ´ rm a ´ n swirling viscous flow is determined based on the differential characteristic set algorithm. Secondly, we used the symmetry to reduce von K a ´ rm a ´ n swirling viscous flow to an initial value problem of the original differential equations. Finally, we numerically solve the initial value problem of the original differential equations by using the Runge-Kutta method. Full article
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Open AccessFeature PaperArticle Stability of Bounded Dynamical Networks with Symmetry
Symmetry 2018, 10(4), 121; doi:10.3390/sym10040121
Received: 2 April 2018 / Revised: 12 April 2018 / Accepted: 13 April 2018 / Published: 19 April 2018
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Abstract
Motivated by dynamical models describing phase separation and the motion of interfaces separating phases, we study the stability of dynamical networks in planar domains formed by triple junctions. We take into account symmetry, angle-intersection conditions at the junctions and at the points at
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Motivated by dynamical models describing phase separation and the motion of interfaces separating phases, we study the stability of dynamical networks in planar domains formed by triple junctions. We take into account symmetry, angle-intersection conditions at the junctions and at the points at which the curves intersect with the boundary. Firstly, we focus on the case of a network where two triple junctions have all their branches unattached to the boundary and then on the case of a network of hexagons, with one of them having all its branches unattached to the boundary. For both type of networks, we introduce the evolution problem, identify the steady states and study their stability in terms of the geometry of the boundary. Full article
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Open AccessArticle Cosmetic Detection Framework for Face and Iris Biometrics
Symmetry 2018, 10(4), 122; doi:10.3390/sym10040122
Received: 26 March 2018 / Revised: 15 April 2018 / Accepted: 16 April 2018 / Published: 19 April 2018
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Abstract
Cosmetics pose challenges to the recognition performance of face and iris biometric systems due to its ability to alter natural facial and iris patterns. Facial makeup and iris contact lens are considered to be commonly applied cosmetics for the face and iris in
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Cosmetics pose challenges to the recognition performance of face and iris biometric systems due to its ability to alter natural facial and iris patterns. Facial makeup and iris contact lens are considered to be commonly applied cosmetics for the face and iris in this study. The present work aims to present a novel solution for the detection of cosmetics in both face and iris biometrics by the fusion of texture, shape and color descriptors of images. The proposed cosmetic detection scheme combines the microtexton information from the local primitives of texture descriptors with the color spaces achieved from overlapped blocks in order to achieve better detection of spots, flat areas, edges, edge ends, curves, appearance and colors. The proposed cosmetic detection scheme was applied to the YMU YouTube makeup database (YMD) facial makeup database and IIIT-Delhi Contact Lens iris database. The results demonstrate that the proposed cosmetic detection scheme is significantly improved compared to the other schemes implemented in this study. Full article
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Open AccessArticle Accountability Requirements in the Cloud Provider Chain
Symmetry 2018, 10(4), 124; doi:10.3390/sym10040124 (registering DOI)
Received: 21 January 2018 / Revised: 3 April 2018 / Accepted: 17 April 2018 / Published: 20 April 2018
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Abstract
In order to be responsible stewards of other people’s data, cloud providers must be accountable for their data handling practices. The potential long provider chains in cloud computing introduce additional accountability challenges, with many stakeholders involved. Symmetry is very important in any requirements’
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In order to be responsible stewards of other people’s data, cloud providers must be accountable for their data handling practices. The potential long provider chains in cloud computing introduce additional accountability challenges, with many stakeholders involved. Symmetry is very important in any requirements’ elicitation activity, since input from diverse stakeholders needs to be balanced. This article ventures to answer the question “How can one create an accountable cloud service?” by examining requirements which must be fulfilled to achieve an accountability-based approach, based on interaction with over 300 stakeholders. Full article
(This article belongs to the Special Issue Emerging Approaches and Advances in Cloud Computing)
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Open AccessArticle Efficient Algorithms for Real-Time GPU Volumetric Cloud Rendering with Enhanced Geometry
Symmetry 2018, 10(4), 125; doi:10.3390/sym10040125 (registering DOI)
Received: 6 March 2018 / Revised: 13 April 2018 / Accepted: 18 April 2018 / Published: 20 April 2018
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Abstract
This paper presents several new techniques for volumetric cloud rendering using efficient algorithms and data structures based on ray-tracing methods for cumulus generation, achieving an optimum balance between realism and performance. These techniques target applications such as flight simulations, computer games, and educational
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This paper presents several new techniques for volumetric cloud rendering using efficient algorithms and data structures based on ray-tracing methods for cumulus generation, achieving an optimum balance between realism and performance. These techniques target applications such as flight simulations, computer games, and educational software, even with conventional graphics hardware. The contours of clouds are defined by implicit mathematical expressions or triangulated structures inside which volumetric rendering is performed. Novel techniques are used to reproduce the asymmetrical nature of clouds and the effects of light-scattering, with low computing costs. The work includes a new method to create randomized fractal clouds using a recursive grammar. The graphical results are comparable to those produced by state-of-the-art, hyper-realistic algorithms. These methods provide real-time performance, and are superior to particle-based systems. These outcomes suggest that our methods offer a good balance between realism and performance, and are suitable for use in the standard graphics industry. Full article
(This article belongs to the Special Issue Information Technology and Its Applications 2018)
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Open AccessArticle Neutrosophic Triplet Cosets and Quotient Groups
Symmetry 2018, 10(4), 126; doi:10.3390/sym10040126 (registering DOI)
Received: 29 March 2018 / Revised: 16 April 2018 / Accepted: 17 April 2018 / Published: 20 April 2018
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Abstract
In this paper, by utilizing the concept of a neutrosophic extended triplet (NET), we define the neutrosophic image, neutrosophic inverse-image, neutrosophic kernel, and the NET subgroup. The notion of the neutrosophic triplet coset and its relation with the classical coset are defined and
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In this paper, by utilizing the concept of a neutrosophic extended triplet (NET), we define the neutrosophic image, neutrosophic inverse-image, neutrosophic kernel, and the NET subgroup. The notion of the neutrosophic triplet coset and its relation with the classical coset are defined and the properties of the neutrosophic triplet cosets are given. Furthermore, the neutrosophic triplet normal subgroups, and neutrosophic triplet quotient groups are studied. Full article
Open AccessArticle Some Interval Neutrosophic Linguistic Maclaurin Symmetric Mean Operators and Their Application in Multiple Attribute Decision Making
Symmetry 2018, 10(4), 127; doi:10.3390/sym10040127 (registering DOI)
Received: 10 April 2018 / Revised: 15 April 2018 / Accepted: 17 April 2018 / Published: 22 April 2018
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Abstract
There are many practical decision-making problems in people’s lives, but the information given by decision makers (DMs) is often unclear and how to describe this information is of critical importance. Therefore, we introduce interval neutrosophic linguistic numbers (INLNs) to represent the less clear
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There are many practical decision-making problems in people’s lives, but the information given by decision makers (DMs) is often unclear and how to describe this information is of critical importance. Therefore, we introduce interval neutrosophic linguistic numbers (INLNs) to represent the less clear and uncertain information and give their operational rules and comparison methods. In addition, since the Maclaurin symmetric mean (MSM) operator has the special characteristic of capturing the interrelationships among multi-input arguments, we further propose an MSM operator for INLNs (INLMSM). Furthermore, considering the weights of attributes are the important parameters and they can influence the decision results, we also propose a weighted INLMSM (WINLMSM) operator. Based on the WINLMSM operator, we develop a multiple attribute decision making (MADM) method with INLNs and some examples are used to show the procedure and effectiveness of the proposed method. Compared with the existing methods, the proposed method is more convenient to express the complex and unclear information. At the same time, it is more scientific and flexible in solving the MADM problems by considering the interrelationships among multi-attributes. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)

Review

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Open AccessReview The Breaking of Symmetry Leads to Chirality in Cucurbituril-Type Hosts
Symmetry 2018, 10(4), 98; doi:10.3390/sym10040098
Received: 2 February 2018 / Revised: 19 March 2018 / Accepted: 30 March 2018 / Published: 5 April 2018
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Abstract
Cucurbituril-type hosts are highly symmetric, but there are means to break their symmetry. This review will present examples from three directions of induction of chirality in or by cucurbituril-type hosts: first, through the incorporation of stereogenic elements into host molecules; second, through complexation
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Cucurbituril-type hosts are highly symmetric, but there are means to break their symmetry. This review will present examples from three directions of induction of chirality in or by cucurbituril-type hosts: first, through the incorporation of stereogenic elements into host molecules; second, through complexation with achiral guests, which leads to axial supramolecular chirality and helical structures; third, through the formation of complexes with chiral guests in multi-molecule complexes and induction of supramolecular chirality. In addition, a list of chiral guests used in binding studies with cucurbiturils is collected. We would envision that encouraged by the outlined examples of outstanding applications of chiral cucurbituril-supramolecular systems, the boundaries of chiral applications of cucurbiturils would be widened. Full article
(This article belongs to the Special Issue Chiral Auxiliaries and Chirogenesis)
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Open AccessFeature PaperReview The Spatial Homeostasis Hypothesis
Symmetry 2018, 10(4), 103; doi:10.3390/sym10040103
Received: 12 March 2018 / Revised: 5 April 2018 / Accepted: 8 April 2018 / Published: 10 April 2018
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Abstract
From studies on the effects of “high dilutions” on organisms, it was found that their administration induces a delicate physiological (molecular and cellular) response. Occasionally, physiological reactions can become atypical (pathological) individual reactions. To resolve this paradox, the spatial homeostasis hypothesis has been
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From studies on the effects of “high dilutions” on organisms, it was found that their administration induces a delicate physiological (molecular and cellular) response. Occasionally, physiological reactions can become atypical (pathological) individual reactions. To resolve this paradox, the spatial homeostasis hypothesis has been proposed. It considers pathological processes as tools used by living systems, in order to retain their spatial integrity (symmetry), allowing them to properly reflect the geometry of the surrounding world and thus, to be a part of the evolutionary process. This article addresses an interdisciplinary subject and is aimed at natural scientists (physicists, chemists, and biologists) as well as philosophers. Full article
(This article belongs to the Special Issue Symmetry: Anniversary Feature Papers 2018)
Open AccessFeature PaperReview Lie and Q-Conditional Symmetries of Reaction-Diffusion-Convection Equations with Exponential Nonlinearities and Their Application for Finding Exact Solutions
Symmetry 2018, 10(4), 123; doi:10.3390/sym10040123 (registering DOI)
Received: 13 March 2018 / Revised: 11 April 2018 / Accepted: 12 April 2018 / Published: 20 April 2018
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Abstract
This review is devoted to search for Lie and Q-conditional (nonclassical) symmetries and exact solutions of a class of reaction-diffusion-convection equations with exponential nonlinearities. A complete Lie symmetry classification of the class is derived via two different algorithms in order to show
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This review is devoted to search for Lie and Q-conditional (nonclassical) symmetries and exact solutions of a class of reaction-diffusion-convection equations with exponential nonlinearities. A complete Lie symmetry classification of the class is derived via two different algorithms in order to show that the result depends essentially on the type of equivalence transformations used for the classification. Moreover, a complete description of Q-conditional symmetries for PDEs from the class in question is also presented. It is shown that all the well-known results for reaction-diffusion equations with exponential nonlinearities follow as particular cases from the results derived for this class of reaction-diffusion-convection equations. The symmetries obtained for constructing exact solutions of the relevant equations are successfully applied. The exact solutions are compared with those found by means of different techniques. Finally, an application of the exact solutions for solving boundary-value problems arising in population dynamics is presented. Full article
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Other

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Open AccessBrief Report Energy, Christiaan Huygens, and the Wonderful Cycloid—Theory versus Experiment
Symmetry 2018, 10(4), 111; doi:10.3390/sym10040111
Received: 4 February 2018 / Revised: 14 March 2018 / Accepted: 8 April 2018 / Published: 16 April 2018
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Abstract
The cycloid is one of the most intriguing objects in the classical physics world, at once solving the brachistochrone and isochronous curve problems. Historically, the cycloid shape has been employed to great success in many physical contexts. We discuss one such case, presenting
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The cycloid is one of the most intriguing objects in the classical physics world, at once solving the brachistochrone and isochronous curve problems. Historically, the cycloid shape has been employed to great success in many physical contexts. We discuss one such case, presenting the longitude problem as a pathway into an in-depth discussion of the analytical solution of a point mass motion along a cycloid. The classical solution is presented, and the modifications needed for a rolling ball along a cycloid rail are made. A comparison is then made between the two cases, and we show that the difference in most physical cases between the point mass and the rolling ball is at most ~7%. Next, an experiment is presented in which the isochronous nature of the cycloid path is tested, to different degrees of success. The results are discussed and several possible origins of the discrepancy between the theory and the experimental results are identified. We conclude with a discussion of skidding and slipless rolling. Full article
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