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Symmetry, Volume 8, Issue 12 (December 2016)

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Research

Jump to: Review, Other

Open AccessArticle Data Aggregation Gateway Framework for CoAP Group Communications
Symmetry 2016, 8(12), 138; doi:10.3390/sym8120138
Received: 7 August 2016 / Revised: 2 November 2016 / Accepted: 18 November 2016 / Published: 24 November 2016
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Abstract
In this paper, a data aggregation gateway framework (DA-GW) for constrained application protocol (CoAP) group communications is proposed. The DA-GW framework is designed to improve the throughput performance and energy efficiency of group communication to monitor and control multiple sensor devices collectively with
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In this paper, a data aggregation gateway framework (DA-GW) for constrained application protocol (CoAP) group communications is proposed. The DA-GW framework is designed to improve the throughput performance and energy efficiency of group communication to monitor and control multiple sensor devices collectively with a single user terminal. The DA-GW consists of four function blocks—the message analyzer, group manager, message scheduler and data handler—and three informative databases—the client database, resource database and information database. The DA-GW performs group management and group communication through each functional block and stores resources in the informative databases. The DA-GW employs international standard-based data structures and provides the interoperability of heterogeneous devices used in various applications. The DA-GW is implemented using a Java-based open source framework called jCoAP to evaluate the functions and performance of the DA-GW. The experiment results showed that the DA-GW framework revealed better performance than existing group communication methods in terms of throughput and energy consumption. Full article
(This article belongs to the Special Issue Symmetry in Systems Design and Analysis)
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Open AccessArticle Attribute Control Chart Construction Based on Fuzzy Score Number
Symmetry 2016, 8(12), 139; doi:10.3390/sym8120139
Received: 12 October 2016 / Revised: 12 November 2016 / Accepted: 22 November 2016 / Published: 26 November 2016
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Abstract
There is much uncertainty and fuzziness in product quality attributes or quality parameters of a manufacturing process, so the traditional quality control chart can be difficult to apply. This paper proposes a fuzzy control chart. The plotted data was obtained by transforming expert
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There is much uncertainty and fuzziness in product quality attributes or quality parameters of a manufacturing process, so the traditional quality control chart can be difficult to apply. This paper proposes a fuzzy control chart. The plotted data was obtained by transforming expert scores into fuzzy numbers. Two types of nonconformity judgment rules—necessity and possibility measurement rules—are proposed. Through graphical analysis, the nonconformity judging method (i.e., assessing directly based on the shape feature of a fuzzy control chart) is proposed. For four different widely used membership functions, control levels were analyzed and compared by observing gaps between the upper and lower control limits. The result of the case study validates the feasibility and reliability of the proposed approach. Full article
(This article belongs to the Special Issue Symmetry in Complex Networks II)
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Open AccessArticle Nonclassical Symmetries of a Nonlinear Diffusion–Convection/Wave Equation and Equivalents Systems
Symmetry 2016, 8(12), 140; doi:10.3390/sym8120140
Received: 7 August 2016 / Revised: 22 November 2016 / Accepted: 22 November 2016 / Published: 26 November 2016
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Abstract
It is generally known that classical point and potential Lie symmetries of differential equations (the latter calculated as point symmetries of an equivalent system) can be different. We question whether this is true when the symmetries are extended to nonclassical symmetries. In this
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It is generally known that classical point and potential Lie symmetries of differential equations (the latter calculated as point symmetries of an equivalent system) can be different. We question whether this is true when the symmetries are extended to nonclassical symmetries. In this paper, we consider two classes of nonlinear partial differential equations; the first one is a diffusion–convection equation, the second one a wave, where we will show that the majority of the nonclassical point symmetries are included in the nonclassical potential symmetries. We highlight a special case were the opposite is true. Full article
Open AccessArticle Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children’s Lifestyle Index
Symmetry 2016, 8(12), 141; doi:10.3390/sym8120141
Received: 17 July 2016 / Revised: 18 November 2016 / Accepted: 18 November 2016 / Published: 28 November 2016
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Abstract
Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household
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Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results are compared in terms of root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error metrics. An analysis of the proposed causal model suggests there are multiple significant interconnections among the variables of interest. According to both Bayesian and ML techniques, the proposed framework illustrates that parental socioeconomic status and parental lifestyle strongly impact children’s lifestyle. The impact of household food security on children’s lifestyle is rejected. However, there is a strong relationship between household food security and both parental socioeconomic status and parental lifestyle. Moreover, the outputs illustrate that the Bayesian prediction model has a good fit with the data, unlike the ML approach. The reasons for this discrepancy between ML and Bayesian prediction are debated and potential advantages and caveats with the application of the Bayesian approach in future studies are discussed. Full article
(This article belongs to the Special Issue Symmetry in Complex Networks II)
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Open AccessArticle Fluctuating Asymmetry of Craniological Features of Small Mammals as a Reflection of Heterogeneity of Natural Populations
Symmetry 2016, 8(12), 142; doi:10.3390/sym8120142
Received: 31 August 2016 / Revised: 14 November 2016 / Accepted: 23 November 2016 / Published: 29 November 2016
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Abstract
Fluctuating asymmetry (FA) in nine species of small mammals (Insectivora and Rodentia) was estimated using 10 cranial features (foramina for nerves and blood vessels). The main criterion was the occurrence of the fluctuating asymmetry manifestations (OFAM). A total of 2300 skulls collected in
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Fluctuating asymmetry (FA) in nine species of small mammals (Insectivora and Rodentia) was estimated using 10 cranial features (foramina for nerves and blood vessels). The main criterion was the occurrence of the fluctuating asymmetry manifestations (OFAM). A total of 2300 skulls collected in the taiga and forest-tundra of Yakutia (Northeast Asia) were examined. The examined species are characterized by comparable OFAM values in the vast territories of the taiga zone; on the ecological periphery of the range an increased FA level is registered. Asymmetric manifestations in analyzed features are equally likely to occur in males and females. OFAM values in juveniles are higher than in adults; this difference is more pronounced on the periphery of the geographic range. Among juveniles, lower FA levels are observed in individuals that have bred. It can be surmised that the risk of elimination of individuals with high FA levels increases in stressful periods (active reproduction and winter). In conditions that are close to optimal, populations demonstrate relatively homogeneous FA levels, while on the periphery of the area an increase in occurrence of disturbances in developmental stability is observed, which leads, on one hand, to higher average FA for the population and, on the other hand, to heterogeneity of the population in this parameter. Full article
(This article belongs to the Special Issue Fluctuating Asymmetry 2016)
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Open AccessArticle A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques
Symmetry 2016, 8(12), 143; doi:10.3390/sym8120143
Received: 31 July 2016 / Revised: 14 November 2016 / Accepted: 16 November 2016 / Published: 1 December 2016
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Abstract
This paper proposes novel edge-linking algorithms capable of producing a set of edge segments from a binary edge map generated by a conventional edge-detection algorithm. These proposed algorithms transform the conventional edge-linking problem into a single-target tracking problem, which is a well-known problem
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This paper proposes novel edge-linking algorithms capable of producing a set of edge segments from a binary edge map generated by a conventional edge-detection algorithm. These proposed algorithms transform the conventional edge-linking problem into a single-target tracking problem, which is a well-known problem in object tracking. The conversion of the problem enables us to apply sophisticated Bayesian inference to connect the edge points. We test our proposed approaches on real images that are corrupted with noise. Full article
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Open AccessArticle Using Convolutional Neural Network Filters to Measure Left-Right Mirror Symmetry in Images
Symmetry 2016, 8(12), 144; doi:10.3390/sym8120144
Received: 3 August 2016 / Revised: 1 November 2016 / Accepted: 28 November 2016 / Published: 1 December 2016
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Abstract
We propose a method for measuring symmetry in images by using filter responses from Convolutional Neural Networks (CNNs). The aim of the method is to model human perception of left/right symmetry as closely as possible. Using the Convolutional Neural Network (CNN) approach has
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We propose a method for measuring symmetry in images by using filter responses from Convolutional Neural Networks (CNNs). The aim of the method is to model human perception of left/right symmetry as closely as possible. Using the Convolutional Neural Network (CNN) approach has two main advantages: First, CNN filter responses closely match the responses of neurons in the human visual system; they take information on color, edges and texture into account simultaneously. Second, we can measure higher-order symmetry, which relies not only on color, edges and texture, but also on the shapes and objects that are depicted in images. We validated our algorithm on a dataset of 300 music album covers, which were rated according to their symmetry by 20 human observers, and compared results with those from a previously proposed method. With our method, human perception of symmetry can be predicted with high accuracy. Moreover, we demonstrate that the inclusion of features from higher CNN layers, which encode more abstract image content, increases the performance further. In conclusion, we introduce a model of left/right symmetry that closely models human perception of symmetry in CD album covers. Full article
(This article belongs to the Special Issue Symmetry in Vision)
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Open AccessArticle On Center, Periphery and Average Eccentricity for the Convex Polytopes
Symmetry 2016, 8(12), 145; doi:10.3390/sym8120145
Received: 3 November 2016 / Revised: 22 November 2016 / Accepted: 24 November 2016 / Published: 2 December 2016
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Abstract
A vertex v is a peripheral vertex in G if its eccentricity is equal to its diameter, and periphery P(G) is a subgraph of G induced by its peripheral vertices. Further, a vertex v in G is a central vertex
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A vertex v is a peripheral vertex in G if its eccentricity is equal to its diameter, and periphery P ( G ) is a subgraph of G induced by its peripheral vertices. Further, a vertex v in G is a central vertex if e ( v ) = r a d ( G ) , and the subgraph of G induced by its central vertices is called center C ( G ) of G . Average eccentricity is the sum of eccentricities of all of the vertices in a graph divided by the total number of vertices, i.e., a v e c ( G ) = { 1 n e G ( u ) ; u V ( G ) } . If every vertex in G is central vertex, then C ( G ) = G , and hence, G is self-centered. In this report, we find the center, periphery and average eccentricity for the convex polytopes. Full article
(This article belongs to the Special Issue Polyhedral Structures)
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Open AccessArticle Design of a Sustainable and Efficient Transportation Station (SETS) Based on Renewable Sources and Efficient Electric Drives
Symmetry 2016, 8(12), 146; doi:10.3390/sym8120146
Received: 31 October 2016 / Revised: 20 November 2016 / Accepted: 28 November 2016 / Published: 2 December 2016
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Abstract
The need for reduction in power consumption for public facilities has increased after the occurrences of multiple blackout events. In an effort to enable the development of green and smart social infrastructure, this paper introduces a design for a sustainable and efficient transportation
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The need for reduction in power consumption for public facilities has increased after the occurrences of multiple blackout events. In an effort to enable the development of green and smart social infrastructure, this paper introduces a design for a sustainable and efficient transportation system (SETS). For this design, renewable power sources and efficient electric drives are considered to be crucial technologies. Considering the subway station as an illustrative example, a power system design that uses wind and solar energy as major power sources is studied. The adjustable speed electric drive system that uses synchronous reluctance machines for ventilation systems contributes to increasing the overall power consumption efficiency. The effectiveness of the proposed SETS system is verified through a set of various field measurement data and simulation results. While the verification results demonstrate that operation of SETS is enabled by effective integration of renewable sources and efficient ventilation systems, future research directions have also been identified. Full article
(This article belongs to the Special Issue Symmetry in Systems Design and Analysis)
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Open AccessArticle Comprehensive Reputation-Based Security Mechanism against Dynamic SSDF Attack in Cognitive Radio Networks
Symmetry 2016, 8(12), 147; doi:10.3390/sym8120147
Received: 8 November 2016 / Revised: 30 November 2016 / Accepted: 30 November 2016 / Published: 3 December 2016
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Abstract
Collaborative spectrum sensing (CSS) was envisioned to improve the reliability of spectrum sensing in centralized cognitive radio networks (CRNs). However, secondary users (SUs)’ changeable environment and ease of compromise make CSS vulnerable to security threats, which further mislead the global decision making and
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Collaborative spectrum sensing (CSS) was envisioned to improve the reliability of spectrum sensing in centralized cognitive radio networks (CRNs). However, secondary users (SUs)’ changeable environment and ease of compromise make CSS vulnerable to security threats, which further mislead the global decision making and degrade the overall performance. A popular attack in CSS is the called spectrum sensing data falsification (SSDF) attack. In the SSDF attack, malicious cognitive users (MUs) send false sensing results to the fusion center, which significantly degrades detection accuracy. In this paper, a comprehensive reputation-based security mechanism against dynamic SSDF attack for CRNs is proposed. In the mechanism, the reliability of SUs in collaborative sensing is measured with comprehensive reputation values in accordance with the SUs’ current and historical sensing behaviors. Meanwhile a punishment strategy is presented to revise the reputation, in which a reward factor and a penalty factor are introduced to encourage SUs to engage in positive and honest sensing activities. The whole mechanism focuses on ensuring the correctness of the global decision continuously. Specifically, the proposed security scheme can effectively alleviate the effect of users’ malicious behaviors on network decision making, which contributes greatly to enhancing the fairness and robustness of CRNs. Considering that the attack strategy adopted by MUs has been gradually transforming from simplicity, fixedness and singleness into complexity, dynamic and crypticity, we introduce two dynamic behavior patterns (true to false and then to true (TFT) and false to true and then to false (FTF)) to further validate the effectiveness of our proposed defense mechanism. Abundant simulation results verify the rationality and validity of our proposed mechanism. Full article
(This article belongs to the Special Issue Symmetry in Complex Networks II)
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Open AccessArticle EMG Pattern Classification by Split and Merge Deep Belief Network
Symmetry 2016, 8(12), 148; doi:10.3390/sym8120148
Received: 18 April 2016 / Revised: 21 November 2016 / Accepted: 1 December 2016 / Published: 6 December 2016
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Abstract
In this paper; we introduce an enhanced electromyography (EMG) pattern recognition algorithm based on a split-and-merge deep belief network (SM-DBN). Generally, it is difficult to classify the EMG features because the EMG signal has nonlinear and time-varying characteristics. Therefore, various machine-learning methods have
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In this paper; we introduce an enhanced electromyography (EMG) pattern recognition algorithm based on a split-and-merge deep belief network (SM-DBN). Generally, it is difficult to classify the EMG features because the EMG signal has nonlinear and time-varying characteristics. Therefore, various machine-learning methods have been applied in several previously published studies. A DBN is a fast greedy learning algorithm that can identify a fairly good set of weights rapidly—even in deep networks with a large number of parameters and many hidden layers. To reduce overfitting and to enhance performance, the adopted optimization method was based on genetic algorithms (GA). As a result, the performance of the SM-DBN was 12.06% higher than conventional DBN. Additionally, SM-DBN results in a short convergence time, thereby reducing the training epoch. It is thus efficient in reducing the risk of overfitting. It is verified that the optimization was improved using GA. Full article
(This article belongs to the Special Issue Symmetry in Systems Design and Analysis)
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Open AccessArticle M-Polynomial and Degree-Based Topological Indices of Polyhex Nanotubes
Symmetry 2016, 8(12), 149; doi:10.3390/sym8120149
Received: 13 October 2016 / Revised: 4 November 2016 / Accepted: 1 December 2016 / Published: 6 December 2016
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Abstract
The discovery of new nanomaterials adds new dimensions to industry, electronics, and pharmaceutical and biological therapeutics. In this article, we first find closed forms of M-polynomials of polyhex nanotubes. We also compute closed forms of various degree-based topological indices of these tubes. These
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The discovery of new nanomaterials adds new dimensions to industry, electronics, and pharmaceutical and biological therapeutics. In this article, we first find closed forms of M-polynomials of polyhex nanotubes. We also compute closed forms of various degree-based topological indices of these tubes. These indices are numerical tendencies that often depict quantitative structural activity/property/toxicity relationships and correlate certain physico-chemical properties, such as boiling point, stability, and strain energy, of respective nanomaterial. To conclude, we plot surfaces associated to M-polynomials and characterize some facts about these tubes. Full article
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Open AccessArticle Morphometric Asymmetry of Frustule Outlines in the Pennate Diatom Luticola poulickovae (Bacillariophyceae)
Symmetry 2016, 8(12), 150; doi:10.3390/sym8120150
Received: 20 September 2016 / Revised: 25 November 2016 / Accepted: 30 November 2016 / Published: 7 December 2016
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Abstract
Side orientation of cells is usually ambiguous in unicellular organisms, making it impossible to separate components of directional asymmetry (DA) and fluctuating asymmetry (FA). However, frustules of the diatom Luticola poulickovae have biradially symmetric outlines, and their central areas bear ornamentation that is
[...] Read more.
Side orientation of cells is usually ambiguous in unicellular organisms, making it impossible to separate components of directional asymmetry (DA) and fluctuating asymmetry (FA). However, frustules of the diatom Luticola poulickovae have biradially symmetric outlines, and their central areas bear ornamentation that is asymmetric across the apical axis. The goal of this study was to explore differentiation of morphometric asymmetry across the apical axis into DA and FA components. Is there detectable DA of the valve outlines of two L. poulickovae strains that may be related to the asymmetric central areas? Given that the life cycle of diatoms involves cell-size diminution, and cell shape is strongly affected by allometry, we also explored the question of whether asymmetry is correlated with cell size. The extent of symmetric variation among individuals in each strain, as well as DA and FA across the apical axis, were quantified using two Procrustes ANOVA models. The results revealed no correlation of either total asymmetry or FA with valve size. DA was significant and considerably more pronounced than FA in both strains, indicating that there is previously unknown systematic asymmetry of valve outlines of L. poulickovae, which may be related to the asymmetry of its central area. Full article
(This article belongs to the Special Issue Fluctuating Asymmetry 2016)
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Open AccessArticle An Improved User Association Algorithm for MAP–FAPs Heterogeneous Networks
Symmetry 2016, 8(12), 151; doi:10.3390/sym8120151
Received: 1 November 2016 / Revised: 1 December 2016 / Accepted: 7 December 2016 / Published: 10 December 2016
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Abstract
Heterogeneous networks (HetNets) give users the opportunity to access different access points(APs), which will simultaneously affect user performance and system performance, so user association in HetNets plays a critical role in enhancing the load balancing and the system sum-throughput of networks. Meanwhile, the
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Heterogeneous networks (HetNets) give users the opportunity to access different access points(APs), which will simultaneously affect user performance and system performance, so user association in HetNets plays a critical role in enhancing the load balancing and the system sum-throughput of networks. Meanwhile, the incremental sum-throughput currently fails to meet the escalating data demands. Besides, ensuring fairness amongst users constitutes another urgent issue in the radio resource management (RRM) of HetNets. What is more, few works consider the maximum service user number constraint in femtocell access points (FAPs). To solve the aforementioned problem, this paper associates users to APs by considering system sum-throughput and fairness at the same time in HetNets under a maximum service user number constraint of FAPs; accordingly, the user association problem is formulated. By releasing constraint, the optimal user association algorithm is obtained by Lagrangian function, and based on this optimal solution, a low complexity suboptimal user association algorithm is proposed. At last, this paper investigates the relationship between system sum-throughput and maximum service user number of FAPs. Numerical simulation results show that the proposed algorithm can improve sum-throughput and fairness at the same time at a specific maximum service user number of FAPs. Full article
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Open AccessArticle Continuous Learning Graphical Knowledge Unit for Cluster Identification in High Density Data Sets
Symmetry 2016, 8(12), 152; doi:10.3390/sym8120152
Received: 8 June 2016 / Revised: 7 November 2016 / Accepted: 5 December 2016 / Published: 14 December 2016
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Abstract
Big data are visually cluttered by overlapping data points. Rather than removing, reducing or reformulating overlap, we propose a simple, effective and powerful technique for density cluster generation and visualization, where point marker (graphical symbol of a data point) overlap is exploited in
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Big data are visually cluttered by overlapping data points. Rather than removing, reducing or reformulating overlap, we propose a simple, effective and powerful technique for density cluster generation and visualization, where point marker (graphical symbol of a data point) overlap is exploited in an additive fashion in order to obtain bitmap data summaries in which clusters can be identified visually, aided by automatically generated contour lines. In the proposed method, the plotting area is a bitmap and the marker is a shape of more than one pixel. As the markers overlap, the red, green and blue (RGB) colour values of pixels in the shared region are added. Thus, a pixel of a 24-bit RGB bitmap can code up to 224 (over 1.6 million) overlaps. A higher number of overlaps at the same location makes the colour of this area identical, which can be identified by the naked eye. A bitmap is a matrix of colour values that can be represented as integers. The proposed method updates this matrix while adding new points. Thus, this matrix can be considered as an up-to-time knowledge unit of processed data. Results show cluster generation, cluster identification, missing and out-of-range data visualization, and outlier detection capability of the newly proposed method. Full article
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)
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Open AccessArticle Noether Symmetries Quantization and Superintegrability of Biological Models
Symmetry 2016, 8(12), 155; doi:10.3390/sym8120155
Received: 17 October 2016 / Revised: 2 December 2016 / Accepted: 12 December 2016 / Published: 20 December 2016
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Abstract
It is shown that quantization and superintegrability are not concepts that are inherent to classical Physics alone. Indeed, one may quantize and also detect superintegrability of biological models by means of Noether symmetries. We exemplify the method by using a mathematical model that
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It is shown that quantization and superintegrability are not concepts that are inherent to classical Physics alone. Indeed, one may quantize and also detect superintegrability of biological models by means of Noether symmetries. We exemplify the method by using a mathematical model that was proposed by Basener and Ross (2005), and that describes the dynamics of growth and sudden decrease in the population of Easter Island. Full article
Open AccessArticle THD Reduction of Distribution System Based on ASRFC and HVC Method for SVC under EV Charger Condition for Power Factor Improvement
Symmetry 2016, 8(12), 156; doi:10.3390/sym8120156
Received: 31 October 2016 / Revised: 12 December 2016 / Accepted: 13 December 2016 / Published: 20 December 2016
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Abstract
Electric vehicles (EVs) have been gaining popularity in recent years due to growing concerns about fuel depletion and increasing petrol prices. Random uncoordinated charging of multiple EVs at residential distribution feeders with moderate penetration levels is expected in the near future. This paper
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Electric vehicles (EVs) have been gaining popularity in recent years due to growing concerns about fuel depletion and increasing petrol prices. Random uncoordinated charging of multiple EVs at residential distribution feeders with moderate penetration levels is expected in the near future. This paper describes a high performance voltage controller for the EVs charging system, and proposes a scheme of asymmetric synchronous reference frame controller (ASRFC) in order to compensate for the voltage distortions and unbalance distribution system due to EVs charger. This paper explores the power factor of distribution and residential network under random EVs charger on the bus load. ASRFC and harmonic voltage compensator (HVC) are employed for static VAR compensator (SVC) in this paper. The proposed scheme can improve the power factor and total harmonic distortion (THD) of the smart grid due to the EVs charger in grid. The effectiveness of the scheme was investigated and verified through computer simulations of a 22.9-kV grid. Full article
(This article belongs to the Special Issue Symmetry in Systems Design and Analysis)
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Open AccessArticle The Method of Linear Determining Equations to Evolution System and Application for Reaction-Diffusion System with Power Diffusivities
Symmetry 2016, 8(12), 157; doi:10.3390/sym8120157
Received: 6 September 2016 / Revised: 11 December 2016 / Accepted: 13 December 2016 / Published: 20 December 2016
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Abstract
The method of linear determining equations is constructed to study conditional Lie–Bäcklund symmetry and the differential constraint of a two-component second-order evolution system, which generalize the determining equations used in the search for classical Lie symmetry. As an application of the approach, the
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The method of linear determining equations is constructed to study conditional Lie–Bäcklund symmetry and the differential constraint of a two-component second-order evolution system, which generalize the determining equations used in the search for classical Lie symmetry. As an application of the approach, the two-component reaction-diffusion system with power diffusivities is considered. The conditional Lie–Bäcklund symmetries and differential constraints admitted by the reaction-diffusion system are identified. Consequently, the reductions of the resulting system are established due to the compatibility of the corresponding invariant surface conditions and the original system. Full article
Open AccessArticle Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach
Symmetry 2016, 8(12), 159; doi:10.3390/sym8120159
Received: 23 August 2016 / Revised: 26 November 2016 / Accepted: 12 December 2016 / Published: 21 December 2016
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Abstract
This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach into the segmentation-based framework. Firstly, the reference image is segmented
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This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach into the segmentation-based framework. Firstly, the reference image is segmented by using the mean-shift algorithm. Secondly, the initial disparity of each segment is estimated by an adaptive multi-cost method, which consists of a novel multi-cost function and an adaptive support window cost aggregation strategy. The multi-cost function increases the robustness of the initial raw matching costs calculation and the adaptive window reduces the matching ambiguity effectively. Thirdly, an iterative outlier suppression and disparity plane parameters fitting algorithm is designed to estimate the disparity plane parameters. Lastly, an energy function is formulated in segment domain, and the optimal plane label is approximated by belief propagation. The experimental results with the Middlebury stereo datasets, along with synthesized and real-world stereo images, demonstrate the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Symmetry in Complex Networks II)
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Review

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Open AccessReview Fluctuating Asymmetry of Human Populations: A Review
Symmetry 2016, 8(12), 154; doi:10.3390/sym8120154
Received: 23 September 2016 / Revised: 14 November 2016 / Accepted: 12 December 2016 / Published: 16 December 2016
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Abstract
Fluctuating asymmetry, the random deviation from perfect symmetry, is a widely used population-level index of developmental instability, developmental noise, and robustness. It reflects a population’s state of adaptation and genomic coadaptation. Here, we review the literature on fluctuating asymmetry of human populations. The
[...] Read more.
Fluctuating asymmetry, the random deviation from perfect symmetry, is a widely used population-level index of developmental instability, developmental noise, and robustness. It reflects a population’s state of adaptation and genomic coadaptation. Here, we review the literature on fluctuating asymmetry of human populations. The most widely used bilateral traits include skeletal, dental, and facial dimensions; dermatoglyphic patterns and ridge counts; and facial shape. Each trait has its advantages and disadvantages, but results are most robust when multiple traits are combined into a composite index of fluctuating asymmetry (CFA). Both environmental (diet, climate, toxins) and genetic (aneuploidy, heterozygosity, inbreeding) stressors have been linked to population-level variation in fluctuating asymmetry. In general, these stressors increase average fluctuating asymmetry. Nevertheless, there have been many conflicting results, in part because (1) fluctuating asymmetry is a weak signal in a sea of noise; and (2) studies of human fluctuating asymmetry have not always followed best practices. The most serious concerns are insensitive asymmetry indices (correlation coefficient and coefficient of indetermination), inappropriate size scaling, unrecognized mixture distributions, inappropriate corrections for directional asymmetry, failure to use composite indices, and inattention to measurement error. Consequently, it is often difficult (or impossible) to compare results across traits, and across studies. Full article
(This article belongs to the Special Issue Fluctuating Asymmetry 2016)
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Other

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Open AccessComment A Modification on the Hesitant Fuzzy Set Lexicographical Ranking Method
Symmetry 2016, 8(12), 153; doi:10.3390/sym8120153
Received: 10 November 2016 / Revised: 27 November 2016 / Accepted: 5 December 2016 / Published: 14 December 2016
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Abstract
Recently, a novel hesitant fuzzy set (HFS) ranking technique based on the idea of lexicographical ordering is proposed and an example is presented to demonstrate that the proposed ranking method is invariant with multiple occurrences of any element of a hesitant fuzzy element
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Recently, a novel hesitant fuzzy set (HFS) ranking technique based on the idea of lexicographical ordering is proposed and an example is presented to demonstrate that the proposed ranking method is invariant with multiple occurrences of any element of a hesitant fuzzy element (HFE). In this paper, we show by examples that the HFS lexicographical ordering method is sometimes invalid, and a modified ranking method is presented. In comparison with the HFS lexicographical ordering method, the modified ranking method is more reasonable in more general cases. Full article

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symmetry@mdpi.com
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18
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