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Symmetry, Volume 10, Issue 1 (January 2018)

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Cover Story (view full-size image) The application of helicenes as chiral auxiliaries and as chirogenic systems for separation [...] Read more.
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Open AccessEditorial Graph Theory
Symmetry 2018, 10(1), 32; https://doi.org/10.3390/sym10010032
Received: 19 January 2018 / Revised: 19 January 2018 / Accepted: 19 January 2018 / Published: 22 January 2018
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Abstract
This book contains the successful invited submissions [1–10] to a special issue of Symmetry on the subject area of ‘graph theory’ [...]
Full article
(This article belongs to the Special Issue Graph Theory)
Open AccessArticle Gluing Formula for Casimir Energies
Symmetry 2018, 10(1), 31; https://doi.org/10.3390/sym10010031
Received: 27 December 2017 / Revised: 15 January 2018 / Accepted: 18 January 2018 / Published: 21 January 2018
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Abstract
We provide a completely new perspective for the analysis of Casimir forces in very general piston configurations. To this end, in order to be self-contained, we prove a “gluing formula” well known in mathematics and relate it with Casimir forces in piston configurations.
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We provide a completely new perspective for the analysis of Casimir forces in very general piston configurations. To this end, in order to be self-contained, we prove a “gluing formula” well known in mathematics and relate it with Casimir forces in piston configurations. At the center of our description is the Dirichlet-to-Neumann operator, which encodes all the information about those forces. As an application, the results for previously considered piston configurations are reproduced in a streamlined fashion. Full article
(This article belongs to the Special Issue Casimir Physics and Applications)
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Open AccessArticle A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments
Symmetry 2018, 10(1), 30; https://doi.org/10.3390/sym10010030
Received: 15 November 2017 / Revised: 13 January 2018 / Accepted: 15 January 2018 / Published: 17 January 2018
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Abstract
Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should
[...] Read more.
Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions. Full article
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Open AccessArticle How Symmetric Are Real-World Graphs? A Large-Scale Study
Symmetry 2018, 10(1), 29; https://doi.org/10.3390/sym10010029
Received: 22 December 2017 / Revised: 9 January 2018 / Accepted: 10 January 2018 / Published: 16 January 2018
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Abstract
The analysis of symmetry is a main principle in natural sciences, especially physics. For network sciences, for example, in social sciences, computer science and data science, only a few small-scale studies of the symmetry of complex real-world graphs exist. Graph symmetry is a
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The analysis of symmetry is a main principle in natural sciences, especially physics. For network sciences, for example, in social sciences, computer science and data science, only a few small-scale studies of the symmetry of complex real-world graphs exist. Graph symmetry is a topic rooted in mathematics and is not yet well-received and applied in practice. This article underlines the importance of analyzing symmetry by showing the existence of symmetry in real-world graphs. An analysis of over 1500 graph datasets from the meta-repository networkrepository.com is carried out and a normalized version of the “network redundancy” measure is presented. It quantifies graph symmetry in terms of the number of orbits of the symmetry group from zero (no symmetries) to one (completely symmetric), and improves the recognition of asymmetric graphs. Over 70% of the analyzed graphs contain symmetries (i.e., graph automorphisms), independent of size and modularity. Therefore, we conclude that real-world graphs are likely to contain symmetries. This contribution is the first larger-scale study of symmetry in graphs and it shows the necessity of handling symmetry in data analysis: The existence of symmetries in graphs is the cause of two problems in graph clustering we are aware of, namely, the existence of multiple equivalent solutions with the same value of the clustering criterion and, secondly, the inability of all standard partition-comparison measures of cluster analysis to identify automorphic partitions as equivalent. Full article
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Open AccessEditorial Acknowledgement to Reviewers of Symmetry in 2017
Symmetry 2018, 10(1), 28; https://doi.org/10.3390/sym10010028
Received: 12 January 2018 / Accepted: 12 January 2018 / Published: 12 January 2018
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Abstract
Peer review is an essential part in the publication process, ensuring that Symmetry maintains high quality standards for its published papers. In 2017, a total of 328 papers were published in the journal.[...] Full article
Open AccessArticle The Posterior Sustained Negativity Revisited—An SPN Reanalysis of Jacobsen and Höfel (2003)
Symmetry 2018, 10(1), 27; https://doi.org/10.3390/sym10010027
Received: 12 October 2017 / Revised: 21 December 2017 / Accepted: 10 January 2018 / Published: 12 January 2018
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Abstract
Symmetry is an important cue for the aesthetic judgment of beauty. Using a binary forced-choice format in a cued mixed design, Jacobsen and Höfel (2003) compared aesthetic judgments of beauty and symmetry judgments of novel graphic patterns. A late posterior sustained negativity elicited
[...] Read more.
Symmetry is an important cue for the aesthetic judgment of beauty. Using a binary forced-choice format in a cued mixed design, Jacobsen and Höfel (2003) compared aesthetic judgments of beauty and symmetry judgments of novel graphic patterns. A late posterior sustained negativity elicited by symmetric patterns was observed in the symmetry judgment condition, but not in the beauty judgement condition. Therefore, this negativity appeared to be mainly driven by the task.In a series of studies, Bertamini, Makin, and colleagues observed a comparable sustained posterior negativity (SPN) to symmetric stimuli, mainly taken to reflect obligatory symmetry processing independent of task requirements. We reanalyzed the data by Jacobsen and Höfel (2003) using similar parameters for data analysis as Bertamini, Makin, and colleagues to examine these apparent differences. The reanalysis confirmed both a task-driven effect on the posterior sustained negativity/SPN to symmetric patterns in the symmetry judgment condition and a strong symmetry-driven SPN to symmetric patterns. Differences between the references used for analyses of the electroencephalogram (EEG) had an effect. Based on the reanalysis, the Jacobsen and Höfel (2003) data also fit well with Bertamini’s, Makin’s, and colleagues’ account of obligatory symmetry processing. Full article
(This article belongs to the Special Issue Symmetry-Related Activity in Mid-Level Vision)
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Open AccessArticle The Variety of 7-Dimensional 2-Step Nilpotent Lie Algebras
Symmetry 2018, 10(1), 26; https://doi.org/10.3390/sym10010026
Received: 19 December 2017 / Revised: 2 January 2018 / Accepted: 6 January 2018 / Published: 11 January 2018
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Abstract
In this note, we consider degenerations between complex 2-step nilpotent Lie algebras of dimension 7 within the variety N72. This allows us to obtain the rigid algebras in N72, whose closures give the irreducible components of the
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In this note, we consider degenerations between complex 2-step nilpotent Lie algebras of dimension 7 within the variety N 7 2 . This allows us to obtain the rigid algebras in N 7 2 , whose closures give the irreducible components of the variety. Full article
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Open AccessFeature PaperArticle A Critical Note on Symmetry Contact Artifacts and the Evaluation of the Quality of Homology Models
Symmetry 2018, 10(1), 25; https://doi.org/10.3390/sym10010025
Received: 20 November 2017 / Revised: 2 January 2018 / Accepted: 2 January 2018 / Published: 11 January 2018
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Abstract
It is much easier to determine a protein’s sequence than to determine its three dimensional structure and consequently homology modeling will be an essential aspect of most studies that require 3D protein structure data. Homology modeling templates tend to be PDB files. About
[...] Read more.
It is much easier to determine a protein’s sequence than to determine its three dimensional structure and consequently homology modeling will be an essential aspect of most studies that require 3D protein structure data. Homology modeling templates tend to be PDB files. About 88% of all protein structures in the PDB have been determined with X-ray crystallography, and thus are based on crystals that by necessity hold non-natural packing contacts in accordance with the crystal symmetry. Active site residues, residues involved in intermolecular interactions, residues that get post-translationally modified, or other sites of interest, normally are located at the protein surface so that it is particularly important to correctly model surface-located residues. Unfortunately, surface residues are just those that suffer most from crystal packing artifacts. Our study of the influence of crystal packing artifacts on the quality of homology models reveals that this influence is much larger than generally assumed, and that the evaluation of the quality of homology models should properly account for these artifacts. Full article
(This article belongs to the Special Issue Structural Symmetry and Protein Function)
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Open AccessArticle Efficient Location of Resources in Cylindrical Networks
Symmetry 2018, 10(1), 24; https://doi.org/10.3390/sym10010024
Received: 4 December 2017 / Revised: 4 January 2018 / Accepted: 8 January 2018 / Published: 10 January 2018
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Abstract
The location of resources in a network satisfying some optimization property is a classical combinatorial problem that can be modeled and solved by using graphs. Key tools in this problem are the domination-type properties, which have been defined and widely studied in different
[...] Read more.
The location of resources in a network satisfying some optimization property is a classical combinatorial problem that can be modeled and solved by using graphs. Key tools in this problem are the domination-type properties, which have been defined and widely studied in different types of graph models, such as undirected and directed graphs, finite and infinite graphs, simple graphs and hypergraphs. When the required optimization property is that every node of the network must have access to exactly one node with the desired resource, the appropriate models are the efficient dominating sets. However, the existence of these vertex sets is not guaranteed in every graph, so relaxing some conditions is necessary to ensure the existence of some kind of dominating sets, as efficient as possible, in a larger number of graphs. In this paper, we study independent [ 1 , 2 ] -sets, a generalization of efficient dominating sets defined by Chellali et al., in the case of cylindrical networks. It is known that efficient dominating sets exist in very special cases of cylinders, but the particular symmetry of these graphs will allow us to provide regular patterns that guarantee the existence of independent [ 1 , 2 ] -sets in every cylinder, except in one single case, and to compute exact values of the optimal parameter, the independent [ 1 , 2 ] -number, in cylinders of selected sizes. Full article
(This article belongs to the Special Issue Graph Theory)
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Open AccessArticle Separable Reversible Data Hiding in Encrypted Signals with Public Key Cryptography
Symmetry 2018, 10(1), 23; https://doi.org/10.3390/sym10010023
Received: 5 December 2017 / Revised: 26 December 2017 / Accepted: 9 January 2018 / Published: 10 January 2018
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Abstract
We propose separable reversible data hiding in an encrypted signal with public key cryptography. In our separable framework, the image owner encrypts the original image by using a public key. On receipt of the encrypted signal, the data-hider embeds data in it by
[...] Read more.
We propose separable reversible data hiding in an encrypted signal with public key cryptography. In our separable framework, the image owner encrypts the original image by using a public key. On receipt of the encrypted signal, the data-hider embeds data in it by using a data-hiding key. The image decryption and data extraction are independent and separable at the receiver side. Even though the receiver, who has only the data-hiding key, does not learn about the decrypted content, he can extract data from the received marked encrypted signal. However, the receiver who has only the private key cannot extract the embedded data, but he can directly decrypt the received marked encrypted signal to obtain the original image without any error. Compared with other schemes using a cipher stream to encrypt the image, the proposed scheme is more appropriate for cloud services without degrading the security level. Full article
(This article belongs to the Special Issue Emerging Data Hiding Systems in Image Communications)
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Open AccessArticle Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products
Symmetry 2018, 10(1), 22; https://doi.org/10.3390/sym10010022
Received: 12 December 2017 / Revised: 27 December 2017 / Accepted: 3 January 2018 / Published: 10 January 2018
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Abstract
This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods:
[...] Read more.
This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method’s superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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Open AccessArticle Mixing Matrix Estimation of Underdetermined Blind Source Separation Based on Data Field and Improved FCM Clustering
Symmetry 2018, 10(1), 21; https://doi.org/10.3390/sym10010021
Received: 3 November 2017 / Revised: 2 January 2018 / Accepted: 3 January 2018 / Published: 9 January 2018
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Abstract
In modern electronic warfare, multiple input multiple output (MIMO) radar has become an important tool for electronic reconnaissance and intelligence transmission because of its anti-stealth, high resolution, low intercept and anti-destruction characteristics. As a common MIMO radar signal, discrete frequency coding waveform (DFCW)
[...] Read more.
In modern electronic warfare, multiple input multiple output (MIMO) radar has become an important tool for electronic reconnaissance and intelligence transmission because of its anti-stealth, high resolution, low intercept and anti-destruction characteristics. As a common MIMO radar signal, discrete frequency coding waveform (DFCW) has a serious overlap of both time and frequency, so it cannot be directly used in the current radar signal separation problems. The existing fuzzy clustering algorithms have problems in initial value selection, low convergence rate and local extreme values which will lead to the low accuracy of the mixing matrix estimation. Consequently, a novel mixing matrix estimation algorithm based on data field and improved fuzzy C-means (FCM) clustering is proposed. First of all, the sparsity and linear clustering characteristics of the time–frequency domain MIMO radar signals are enhanced by using the single-source principal value of complex angular detection. Secondly, the data field uses the potential energy information to analyze the particle distribution, thus design a new clustering number selection scheme. Then the particle swarm optimization algorithm is introduced to improve the iterative clustering process of FCM, and finally get the estimated value of the mixing matrix. The simulation results show that the proposed algorithm improves both the estimation accuracy and the robustness of the mixing matrix. Full article
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Open AccessFeature PaperArticle The Asymmetry is Derived from Mechanical Interlocking of Achiral Axle and Achiral Ring Components –Syntheses and Properties of Optically Pure [2]Rotaxanes–
Symmetry 2018, 10(1), 20; https://doi.org/10.3390/sym10010020
Received: 25 November 2017 / Revised: 20 December 2017 / Accepted: 27 December 2017 / Published: 9 January 2018
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Abstract
Rotaxanes consisting of achiral axle and achiral ring components can possess supramolecular chirality due to their unique geometrical architectures. To synthesize such chiral rotaxanes, we adapted a prerotaxane method based on aminolysis of a metacyclophane type prerotaxane that had planar chirality, which is
[...] Read more.
Rotaxanes consisting of achiral axle and achiral ring components can possess supramolecular chirality due to their unique geometrical architectures. To synthesize such chiral rotaxanes, we adapted a prerotaxane method based on aminolysis of a metacyclophane type prerotaxane that had planar chirality, which is composed of an achiral stopper unit and a crown ether type ring component. The prerotaxanes were well resolved using chiral HPLC into a pair of enantiomerically pure prerotaxanes, which were transferred into corresponding chiral rotaxanes, respectively. Obtained chiral rotaxanes were revealed to have considerable enantioselectivity. Full article
(This article belongs to the Special Issue Chiral Auxiliaries and Chirogenesis)
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Open AccessArticle Efficient Information Hiding Based on Theory of Numbers
Symmetry 2018, 10(1), 19; https://doi.org/10.3390/sym10010019
Received: 2 December 2017 / Revised: 26 December 2017 / Accepted: 3 January 2018 / Published: 8 January 2018
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Abstract
Data hiding is an efficient technique that conceals secret data into a digital medium. In 2006, Zhang and Wang proposed a data hiding scheme called exploiting modification direction (EMD) which has become a milestone in the field of data hiding. In recent years,
[...] Read more.
Data hiding is an efficient technique that conceals secret data into a digital medium. In 2006, Zhang and Wang proposed a data hiding scheme called exploiting modification direction (EMD) which has become a milestone in the field of data hiding. In recent years, many EMD-type data hiding schemes have been developed, but their embedding capacity remains restricted. In this paper, a novel data hiding scheme based on the combination of Chinese remainder theorem (CRT) and a new extraction function is proposed. By the proposed scheme, the cover image is divided into non-overlapping pixel groups for embedding to increase the embedding capacity. Experimental results show that the embedding capacity of the proposed scheme is significantly higher (greater than 2.5 bpp) than previously proposed schemes while ensuring very good visual quality of the stego image. In addition, security analysis is given to show that the proposed scheme can resist visual attack. Full article
(This article belongs to the Special Issue Emerging Data Hiding Systems in Image Communications)
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Open AccessArticle WPCB-Tree: A Novel Flash-Aware B-Tree Index Using a Write Pattern Converter
Symmetry 2018, 10(1), 18; https://doi.org/10.3390/sym10010018
Received: 23 October 2017 / Revised: 30 December 2017 / Accepted: 3 January 2018 / Published: 8 January 2018
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Abstract
For the past few years, flash memory has been widely used because of its prominent advantages such as fast access speed, nonvolatility, high reliability, and low power consumption. However, flash memory still has several drawbacks that need to be overcome, e.g., the erase-before-write
[...] Read more.
For the past few years, flash memory has been widely used because of its prominent advantages such as fast access speed, nonvolatility, high reliability, and low power consumption. However, flash memory still has several drawbacks that need to be overcome, e.g., the erase-before-write characteristic and a limited life cycle. Among these drawbacks, the erase-before-write characteristic causes the B-tree implementation on flash memory to be inefficient because it generates many erase operations. This study introduces a novel B-tree index structure using a write pattern converter (WPCB-tree) for flash memory. A WPCB-tree can minimize the risk of data loss and can improve the performance of the B-tree on flash memory. This WPCB-tree uses some blocks of flash memory as a buffer that temporarily stores all updated nodes. When the buffer is full, a buffer block is selected by a greedy algorithm, then the node pages in the block are converted into a sequential write pattern, and finally they are written into flash memory. In addition, in the case that all key values of a leaf node are continuously inserted, the WPCB-tree does not split the leaf node. As a result, this mechanism helps the WPCB-tree reduce the number of write operations on the flash memory. The experimental results show that the proposed B-tree variant on flash memory yields a better performance than that of other existing variants of the B-tree. Full article
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Open AccessArticle Interactive Cutting of Thin Deformable Objects
Symmetry 2018, 10(1), 17; https://doi.org/10.3390/sym10010017
Received: 23 November 2017 / Revised: 22 December 2017 / Accepted: 3 January 2018 / Published: 5 January 2018
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Abstract
Simulation of cutting is essential for many applications such as virtual surgical training. Most existing methods use the same triangle mesh for both visualization and collision handling, although the requirements for them in the interactive simulation are different. We introduce visual-collision binding between
[...] Read more.
Simulation of cutting is essential for many applications such as virtual surgical training. Most existing methods use the same triangle mesh for both visualization and collision handling, although the requirements for them in the interactive simulation are different. We introduce visual-collision binding between high-resolution visual meshes and low-resolution collision meshes, and thus extend the spatially reduced framework to support cutting. There are two phases in our framework: pre-processing and simulation. In the pre-processing phase, the fvisual-collision binding is built based on the computation of geodesic paths. In the simulation phase, the cutting paths are detected on the collision triangles and then mapped to local 2D coordinates systems in which the intersections between visual mesh and the cutting paths are calculated. Both collision and visual meshes are then re-meshed locally. The visual-collision binding is updated after cutting, based on which the collision-simulation and visual-simulation embedding are updated locally. Experimental results show that our cutting method is an efficient and flexible tool for interactive cutting simulation. Full article
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Open AccessArticle Detecting Ghost Targets Using Multilayer Perceptron in Multiple-Target Tracking
Symmetry 2018, 10(1), 16; https://doi.org/10.3390/sym10010016
Received: 15 November 2017 / Revised: 30 December 2017 / Accepted: 2 January 2018 / Published: 4 January 2018
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Abstract
This paper deals with a method for removing a ghost target that is not a real object from the output of a multiple object-tracking algorithm. This method uses an artificial neural network (multilayer perceptron) and introduces a structure, learning, verification, and evaluation method
[...] Read more.
This paper deals with a method for removing a ghost target that is not a real object from the output of a multiple object-tracking algorithm. This method uses an artificial neural network (multilayer perceptron) and introduces a structure, learning, verification, and evaluation method for the artificial neural network. The implemented system was tested at an intersection in a city center. Results from a 28-min measurement were 88% accurate when the multilayer perceptron for ghost target classification successfully detected the ghost targets, and 6.7% inaccurate when ghost targets were mistaken for actual targets. This method is expected to contribute to the advancement of intelligent transportation systems if the weaknesses revealed during the evaluation of the system are complemented and refined. Full article
(This article belongs to the Special Issue Emerging Approaches and Advances in Big Data)
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Open AccessArticle Electroencephalogram Similarity Analysis Using Temporal and Spectral Dynamics Analysis for Propofol and Desflurane Induced Unconsciousness
Symmetry 2018, 10(1), 15; https://doi.org/10.3390/sym10010015
Received: 4 December 2017 / Revised: 26 December 2017 / Accepted: 2 January 2018 / Published: 4 January 2018
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Abstract
Important information about the state dynamics of the brain during anesthesia is unraveled by Electroencephalogram (EEG) approaches. Patterns that are observed through EEG related to neural circuit mechanism under different molecular targets dependent anesthetics have recently attracted much attention. Propofol, a Gamma-amino butyric
[...] Read more.
Important information about the state dynamics of the brain during anesthesia is unraveled by Electroencephalogram (EEG) approaches. Patterns that are observed through EEG related to neural circuit mechanism under different molecular targets dependent anesthetics have recently attracted much attention. Propofol, a Gamma-amino butyric acid, is known with evidently increasing alpha oscillation. Desflurane shares the same receptor action and should be similar to propofol. To explore their dynamics, EEG under routine surgery level anesthetic depth is analyzed using multitaper spectral method from two groups: propofol (n = 28) and desflurane (n = 23). The time-varying spectrum comparison was undertaken to characterize their properties. Results show that both of the agents are dominated by slow and alpha waves. Especially, for increased alpha band feature, propofol unconsciousness shows maximum power at about 10 Hz (mean ± SD; frequency: 10.2 ± 1.4 Hz; peak power, −14.0 ± 1.6 dB), while it is approximate about 8 Hz (mean ± SD; frequency: 8.3 ± 1.3 Hz; peak power, −13.8 ± 1.6 dB) for desflurane with significantly lower frequency-resolved spectra for this band. In addition, the mean power of propofol is much higher from alpha to gamma band, including slow oscillation than that of desflurane. The patterns might give us an EEG biomarker for specific anesthetic. This study suggests that both of the anesthetics exhibit similar spectral dynamics, which could provide insight into some common neural circuit mechanism. However, differences between them also indicate their uniqueness where relevant. Full article
(This article belongs to the Special Issue Medical Imaging and Imaging Modalities)
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Open AccessArticle Secure Cyber Deception Architecture and Decoy Injection to Mitigate the Insider Threat
Symmetry 2018, 10(1), 14; https://doi.org/10.3390/sym10010014
Received: 18 September 2017 / Revised: 14 November 2017 / Accepted: 29 November 2017 / Published: 2 January 2018
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Abstract
We propose a novel dynamic host mutation (DHM) architecture based on moving target defense (MTD) that can actively cope with cyberattacks. The goal of the DHM is to break the cyber kill chain, expand the attack surface to increase the attacker’s target analysis
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We propose a novel dynamic host mutation (DHM) architecture based on moving target defense (MTD) that can actively cope with cyberattacks. The goal of the DHM is to break the cyber kill chain, expand the attack surface to increase the attacker’s target analysis cost, and disrupt the attacker’s fingerprinting to disable the server trace. We define the participating entities that share the MTD policy within the enterprise network or the critical infrastructure, and define functional modules of each entity for DHM enforcement. The threat model of this study is an insider threat of a type not considered in previous studies. We define an attack model considering an insider threat and propose a decoy injection mechanism to confuse the attacker. In addition, we analyze the security of the proposed structure and mechanism based on the security requirements and propose a trade-off considering security and availability. Full article
(This article belongs to the Special Issue Symmetry in Secure Cyber World)
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Open AccessFeature PaperArticle An Effective Authentication Scheme Using DCT for Mobile Devices
Symmetry 2018, 10(1), 13; https://doi.org/10.3390/sym10010013
Received: 5 November 2017 / Revised: 20 December 2017 / Accepted: 23 December 2017 / Published: 2 January 2018
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Abstract
This paper proposes an image authentication scheme for mobile devices. The proposed scheme generates an image watermark by using discrete cosine transform (DCT) and hides the watermark in the spatial pixels for image authentication and tamper detection. The hiding operator used in this
[...] Read more.
This paper proposes an image authentication scheme for mobile devices. The proposed scheme generates an image watermark by using discrete cosine transform (DCT) and hides the watermark in the spatial pixels for image authentication and tamper detection. The hiding operator used in this paper is very simple in a mobile environment allowing high-speed authentication using a low-power mobile device. The quality of the stego-image and the recovered image becomes excellent as a result of the proposed scheme. Full article
(This article belongs to the Special Issue Information Technology and Its Applications)
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Open AccessArticle On the Interdependence of the Financial Market and Open Access Spectrum Market in the 5G Network
Symmetry 2018, 10(1), 12; https://doi.org/10.3390/sym10010012
Received: 8 December 2017 / Revised: 29 December 2017 / Accepted: 29 December 2017 / Published: 31 December 2017
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Abstract
Modern 5G networks offer a large space for innovation and a completely new approach to addressing network functioning. A fixed spectrum assignment policy is a significant limitation of today’s wireless communication network practice and is to be replaced by a completely new approach
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Modern 5G networks offer a large space for innovation and a completely new approach to addressing network functioning. A fixed spectrum assignment policy is a significant limitation of today’s wireless communication network practice and is to be replaced by a completely new approach called dynamic spectrum access (DSA). However, there is no general agreement on the organization of the DSA. Some studies suggest that open access market can be inspired by the electricity or financial markets. It allows to treat operators with region coverage as investors entering the market and trading the spectra on an on-demand basis. Because investors operate in both the financial markets and the markets for spectra, new interference between both markets emerges. Our paper shows how the risk-free rate of return stemming from the financial markets influences the techno-economic properties of the network. We show that, for low risk-free returns, the spectrum market becomes oversupplied, which keeps service prices very low and spectrum trading volumes large. In contrast, if risk-free returns are high, then spectrum trading volumes decline and the market becomes price sensitive; in other words, economic rules begin to work better. Full article
(This article belongs to the Special Issue Novel Learning-Based Approaches for Cognitive Radio Networks)
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Open AccessArticle Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks
Symmetry 2018, 10(1), 11; https://doi.org/10.3390/sym10010011
Received: 5 November 2017 / Revised: 26 December 2017 / Accepted: 27 December 2017 / Published: 29 December 2017
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Mosaic, Rust, Brown spot, and Alternaria leaf spot are the four common types of apple leaf diseases. Early diagnosis and accurate identification of apple leaf diseases can control the spread of infection and ensure the healthy development of the apple industry. The existing
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Mosaic, Rust, Brown spot, and Alternaria leaf spot are the four common types of apple leaf diseases. Early diagnosis and accurate identification of apple leaf diseases can control the spread of infection and ensure the healthy development of the apple industry. The existing research uses complex image preprocessing and cannot guarantee high recognition rates for apple leaf diseases. This paper proposes an accurate identifying approach for apple leaf diseases based on deep convolutional neural networks. It includes generating sufficient pathological images and designing a novel architecture of a deep convolutional neural network based on AlexNet to detect apple leaf diseases. Using a dataset of 13,689 images of diseased apple leaves, the proposed deep convolutional neural network model is trained to identify the four common apple leaf diseases. Under the hold-out test set, the experimental results show that the proposed disease identification approach based on the convolutional neural network achieves an overall accuracy of 97.62%, the model parameters are reduced by 51,206,928 compared with those in the standard AlexNet model, and the accuracy of the proposed model with generated pathological images obtains an improvement of 10.83%. This research indicates that the proposed deep learning model provides a better solution in disease control for apple leaf diseases with high accuracy and a faster convergence rate, and that the image generation technique proposed in this paper can enhance the robustness of the convolutional neural network model. Full article
(This article belongs to the Special Issue Information Technology and Its Applications)
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Open AccessFeature PaperReview Helicene-Based Chiral Auxiliaries and Chirogenesis
Symmetry 2018, 10(1), 10; https://doi.org/10.3390/sym10010010
Received: 7 December 2017 / Revised: 25 December 2017 / Accepted: 26 December 2017 / Published: 29 December 2017
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Abstract
Helicenes are unique helical chromophores possessing advanced and well-controlled spectral and chemical properties owing to their diverse functionalization and defined structures. Specific modification of these molecules by introducing aromatic rings of differing nature and different functional groups results in special chiroptical properties, making
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Helicenes are unique helical chromophores possessing advanced and well-controlled spectral and chemical properties owing to their diverse functionalization and defined structures. Specific modification of these molecules by introducing aromatic rings of differing nature and different functional groups results in special chiroptical properties, making them effective chiral auxiliaries and supramolecular chirogenic hosts. This review aims to highlight these distinct structural features of helicenes; the different synthetic and supramolecular approaches responsible for their efficient chirality control; and their employment in the chirogenic systems, which are still not fully explored. It further covers the limitation, scope, and future prospects of helicene chromophores in chiral chemistry. Full article
(This article belongs to the Special Issue Chiral Auxiliaries and Chirogenesis)
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Open AccessFeature PaperReview Supersymmetric Higher Spin Models in Three Dimensional Spaces
Symmetry 2018, 10(1), 9; https://doi.org/10.3390/sym10010009
Received: 2 December 2017 / Revised: 23 December 2017 / Accepted: 25 December 2017 / Published: 28 December 2017
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Abstract
We review the component Lagrangian construction of the supersymmetric higher spin models in three-dimensional (3D) Minkowski and anti de Sitter (AdS) spaces. The approach is based on the frame-like gauge-invariant formulation, where massive higher spin fields are realized through
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We review the component Lagrangian construction of the supersymmetric higher spin models in three-dimensional (3D) Minkowski and anti de Sitter ( A d S ) spaces. The approach is based on the frame-like gauge-invariant formulation, where massive higher spin fields are realized through a system of massless ones. We develop a supersymmetric generalization of this formulation to the Lagrangian construction of the on-shell N = 1 , 3D higher spin supermultiplets. In 3D Minkowski space, we show that the massive supermultiplets can be constructed from one extended massless supermultiplet by adding the mass terms to the Lagrangian and the corresponding corrections to the supertransformations of the fermionic fields. In 3D A d S space, we construct massive supermultiplets using a formulation of the massive fields in terms of the set of gauge-invariant objects (curvatures) in the process of their consistent supersymmetric deformation. Full article
(This article belongs to the Special Issue Symmetry: Feature Papers 2017)
Open AccessFeature PaperArticle General k-Dimensional Solvable Systems of Difference Equations
Symmetry 2018, 10(1), 8; https://doi.org/10.3390/sym10010008
Received: 6 December 2017 / Revised: 21 December 2017 / Accepted: 21 December 2017 / Published: 28 December 2017
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Abstract
The solvability of a k-dimensional system of difference equations of interest, which extends several recently studied ones, is investigated. A general sufficient condition for the solvability of the system is given, considerably extending some recent results in the literature. Full article
Open AccessArticle Stability of Spline-Type Systems in the Abelian Case
Symmetry 2018, 10(1), 7; https://doi.org/10.3390/sym10010007
Received: 29 November 2017 / Revised: 20 December 2017 / Accepted: 21 December 2017 / Published: 27 December 2017
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Abstract
In this paper, the stability of translation-invariant spaces of distributions over locally compact groups is stated as boundedness of synthesis and projection operators. At first, a characterization of the stability of spline-type spaces is given, in the standard sense of the stability for
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In this paper, the stability of translation-invariant spaces of distributions over locally compact groups is stated as boundedness of synthesis and projection operators. At first, a characterization of the stability of spline-type spaces is given, in the standard sense of the stability for shift-invariant spaces, that is, linear independence characterizes lower boundedness of the synthesis operator in Banach spaces of distributions. The constructive nature of the proof for Theorem 2 enabled us to constructively realize the biorthogonal system of a given one. Then, inspired by the multiresolution analysis and the Lax equivalence for general discretization schemes, we approached the stability of a sequence of spline-type spaces as uniform boundedness of projection operators. Through Theorem 3, we characterize stable sequences of stable spline-type spaces. Full article
Open AccessEditorial Fuzzy Techniques for Decision Making
Symmetry 2018, 10(1), 6; https://doi.org/10.3390/sym10010006
Received: 22 December 2017 / Revised: 22 December 2017 / Accepted: 25 December 2017 / Published: 27 December 2017
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Abstract
This book contains the successful invited submissions [1–21] to a Special Issue of Symmetry on the subject area of “Fuzzy Techniques for Decision Making”.[...] Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making) Printed Edition available
Open AccessArticle Multiple Criteria Decision Making and General Regression for Determining Influential Factors on S&P 500 Index Futures
Symmetry 2018, 10(1), 5; https://doi.org/10.3390/sym10010005
Received: 21 November 2017 / Revised: 14 December 2017 / Accepted: 16 December 2017 / Published: 27 December 2017
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Abstract
We employ the DEMATEL-based analytic network process (D-ANP) to evaluate the weight of various factors on S&P 500 index futures. The general regression method is employed to prove the result. We then employed grey relational analysis (GRA) to examine predictive power of determinants
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We employ the DEMATEL-based analytic network process (D-ANP) to evaluate the weight of various factors on S&P 500 index futures. The general regression method is employed to prove the result. We then employed grey relational analysis (GRA) to examine predictive power of determinants suggested by 13 experts for fluctuations in S&P 500 index futures. This study yields a number of empirical results. (1) The explanatory power of macroeconomic factors for S&P 500 index futures outperforms that of technical indicators, as found in most of previous research papers; (2) The D-ANP revealed that five core factors (US dollar index, ISM manufacturing purchasing managers’ index (PMI), interest rate, volatility index, and unemployment rate) affect fluctuations in S&P 500 index futures, of which the US dollar index is the most important; (3) A casual diagram shows that the US dollar index and interest rate have mutual effects, and the US dollar index unilaterally affects ISM manufacturing PMI, unemployment rate, and the volatility index; (4) Granger causality test results confirmed some similar results obtained via the D-ANP that the US dollar index, interest rate, and the PMI have major impacts on the S&P 500 index futures; (5) The general regression results confirmed that four of five factors selected via the D-ANP (US dollar index, interest rate, volatility index, and unemployment rate) have strong explanatory power in forecasting the rate of return on S&P 500 index futures; (6) The GRA revealed that the explanatory power of various factors selected via the D-ANP was better for S&P 500 than for Dow Jones Industrial Average (DJIA) and Nasdaq 100 index futures; (7) The explanatory power is better for S&P 500 Industrial than for S&P 500 transportation, utility, and financial index futures. Full article
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Open AccessArticle Real-Time Video Stitching Using Camera Path Estimation and Homography Refinement
Symmetry 2018, 10(1), 4; https://doi.org/10.3390/sym10010004
Received: 1 December 2017 / Revised: 20 December 2017 / Accepted: 25 December 2017 / Published: 26 December 2017
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Abstract
We propose a novel real-time video stitching method using camera path estimation and homography refinement. The method can stably stitch multiple frames acquired from moving cameras in real time. In the proposed method, one initial between-camera (BC) homography and each camera path (CP)
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We propose a novel real-time video stitching method using camera path estimation and homography refinement. The method can stably stitch multiple frames acquired from moving cameras in real time. In the proposed method, one initial between-camera (BC) homography and each camera path (CP) homography are used to estimate the BC homography at every frame. The BC homography is refined by using block matching to adjust the errors of estimated CPs (homography refinement). For fast processing, we extract features using the difference of intensities and use the optical flow to estimate camera motion (CM) homographies, which are multiplied with the previous CMs to calculate CPs (camera path estimations). In experiments, we demonstrated the performance of the CP estimation and homography refinement approach by comparing it with other methods. The experimental results show that the proposed method can stably stitch two image sequences at a rate exceeding 13 fps (frames per second). Full article
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Open AccessArticle Deep Learning for Detection of Object-Based Forgery in Advanced Video
Symmetry 2018, 10(1), 3; https://doi.org/10.3390/sym10010003
Received: 26 October 2017 / Revised: 21 December 2017 / Accepted: 21 December 2017 / Published: 26 December 2017
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Abstract
Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based
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Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN) to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results. Full article
(This article belongs to the Special Issue Emerging Data Hiding Systems in Image Communications)
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