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Symmetry, Volume 9, Issue 4 (April 2017)

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Cover Story We tested if developmental instability (DI), measured through limb bone asymmetry, increased with [...] Read more.
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Research

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Open AccessArticle Enhanced Joint and Separable Reversible Data Hiding in Encrypted Images with High Payload
Symmetry 2017, 9(4), 50; doi:10.3390/sym9040050
Received: 14 February 2017 / Revised: 10 March 2017 / Accepted: 23 March 2017 / Published: 28 March 2017
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Abstract
Recently, much attention has been paid to reversible data hiding (RDH) in encrypted images, since it preserves the data that the original image can be perfectly recovered after data extraction while protecting the confidentiality of image content. In this paper, we propose joint
[...] Read more.
Recently, much attention has been paid to reversible data hiding (RDH) in encrypted images, since it preserves the data that the original image can be perfectly recovered after data extraction while protecting the confidentiality of image content. In this paper, we propose joint and separable RDH techniques using an improved embedding pattern and a new measurement function in encrypted images with a high payload. The first problem in recent joint data hiding is that the encrypted image is divided into blocks, and the spatial correlation in the block cannot fully reflect the smoothness of a natural image. The second problem is that half embedding is used to embed data and the prediction error is exploited to calculate the smoothness, which also fails to give good performance. To solve these problems, we divide the encrypted image into four sets, instead of blocks; the actual value of pixels is considered, rather than an estimated value, and the absolute difference between neighboring pixels is used in preference to prediction error to calculate the smoothness. Therefore, it is possible to use spatial correlation of the natural image perfectly. The experimental results show that the proposed joint and separable methods offer better performance over other works. Full article
(This article belongs to the Special Issue Symmetry in Secure Cyber World)
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Open AccessArticle Developmental Origins of Limb Developmental Instability in Human Fetuses: Many Abnormalities Make the Difference
Symmetry 2017, 9(4), 51; doi:10.3390/sym9040051
Received: 16 February 2017 / Revised: 20 March 2017 / Accepted: 23 March 2017 / Published: 28 March 2017
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Abstract
Fluctuating asymmetry (FA) is the small random deviation from perfect symmetry in bilateral traits and is often used to assess developmental instability (DI) experienced by organisms. In this study, with a unique dataset of 1389 deceased human fetuses, we investigated the relationship between
[...] Read more.
Fluctuating asymmetry (FA) is the small random deviation from perfect symmetry in bilateral traits and is often used to assess developmental instability (DI) experienced by organisms. In this study, with a unique dataset of 1389 deceased human fetuses, we investigated the relationship between abnormal development and human limb FA in different ways, using a more fundamental approach than usually done. We studied whether there is an underlying developmental basis of DI, as measured by FA, by investigating, first, whether limb FA can be attributed to developmental abnormalities associated with specific organ systems, germ layers or patterning processes, and second, whether limb FA increases with increasing number of developmental abnormalities either gradually, or in a threshold-like fashion. Limb FA was found to increase in fetuses with cardiovascular and nervous system abnormalities. Fetuses with ectoderm-derived abnormalities were also found to have significantly higher limb FA, but no other germ layers were found to be associated. We found no significant correlation between specific developmental processes, such as neural crest development, segmentation, midline and left-right patterning and limb FA. Although only some congenital abnormalities were correlated with limb FA, our results do suggest that limb FA increases when an increasing number of organ systems, germ layers or developmental pathways are disrupted. Therefore, we conclude that limb FA is mainly a good indicator for DI in the case of particularly severe perturbations of development and that FA does not reflect the subtler deviations from developmental stability. Full article
(This article belongs to the Special Issue Symmetry in Human Evolutionary Biology)
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Open AccessArticle Dual Hesitant Fuzzy Probability
Symmetry 2017, 9(4), 52; doi:10.3390/sym9040052
Received: 3 January 2017 / Revised: 30 March 2017 / Accepted: 1 April 2017 / Published: 7 April 2017
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Abstract
Intuitionistic fuzzy probabilities are an extension of the concept of probabilities with application in several practical problem solving tasks. The former are probabilities represented through intuitionistic fuzzy numbers, to indicate the uncertainty of the membership and nonmembership degrees in the value assigned to
[...] Read more.
Intuitionistic fuzzy probabilities are an extension of the concept of probabilities with application in several practical problem solving tasks. The former are probabilities represented through intuitionistic fuzzy numbers, to indicate the uncertainty of the membership and nonmembership degrees in the value assigned to probabilities. Moreover, a dual hesitant fuzzy set (DHFS) is an extension of an intuitionistic fuzzy set, and its membership degrees and nonmembership degrees are represented by two sets of possible values; this new theory of fuzzy sets is known today as dual hesitant fuzzy set theory. This work will extend the notion of dual hesitant fuzzy probabilities by representing probabilities through the dual hesitant fuzzy numbers, in the sense of Zhu et al., instead of intuitionistic fuzzy numbers. We also give the concept of dual hesitant fuzzy probability, based on which we provide some main results including the properties of dual hesitant fuzzy probability, dual hesitant fuzzy conditional probability, and dual hesitant fuzzy total probability. Full article
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Open AccessArticle Ear Detection under Uncontrolled Conditions with Multiple Scale Faster Region-Based Convolutional Neural Networks
Symmetry 2017, 9(4), 53; doi:10.3390/sym9040053
Received: 24 January 2017 / Revised: 4 April 2017 / Accepted: 4 April 2017 / Published: 10 April 2017
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Abstract
Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion, and imaging conditions provide a great challenge to the traditional
[...] Read more.
Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion, and imaging conditions provide a great challenge to the traditional ear detection methods under uncontrolled conditions. This paper proposes an efficient technique involving Multiple Scale Faster Region-based Convolutional Neural Networks (Faster R-CNN) to detect ears from 2D profile images in natural images automatically. Firstly, three regions of different scales are detected to infer the information about the ear location context within the image. Then an ear region filtering approach is proposed to extract the correct ear region and eliminate the false positives automatically. In an experiment with a test set of 200 web images (with variable photographic conditions), 98% of ears were accurately detected. Experiments were likewise conducted on the Collection J2 of University of Notre Dame Biometrics Database (UND-J2) and University of Beira Interior Ear dataset (UBEAR), which contain large occlusion, scale, and pose variations. Detection rates of 100% and 98.22%, respectively, demonstrate the effectiveness of the proposed approach. Full article
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Open AccessArticle An Efficient VQ Codebook Search Algorithm Applied to AMR-WB Speech Coding
Symmetry 2017, 9(4), 54; doi:10.3390/sym9040054
Received: 6 March 2017 / Revised: 5 April 2017 / Accepted: 10 April 2017 / Published: 12 April 2017
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Abstract
The adaptive multi-rate wideband (AMR-WB) speech codec is widely used in modern mobile communication systems for high speech quality in handheld devices. Nonetheless, a major disadvantage is that vector quantization (VQ) of immittance spectral frequency (ISF) coefficients takes a considerable computational load in
[...] Read more.
The adaptive multi-rate wideband (AMR-WB) speech codec is widely used in modern mobile communication systems for high speech quality in handheld devices. Nonetheless, a major disadvantage is that vector quantization (VQ) of immittance spectral frequency (ISF) coefficients takes a considerable computational load in the AMR-WB coding. Accordingly, a binary search space-structured VQ (BSS-VQ) algorithm is adopted to efficiently reduce the complexity of ISF quantization in AMR-WB. This search algorithm is done through a fast locating technique combined with lookup tables, such that an input vector is efficiently assigned to a subspace where relatively few codeword searches are required to be executed. In terms of overall search performance, this work is experimentally validated as a superior search algorithm relative to a multiple triangular inequality elimination (MTIE), a TIE with dynamic and intersection mechanisms (DI-TIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for overall search load comparison, this work provides an 87% search load reduction at a threshold of quantization accuracy of 0.96, a figure far beyond 55% in the MTIE, 76% in the EEENNS approach, and 83% in the DI-TIE approach. Full article
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Open AccessArticle 3D Reconstruction Framework for Multiple Remote Robots on Cloud System
Symmetry 2017, 9(4), 55; doi:10.3390/sym9040055
Received: 13 December 2016 / Revised: 7 April 2017 / Accepted: 7 April 2017 / Published: 14 April 2017
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Abstract
This paper proposes a cloud-based framework that optimizes the three-dimensional (3D) reconstruction of multiple types of sensor data captured from multiple remote robots. A working environment using multiple remote robots requires massive amounts of data processing in real-time, which cannot be achieved using
[...] Read more.
This paper proposes a cloud-based framework that optimizes the three-dimensional (3D) reconstruction of multiple types of sensor data captured from multiple remote robots. A working environment using multiple remote robots requires massive amounts of data processing in real-time, which cannot be achieved using a single computer. In the proposed framework, reconstruction is carried out in cloud-based servers via distributed data processing. Consequently, users do not need to consider computing resources even when utilizing multiple remote robots. The sensors’ bulk data are transferred to a master server that divides the data and allocates the processing to a set of slave servers. Thus, the segmentation and reconstruction tasks are implemented in the slave servers. The reconstructed 3D space is created by fusing all the results in a visualization server, and the results are saved in a database that users can access and visualize in real-time. The results of the experiments conducted verify that the proposed system is capable of providing real-time 3D scenes of the surroundings of remote robots. Full article
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)
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Open AccessArticle Interactive Blow and Burst of Giant Soap Bubbles
Symmetry 2017, 9(4), 56; doi:10.3390/sym9040056
Received: 16 December 2016 / Revised: 10 April 2017 / Accepted: 11 April 2017 / Published: 14 April 2017
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Abstract
Previous studies on virtual soap bubbles mainly focused on methods for visualizing the physical and geometrical properties of soap bubbles and paid little attention to the possible ways to enhance the interaction between the simulation and the user. In this paper, a user
[...] Read more.
Previous studies on virtual soap bubbles mainly focused on methods for visualizing the physical and geometrical properties of soap bubbles and paid little attention to the possible ways to enhance the interaction between the simulation and the user. In this paper, a user interaction-based giant soap bubble simulation system is proposed in which the free-form shape, size, and position of giant soap bubbles are determined by the user’s hand motions. Our method improves the controllability of soap bubble simulation by correcting the jerky hand trajectory and hand velocity to a smooth and gradual path. Our air flow transfer algorithm can produce detailed deformation and standing wave for soap film in real time. Our novel soap film bursting algorithm represents the process of the bursting phenomenon of soap-film and giant soap bubbles in a unified framework. The results of our experiment demonstrate that the system allows the user to experience the giant soap bubble blowing and bursting process in a virtual environment. Full article
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Open AccessArticle Correlation Coefficients of Extended Hesitant Fuzzy Sets and Their Applications to Decision Making
Symmetry 2017, 9(4), 47; doi:10.3390/sym9040047
Received: 19 December 2016 / Revised: 10 March 2017 / Accepted: 22 March 2017 / Published: 29 March 2017
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Abstract
Extended hesitant fuzzy sets (EHFSs), which allow the membership degree of an element to a set represented by several possible value-groups, can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we derive some
[...] Read more.
Extended hesitant fuzzy sets (EHFSs), which allow the membership degree of an element to a set represented by several possible value-groups, can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we derive some correlation coefficients between EHFSs, which contain two cases, the correlation coefficients taking into account the length of extended hesitant fuzzy elements (EHFEs) and the correlation coefficients without taking into account the length of EHFEs, as a new extension of existing correlation coefficients for hesitant fuzzy sets (HFSs) and apply them to decision making under extended hesitant fuzzy environments. A real-world example based on the energy policy problem is employed to illustrate the actual need for dealing with the difference of evaluation information provided by different experts without information loss in decision making processes. Full article
Open AccessArticle A Fast K-prototypes Algorithm Using Partial Distance Computation
Symmetry 2017, 9(4), 58; doi:10.3390/sym9040058
Received: 6 April 2017 / Revised: 17 April 2017 / Accepted: 18 April 2017 / Published: 21 April 2017
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Abstract
The k-means is one of the most popular and widely used clustering algorithm; however, it is limited to numerical data only. The k-prototypes algorithm is an algorithm famous for dealing with both numerical and categorical data. However, there have been no studies to
[...] Read more.
The k-means is one of the most popular and widely used clustering algorithm; however, it is limited to numerical data only. The k-prototypes algorithm is an algorithm famous for dealing with both numerical and categorical data. However, there have been no studies to accelerate it. In this paper, we propose a new, fast k-prototypes algorithm that provides the same answers as those of the original k-prototypes algorithm. The proposed algorithm avoids distance computations using partial distance computation. Our k-prototypes algorithm finds minimum distance without distance computations of all attributes between an object and a cluster center, which allows it to reduce time complexity. A partial distance computation uses a fact that a value of the maximum difference between two categorical attributes is 1 during distance computations. If data objects have m categorical attributes, the maximum difference of categorical attributes between an object and a cluster center is m. Our algorithm first computes distance with numerical attributes only. If a difference of the minimum distance and the second smallest with numerical attributes is higher than m, we can find the minimum distance between an object and a cluster center without distance computations of categorical attributes. The experimental results show that the computational performance of the proposed k-prototypes algorithm is superior to the original k-prototypes algorithm in our dataset. Full article
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)
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Open AccessArticle Nested One-to-One Symmetric Classification Method on a Fuzzy SVM for Moving Vehicles
Symmetry 2017, 9(4), 48; doi:10.3390/sym9040048
Received: 13 December 2016 / Revised: 20 March 2017 / Accepted: 23 March 2017 / Published: 26 March 2017
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Abstract
As a multi-classification problem, classification of moving vehicles has been studied by different statistical methods. These practical applications have various requirements, efficiencies, and performance, such as the size of training sample sets, convergence rate, and inseparable or ambiguous classification issues. With a reduction
[...] Read more.
As a multi-classification problem, classification of moving vehicles has been studied by different statistical methods. These practical applications have various requirements, efficiencies, and performance, such as the size of training sample sets, convergence rate, and inseparable or ambiguous classification issues. With a reduction in its training time,the one-to-many support vector machine (SVM) method has an advantage over the standard SVM method by directly converting the binary classification problem into two multi-classification problems with short time and fast speed. When the number of training samples of a certain type is far less than the total number of samples, the accuracy of training, however, will be significantlydecreased,leading to theproblem of inseparable area. In this paper, the proposed nested one-to-one symmetric classification method on a fuzzy SVM symmetrically transforms the C multi-classification problems into the C(C-1)/2 binary classification problems with C(C-1)/2 classifiers, and solves the problem of inseparable area. According to the best combination factor of kernel function (γ, C) for the radial basis function (RBF) in the comparative experiments of training sample sets among the different algorithms, and the experimental results of many different training sample sets and test samples, the nested one-to-one symmetric classification algorithm on a fuzzy SVM for moving vehicle is able to obtain the best accuracy of recognition. Full article
(This article belongs to the Special Issue Symmetry in Cooperative Applications II)
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Open AccessArticle Collaborative CAD Synchronization Based on a Symmetric and Consistent Modeling Procedure
Symmetry 2017, 9(4), 59; doi:10.3390/sym9040059
Received: 4 March 2017 / Revised: 11 April 2017 / Accepted: 18 April 2017 / Published: 23 April 2017
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Abstract
One basic issue with collaborative computer aided design (Co-CAD) is how to maintain valid and consistent modeling results across all design sites. Moreover, modeling history is important in parametric CAD modeling. Therefore, different from a typical co-editing approach, this paper proposes a novel
[...] Read more.
One basic issue with collaborative computer aided design (Co-CAD) is how to maintain valid and consistent modeling results across all design sites. Moreover, modeling history is important in parametric CAD modeling. Therefore, different from a typical co-editing approach, this paper proposes a novel method for Co-CAD synchronization, in which all Co-CAD sites maintain symmetric and consistent operating procedures. Consequently, the consistency of both modeling results and history can be achieved. In order to generate a valid, unique, and symmetric queue among collaborative sites, a set of correlated mechanisms is presented in this paper. Firstly, the causal relationship of operations is maintained. Secondly, the operation queue is reconstructed for partial concurrency operation, and the concurrent operation can be retrieved. Thirdly, a symmetric, concurrent operation control strategy is proposed to determine the order of operations and resolve possible conflicts. Compared with existing Co-CAD consistency methods, the proposed method is convenient and flexible in supporting collaborative design. The experiment performed based on the collaborative modeling procedure demonstrates the correctness and applicability of this work. Full article
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Review

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Open AccessReview A Matter of Degree: Strength of Brain Asymmetry and Behaviour
Symmetry 2017, 9(4), 57; doi:10.3390/sym9040057
Received: 29 March 2017 / Revised: 11 April 2017 / Accepted: 11 April 2017 / Published: 18 April 2017
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Abstract
Research on a growing number of vertebrate species has shown that the left and right sides of the brain process information in different ways and that lateralized brain function is expressed in both specific and broad aspects of behaviour. This paper reviews the
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Research on a growing number of vertebrate species has shown that the left and right sides of the brain process information in different ways and that lateralized brain function is expressed in both specific and broad aspects of behaviour. This paper reviews the available evidence relating strength of lateralization to behavioural/cognitive performance. It begins by considering the relationship between limb preference and behaviour in humans and primates from the perspectives of direction and strength of lateralization. In birds, eye preference is used as a reflection of brain asymmetry and the strength of this asymmetry is associated with behaviour important for survival (e.g., visual discrimination of food from non-food and performance of two tasks in parallel). The same applies to studies on aquatic species, mainly fish but also tadpoles, in which strength of lateralization has been assessed as eye preferences or turning biases. Overall, the empirical evidence across vertebrate species points to the conclusion that stronger lateralization is advantageous in a wide range of contexts. Brief discussion of interhemispheric communication follows together with discussion of experiments that examined the effects of sectioning pathways connecting the left and right sides of the brain, or of preventing the development of these left-right connections. The conclusion reached is that degree of functional lateralization affects behaviour in quite similar ways across vertebrate species. Although the direction of lateralization is also important, in many situations strength of lateralization matters more. Finally, possible interactions between asymmetry in different sensory modalities is considered. Full article
(This article belongs to the Special Issue Brain Asymmetry of Structure and/or Function)
Open AccessReview Methods and Tools of Digital Triage in Forensic Context: Survey and Future Directions
Symmetry 2017, 9(4), 49; doi:10.3390/sym9040049
Received: 7 February 2017 / Revised: 22 March 2017 / Accepted: 22 March 2017 / Published: 28 March 2017
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Abstract
Digital triage is the first investigative step of the forensic examination. The digital triage comes in two forms, live triage and post-mortem triage. The primary goal of the live triage is a rapid extraction of an intelligence from the potential sources. The live
[...] Read more.
Digital triage is the first investigative step of the forensic examination. The digital triage comes in two forms, live triage and post-mortem triage. The primary goal of the live triage is a rapid extraction of an intelligence from the potential sources. The live triage raises legitimate concerns. The post-mortem triage is conducted in the laboratory and its main goal is ranking of the seized devices for the possible existence of the relevant evidence. The digital triage has the potential to quickly identify items that are likely to contain the evidential data. Therefore, it is a solution to the problem of case backlogs. However, existing methods and tools of the digital triage have limitations, especially, in the forensic context. Nevertheless, we have no better solution for the time being. In this paper, we critically review published research works and the proposed solutions for digital triage. The review is divided into four sections as follows: live triage, post-mortem triage, mobile device triage, and triage tools. We conclude that many challenges are awaiting for the developers in creating methods and tools of digital triage in order to keep pace with the development of new technologies. Full article
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)

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