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Symmetry, Volume 9, Issue 9 (September 2017) – 30 articles

Cover Story (view full-size image): We discuss groups formed by spatial point symmetry operations in combination with time translations, i.e., spatio-temporal symmetries, and outline some of their possible applications. The figure shows the orbit of an electron in k-space under the influence of a magnetic field (denoted by H), within the semi-classical theory of electron dynamics. The yellow surface represents a constant energy surface in k-space. The spatial operation and time translation, which together form a spatio-temporal symmetry of the trajectory of the electron, are shown with red and blue arrows respectively. View this paper
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Article
Toward Bulk Synchronous Parallel-Based Machine Learning Techniques for Anomaly Detection in High-Speed Big Data Networks
Symmetry 2017, 9(9), 197; https://doi.org/10.3390/sym9090197 - 19 Sep 2017
Cited by 13 | Viewed by 4224
Abstract
Anomaly detection systems, also known as intrusion detection systems (IDSs), continuously monitor network traffic aiming to identify malicious actions. Extensive research has been conducted to build efficient IDSs emphasizing two essential characteristics. The first is concerned with finding optimal feature selection, while another [...] Read more.
Anomaly detection systems, also known as intrusion detection systems (IDSs), continuously monitor network traffic aiming to identify malicious actions. Extensive research has been conducted to build efficient IDSs emphasizing two essential characteristics. The first is concerned with finding optimal feature selection, while another deals with employing robust classification schemes. However, the advent of big data concepts in anomaly detection domain and the appearance of sophisticated network attacks in the modern era require some fundamental methodological revisions to develop IDSs. Therefore, we first identify two more significant characteristics in addition to the ones mentioned above. These refer to the need for employing specialized big data processing frameworks and utilizing appropriate datasets for validating system’s performance, which is largely overlooked in existing studies. Afterwards, we set out to develop an anomaly detection system that comprehensively follows these four identified characteristics, i.e., the proposed system (i) performs feature ranking and selection using information gain and automated branch-and-bound algorithms respectively; (ii) employs logistic regression and extreme gradient boosting techniques for classification; (iii) introduces bulk synchronous parallel processing to cater computational requirements of high-speed big data networks; and; (iv) uses the Infromation Security Centre of Excellence, of the University of Brunswick real-time contemporary dataset for performance evaluation. We present experimental results that verify the efficacy of the proposed system. Full article
(This article belongs to the Special Issue Emerging Approaches and Advances in Big Data)
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Review
Chiral Analysis of Pesticides and Drugs of Environmental Concern: Biodegradation and Enantiomeric Fraction
Symmetry 2017, 9(9), 196; https://doi.org/10.3390/sym9090196 - 16 Sep 2017
Cited by 26 | Viewed by 3205
Abstract
The importance of stereochemistry for medicinal chemistry and pharmacology is well recognized and the dissimilar behavior of enantiomers is fully documented. Regarding the environment, the significance is equivalent since enantiomers of chiral organic pollutants can also differ in biodegradation processes and fate, as [...] Read more.
The importance of stereochemistry for medicinal chemistry and pharmacology is well recognized and the dissimilar behavior of enantiomers is fully documented. Regarding the environment, the significance is equivalent since enantiomers of chiral organic pollutants can also differ in biodegradation processes and fate, as well as in ecotoxicity. This review comprises designed biodegradation studies of several chiral drugs and pesticides followed by enantioselective analytical methodologies to accurately measure the enantiomeric fraction (EF). The enantioselective monitoring of microcosms and laboratory-scale experiments with different environmental matrices is herein reported. Thus, this review focuses on the importance of evaluating the EF variation during biodegradation studies of chiral pharmaceuticals, drugs of abuse, and agrochemicals and has implications for the understanding of the environmental fate of chiral pollutants. Full article
(This article belongs to the Special Issue Chiral Separations)
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Article
Solvable Three-Dimensional Product-Type System of Difference Equations with Multipliers
Symmetry 2017, 9(9), 195; https://doi.org/10.3390/sym9090195 - 16 Sep 2017
Viewed by 1550
Abstract
The solvability of the following three-dimensional product-type system of difference equations [...] Read more.
The solvability of the following three-dimensional product-type system of difference equations x n + 1 = α y n a z n 1 b , y n + 1 = β z n c x n 1 d , z n + 1 = γ x n f y n 1 g , n N 0 , where a , b , c , d , f , g Z , α , β , γ C \ { 0 } and x i , y i , z i C \ { 0 } , i { 0 , 1 } , is shown. This is the first three-dimensional system of the type with multipliers for which formulas are presented for their solutions in closed form in all the cases. Full article
Article
Planning of Knotting Based on Manipulation Skills with Consideration of Robot Mechanism/Motion and Its Realization by a Robot Hand System
Symmetry 2017, 9(9), 194; https://doi.org/10.3390/sym9090194 - 15 Sep 2017
Cited by 3 | Viewed by 3594
Abstract
This paper demonstrates the relationship between the production process of a knot and manipulation skills. First, we define the description (rope intersections, grasp type and fixation positions) of a knot. Second, we clarify the characteristics of the manipulation skills from the viewpoint of [...] Read more.
This paper demonstrates the relationship between the production process of a knot and manipulation skills. First, we define the description (rope intersections, grasp type and fixation positions) of a knot. Second, we clarify the characteristics of the manipulation skills from the viewpoint of the knot description. Next, in order to obtain the production process of the knot, we propose an analysis method based on the structure of the knot and the characteristics of the manipulation skills. Using the proposed analysis method, we analyzed eight kinds of knots, formed with a single rope, two ropes or a single rope and an object. Finally, in order to validate the production process obtained by the proposed analysis method, we show experimental results of an overhand knot and a half hitch produced by using a robot hand system. Full article
(This article belongs to the Special Issue Knot Theory and Its Applications)
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Article
M2M Security Technology of CPS Based on Blockchains
Symmetry 2017, 9(9), 193; https://doi.org/10.3390/sym9090193 - 14 Sep 2017
Cited by 37 | Viewed by 3718
Abstract
As the core of intelligent manufacturing, cyber-physical systems (CPS) have serious security issues, especially for the communication security of their terminal machine-to-machine (M2M) communications. In this paper, blockchain technology is introduced to address such a security problem of communications between different types of [...] Read more.
As the core of intelligent manufacturing, cyber-physical systems (CPS) have serious security issues, especially for the communication security of their terminal machine-to-machine (M2M) communications. In this paper, blockchain technology is introduced to address such a security problem of communications between different types of machines in the CPS. According to the principles of blockchain technology, we designed a blockchain for secure M2M communications. As a communication system, M2M consists of public network areas, device areas, and private areas, and we designed a sophisticated blockchain structure between the public area and private area. For validating our design, we took cotton spinning production as a case study to demonstrate our solution to M2M communication problems under the CPS framework. We have demonstrated that the blockchain technology can effectively solve the safety of expansion of machines in the production process and the communication data between the machines cannot be tampered with. Full article
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Article
A Robust Method for Finding the Automated Best Matched Genes Based on Grouping Similar Fragments of Large-Scale References for Genome Assembly
Symmetry 2017, 9(9), 192; https://doi.org/10.3390/sym9090192 - 13 Sep 2017
Cited by 8 | Viewed by 2426
Abstract
Big data research on genomic sequence analysis has accelerated considerably with the development of next-generation sequencing. Currently, research on genomic sequencing has been conducted using various methods, ranging from the assembly of reads consisting of fragments to the annotation of genetic information using [...] Read more.
Big data research on genomic sequence analysis has accelerated considerably with the development of next-generation sequencing. Currently, research on genomic sequencing has been conducted using various methods, ranging from the assembly of reads consisting of fragments to the annotation of genetic information using a database that contains known genome information. According to the development, most tools to analyze the new organelles’ genetic information requires different input formats such as FASTA, GeneBank (GB) and tab separated files. The various data formats should be modified to satisfy the requirements of the gene annotation system after genome assembly. In addition, the currently available tools for the analysis of organelles are usually developed only for specific organisms, thus the need for gene prediction tools, which are useful for any organism, has been increased. The proposed method—termed the genome_search_plotter—is designed for the easy analysis of genome information from the related references without any file format modification. Anyone who is interested in intracellular organelles such as the nucleus, chloroplast, and mitochondria can analyze the genetic information using the assembled contig of an unknown genome and a reference model without any modification of the data from the assembled contig. Full article
(This article belongs to the Special Issue Emerging Approaches and Advances in Big Data)
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Article
Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity
Symmetry 2017, 9(9), 191; https://doi.org/10.3390/sym9090191 - 11 Sep 2017
Cited by 15 | Viewed by 2097
Abstract
The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership. In this paper, we propose a novel forecasting model based [...] Read more.
The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership. In this paper, we propose a novel forecasting model based on neutrosophic set theory and the fuzzy logical relationships between the status of historical and current values. Firstly, the original time series of the stock market is converted to a fluctuation time series by comparing each piece of data with that of the previous day. The fluctuation time series is then fuzzified into a fuzzy-fluctuation time series in terms of the pre-defined up, equal, and down intervals. Next, the fuzzy logical relationships can be expressed by two neutrosophic sets according to the probabilities of different statuses for each current value and a certain range of corresponding histories. Finally, based on the neutrosophic logical relationships and the status of history, a Jaccard similarity measure is employed to find the most proper logical rule to forecast its future. The authentic Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) time series datasets are used as an example to illustrate the forecasting procedure and performance comparisons. The experimental results show that the proposed method can successfully forecast the stock market and other similar kinds of time series. We also apply the proposed method to forecast the Shanghai Stock Exchange Composite Index (SHSECI) to verify its effectiveness and universality. Full article
(This article belongs to the Special Issue Neutrosophic Theories Applied in Engineering)
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Review
Chiral Stationary Phases for Liquid Chromatography Based on Chitin- and Chitosan-Derived Marine Polysaccharides
Symmetry 2017, 9(9), 190; https://doi.org/10.3390/sym9090190 - 11 Sep 2017
Cited by 20 | Viewed by 3401
Abstract
The development of chiral stationary phases (CSPs) for liquid chromatography (LC) revolutionized the enantioseparation and, nowadays, different types of CSPs are commercially available. Polysaccharide-based CSPs are one of the most versatile and widely used for both analytical and preparative applications and they are [...] Read more.
The development of chiral stationary phases (CSPs) for liquid chromatography (LC) revolutionized the enantioseparation and, nowadays, different types of CSPs are commercially available. Polysaccharide-based CSPs are one of the most versatile and widely used for both analytical and preparative applications and they are able to resolve several classes of racemates. Phenylcarbamates of amylose and cellulose derivatives are the most successful; however, polysaccharide-based CSPs comprising marine-derived polysaccharides are also described revealing high chiral recognition abilities and wider range of mobile phases. A literature survey covering the report on chitin and chitosan based CSPs is presented. The chemical structure of the chiral selectors, their development and applications in chiral LC are emphasized. Full article
(This article belongs to the Special Issue Chiral Separations)
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Article
A Study on Interaction of Gaze Pointer-Based User Interface in Mobile Virtual Reality Environment
Symmetry 2017, 9(9), 189; https://doi.org/10.3390/sym9090189 - 11 Sep 2017
Cited by 15 | Viewed by 3172
Abstract
This research proposes a gaze pointer-based user interface to provide user-oriented interaction suitable for the virtual reality environment on mobile platforms. For this purpose, a mobile platform-based three-dimensional interactive content is produced to test whether the proposed gaze pointer-based interface increases user satisfaction [...] Read more.
This research proposes a gaze pointer-based user interface to provide user-oriented interaction suitable for the virtual reality environment on mobile platforms. For this purpose, a mobile platform-based three-dimensional interactive content is produced to test whether the proposed gaze pointer-based interface increases user satisfaction through the interactions in a virtual reality environment based on mobile platforms. The gaze pointer-based interface—the most common input method for mobile virtual reality content—is designed by considering four types: the visual field range, the feedback system, multi-dimensional information transfer, and background colors. The performance of the proposed gaze pointer-based interface is analyzed by conducting experiments on whether or not it offers motives for user interest, effects of enhanced immersion, provision of new experience, and convenience in operating content. In addition, it is verified whether any negative psychological factors, such as VR sickness, fatigue, difficulty of control, and discomfort in using contents are caused. Finally, through the survey experiment, this study confirmed that it is possible to design different ideal gaze pointer-based interface in mobile VR environment according to presence and convenience. Full article
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Article
On the Form and Growth of Complex Crystals: The Case of Tsai-Type Clusters
Symmetry 2017, 9(9), 188; https://doi.org/10.3390/sym9090188 - 11 Sep 2017
Cited by 5 | Viewed by 2908
Abstract
Where are the atoms in complex crystals such as quasicrystals or periodic crystals with one hundred or more atoms per unit cell? How did they get there? The first of these questions has been gradually answered for many materials over the quarter-century since [...] Read more.
Where are the atoms in complex crystals such as quasicrystals or periodic crystals with one hundred or more atoms per unit cell? How did they get there? The first of these questions has been gradually answered for many materials over the quarter-century since quasicrystals were discovered; in this paper we address the second. We briefly review a history of proposed models for describing atomic positions in crystal structures. We then present a revised description and possible growth model for one particular system of alloys, those containing Tsai-type clusters, that includes an important class of quasicrystals. Full article
(This article belongs to the Special Issue Polyhedral Structures)
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Article
Spatio-Temporal Symmetry—Point Groups with Time Translations
Symmetry 2017, 9(9), 187; https://doi.org/10.3390/sym9090187 - 08 Sep 2017
Cited by 4 | Viewed by 2837
Abstract
Spatial symmetries occur in combination with temporal symmetries in a wide range of physical systems in nature, including time-periodic quantum systems typically described by the Floquet formalism. In this context, groups formed by three-dimensional point group symmetry operations in combination with time translation [...] Read more.
Spatial symmetries occur in combination with temporal symmetries in a wide range of physical systems in nature, including time-periodic quantum systems typically described by the Floquet formalism. In this context, groups formed by three-dimensional point group symmetry operations in combination with time translation operations are discussed in this work. The derivation of these ’spatio-temporal’ groups from conventional point groups and their irreducible representations is outlined, followed by a complete listing. The groups are presented in a template similar to space group operations, and are visualized using a modified version of conventional stereographic projections. Simple examples of physical processes that simultaneously exhibit symmetry in space and time are identified and used to illustrate the application of spatio-temporal groups. Full article
(This article belongs to the Special Issue Symmetry and Symmetry Breaking in Quantum Mechanics)
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Article
An Internet of Things Approach for Extracting Featured Data Using AIS Database: An Application Based on the Viewpoint of Connected Ships
Symmetry 2017, 9(9), 186; https://doi.org/10.3390/sym9090186 - 07 Sep 2017
Cited by 8 | Viewed by 2377
Abstract
Automatic Identification System (AIS), as a major data source of navigational data, is widely used in the application of connected ships for the purpose of implementing maritime situation awareness and evaluating maritime transportation. Efficiently extracting featured data from AIS database is always a [...] Read more.
Automatic Identification System (AIS), as a major data source of navigational data, is widely used in the application of connected ships for the purpose of implementing maritime situation awareness and evaluating maritime transportation. Efficiently extracting featured data from AIS database is always a challenge and time-consuming work for maritime administrators and researchers. In this paper, a novel approach was proposed to extract massive featured data from the AIS database. An Evidential Reasoning rule based methodology was proposed to simulate the procedure of extracting routes from AIS database artificially. First, the frequency distributions of ship dynamic attributes, such as the mean and variance of Speed over Ground, Course over Ground, are obtained, respectively, according to the verified AIS data samples. Subsequently, the correlations between the attributes and belief degrees of the categories are established based on likelihood modeling. In this case, the attributes were characterized into several pieces of evidence, and the evidence can be combined with the Evidential Reasoning rule. In addition, the weight coefficients were trained in a nonlinear optimization model to extract the AIS data more accurately. A real life case study was conducted at an intersection waterway, Yangtze River, Wuhan, China. The results show that the proposed methodology is able to extract data very precisely. Full article
(This article belongs to the Special Issue Applications of Internet of Things)
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Article
An Efficient Image Segmentation Algorithm Using Neutrosophic Graph Cut
Symmetry 2017, 9(9), 185; https://doi.org/10.3390/sym9090185 - 06 Sep 2017
Cited by 11 | Viewed by 2184
Abstract
Segmentation is considered as an important step in image processing and computer vision applications, which divides an input image into various non-overlapping homogenous regions and helps to interpret the image more conveniently. This paper presents an efficient image segmentation algorithm using neutrosophic graph [...] Read more.
Segmentation is considered as an important step in image processing and computer vision applications, which divides an input image into various non-overlapping homogenous regions and helps to interpret the image more conveniently. This paper presents an efficient image segmentation algorithm using neutrosophic graph cut (NGC). An image is presented in neutrosophic set, and an indeterminacy filter is constructed using the indeterminacy value of the input image, which is defined by combining the spatial information and intensity information. The indeterminacy filter reduces the indeterminacy of the spatial and intensity information. A graph is defined on the image and the weight for each pixel is represented using the value after indeterminacy filtering. The segmentation results are obtained using a maximum-flow algorithm on the graph. Numerous experiments have been taken to test its performance, and it is compared with a neutrosophic similarity clustering (NSC) segmentation algorithm and a graph-cut-based algorithm. The results indicate that the proposed NGC approach obtains better performances, both quantitatively and qualitatively. Full article
(This article belongs to the Special Issue Neutrosophic Theories Applied in Engineering)
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Article
An Efficient and Energy-Aware Cloud Consolidation Algorithm for Multimedia Big Data Applications
Symmetry 2017, 9(9), 184; https://doi.org/10.3390/sym9090184 - 06 Sep 2017
Cited by 8 | Viewed by 2706
Abstract
It is well known that cloud computing has many potential advantages over traditional distributed systems. Many enterprises can build their own private cloud with open source infrastructure as a service (IaaS) frameworks. Since enterprise applications and data are migrating to private cloud, the [...] Read more.
It is well known that cloud computing has many potential advantages over traditional distributed systems. Many enterprises can build their own private cloud with open source infrastructure as a service (IaaS) frameworks. Since enterprise applications and data are migrating to private cloud, the performance of cloud computing environments is of utmost importance for both cloud providers and users. To improve the performance, previous studies on cloud consolidation have been focused on live migration of virtual machines based on resource utilization. However, the approaches are not suitable for multimedia big data applications. In this paper, we reveal the performance bottleneck of multimedia big data applications in cloud computing environments and propose a cloud consolidation algorithm that considers application types. We show that our consolidation algorithm outperforms previous approaches. Full article
(This article belongs to the Special Issue Emerging Approaches and Advances in Big Data)
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Article
Community Detection Based on Differential Evolution Using Social Spider Optimization
Symmetry 2017, 9(9), 183; https://doi.org/10.3390/sym9090183 - 06 Sep 2017
Cited by 14 | Viewed by 2604
Abstract
Community detection (CD) has become an important research direction for data mining in complex networks. Evolutionary algorithm-based (EA-based) approaches, among many other existing community detection methods, are widely used. However, EA-based approaches are prone to population degradation and local convergence. Developing more efficient [...] Read more.
Community detection (CD) has become an important research direction for data mining in complex networks. Evolutionary algorithm-based (EA-based) approaches, among many other existing community detection methods, are widely used. However, EA-based approaches are prone to population degradation and local convergence. Developing more efficient evolutionary algorithms thus becomes necessary. In 2013, Cuevas et al. proposed a new differential evolution (DE) hybrid meta-heuristic algorithm based on the simulated cooperative behavior of spiders, known as social spider optimization (SSO). On the basis of improving the SSO algorithm, this paper proposes a community detection algorithm based on differential evolution using social spider optimization (DESSO/CD). In this algorithm, the CD detection process is done by simulating the spider cooperative operators, marriage, and operator selection. The similarity of nodes is defined as local fitness function; the community quality increment is used as a screening criterion for evolutionary operators. Populations are sorted according to their contribution and diversity, making evolution even more different. In the entire process, a random cloud crossover model strategy is used to maintain population diversity. Each generation of the mating radius of the SSO algorithm will be adjusted appropriately according to the iterative times and fitness values. This strategy not only ensures the search space of operators, but also reduces the blindness of exploration. On the other hand, the multi-level, multi-granularity strategy of DESSO/CD can be used to further compensate for resolution limitations and extreme degradation defects based on modular optimization methods. The experimental results demonstrate that the DESSO/CD method could detect the community structure with higher partition accuracy and lower computational cost when compared with existing methods. Since the application of the SSO algorithm in CD research is just beginning, the study is competitive and promising. Full article
(This article belongs to the Special Issue Information Technology and Its Applications)
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Article
Effects of Handedness and Viewpoint on the Imitation of Origami-Making
Symmetry 2017, 9(9), 182; https://doi.org/10.3390/sym9090182 - 06 Sep 2017
Cited by 6 | Viewed by 2026
Abstract
The evolutionary origins of the human bias for 85% right-handedness are obscure. The Apprenticeship Complexity Theory states that the increasing difficulty of acquiring stone tool-making and other manual skills in the Pleistocene favoured learners whose hand preference matched that of their teachers. Furthermore, [...] Read more.
The evolutionary origins of the human bias for 85% right-handedness are obscure. The Apprenticeship Complexity Theory states that the increasing difficulty of acquiring stone tool-making and other manual skills in the Pleistocene favoured learners whose hand preference matched that of their teachers. Furthermore, learning from a viewing position opposite, rather than beside, the demonstrator might be harder because it requires more mental transformation. We varied handedness and viewpoint in a bimanual learning task. Thirty-two participants reproduced folding asymmetric origami figures as demonstrated by a videotaped teacher in four conditions (left-handed teacher opposite the learner, left-handed beside, right-handed opposite, or right-handed beside). Learning performance was measured by time to complete each figure, number of video pauses and rewinds, and similarity of copies to the target shape. There was no effect of handedness or viewpoint on imitation learning. However, participants preferred to produce figures with the same asymmetry as demonstrated, indicating they imitate the teacher's hand preference. We speculate that learning by imitation involves internalising motor representations and that, to facilitate learning by imitation, many motor actions can be flexibly executed using the demonstrated hand configuration. We conclude that matching hand preferences evolved due to socially learning moderately complex bimanual skills. Full article
(This article belongs to the Special Issue Brain Asymmetry of Structure and/or Function)
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Article
Sandor Type Fuzzy Inequality Based on the (s,m)-Convex Function in the Second Sense
Symmetry 2017, 9(9), 181; https://doi.org/10.3390/sym9090181 - 04 Sep 2017
Cited by 1 | Viewed by 2226
Abstract
Integral inequalities play critical roles in measure theory and probability theory. Given recent profound discoveries in the field of fuzzy set theory, fuzzy inequality has become a hot research topic in recent years. For classical Sandor type inequality, this paper intends to extend [...] Read more.
Integral inequalities play critical roles in measure theory and probability theory. Given recent profound discoveries in the field of fuzzy set theory, fuzzy inequality has become a hot research topic in recent years. For classical Sandor type inequality, this paper intends to extend the Sugeno integral. Based on the (s,m)-convex function in the second sense, a new Sandor type inequality is proposed for the Sugeno integral. Examples are given to verify the conclusion of this paper. Full article
(This article belongs to the Special Issue Fuzzy Sets Theory and Its Applications)
Article
Qinling: A Parametric Model in Speculative Multithreading
Symmetry 2017, 9(9), 180; https://doi.org/10.3390/sym9090180 - 02 Sep 2017
Cited by 2 | Viewed by 2297
Abstract
Speculative multithreading (SpMT) is a thread-level automatic parallelization technique that can accelerate sequential programs, especially for irregular applications that are hard to be parallelized by conventional approaches. Thread partition plays a critical role in SpMT. Conventional machine learning-based thread partition approaches applied machine [...] Read more.
Speculative multithreading (SpMT) is a thread-level automatic parallelization technique that can accelerate sequential programs, especially for irregular applications that are hard to be parallelized by conventional approaches. Thread partition plays a critical role in SpMT. Conventional machine learning-based thread partition approaches applied machine learning to offline guide partition, but could not explicitly explore the law between partition and performance. In this paper, we build a parametric model (Qinling) with a multiple regression method to discover the inherent law between thread partition and performance. The paper firstly extracts unpredictable parameters that determine the performance of thread partition in SpMT; secondly, we build a parametric model Qinling with extracted parameters and speedups, and train Qinling offline, as well as apply it to predict the theoretical speedups of unseen applications. Finally, validation is done. Prophet, which consists of an automatic parallelization compiler and a multi-core simulator, is used to obtain real speedups of the input programs. Olden and SPEC2000 benchmarks are used to train and validate the parametric model. Experiments show that Qinling delivers a good performance to predict speedups of unseen programs, and provides feedback guidance for Prophet to obtain the optimal partition parameters. Full article
(This article belongs to the Special Issue Advanced in Artificial Intelligence and Cloud Computing)
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Article
NS-k-NN: Neutrosophic Set-Based k-Nearest Neighbors Classifier
Symmetry 2017, 9(9), 179; https://doi.org/10.3390/sym9090179 - 02 Sep 2017
Cited by 29 | Viewed by 2612
Abstract
k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training [...] Read more.
k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for improving its precision. The neutrosophic set (NS) defines three memberships namely T, I and F. T, I, and F shows the truth membership degree, the false membership degree, and the indeterminacy membership degree, respectively. In this paper, the NS memberships are adopted to improve the classification performance of the k-NN classifier. A new straightforward k-NN approach is proposed based on NS theory. It calculates the NS memberships based on a supervised neutrosophic c-means (NCM) algorithm. A final belonging membership U is calculated from the NS triples as U = T + I F . A similar final voting scheme as given in fuzzy k-NN is considered for class label determination. Extensive experiments are conducted to evaluate the proposed method’s performance. To this end, several toy and real-world datasets are used. We further compare the proposed method with k-NN, fuzzy k-NN, and two weighted k-NN schemes. The results are encouraging and the improvement is obvious. Full article
(This article belongs to the Special Issue Neutrosophic Theories Applied in Engineering)
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Article
A Sparse Signal Reconstruction Method Based on Improved Double Chains Quantum Genetic Algorithm
Symmetry 2017, 9(9), 178; https://doi.org/10.3390/sym9090178 - 02 Sep 2017
Cited by 2 | Viewed by 2288
Abstract
This paper proposes a novel method of sparse signal reconstruction, which combines the improved double chains quantum genetic algorithm (DCQGA) and the orthogonal matching pursuit algorithm (OMP). Firstly, aiming at the problems of the slow convergence speed and poor robustness of traditional DCQGA, [...] Read more.
This paper proposes a novel method of sparse signal reconstruction, which combines the improved double chains quantum genetic algorithm (DCQGA) and the orthogonal matching pursuit algorithm (OMP). Firstly, aiming at the problems of the slow convergence speed and poor robustness of traditional DCQGA, we propose an improved double chains quantum genetic algorithm (IDCQGA). The main innovations contain three aspects: (1) a high density quantum encoding method is presented to reduce the searching space and increase the searching density of the algorithm; (2) the adaptive step size factor is introduced in the chromosome updating, which changes the step size with the gradient of the objective function at the search points; (3) the quantum π / 6 -gate is proposed in chromosome mutation to overcome the deficiency of the traditional NOT-gate mutation with poor performance to increase the diversity of the population. Secondly, for the problem of the OMP algorithm not being able to reconstruct precisely the effective sparse signal in noisy environments, a fidelity orthogonal matching pursuit (FOMP) algorithm is proposed. Finally, the IDCQGA-based OMP and FOMP algorithms are applied to the sparse signal decomposition, and the simulation results show that the proposed algorithms can improve the convergence speed and reconstruction precision compared with other methods in the experiments. Full article
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Article
On Characterizations of Directional Derivatives and Subdifferentials of Fuzzy Functions
Symmetry 2017, 9(9), 177; https://doi.org/10.3390/sym9090177 - 01 Sep 2017
Viewed by 1408
Abstract
In this paper, based on a partial order, we study the characterizations of directional derivatives and the subdifferential of fuzzy function. At the same time, we also discuss the relation between the directional derivative and the subdifferential. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
Article
Parallelization of Modified Merge Sort Algorithm
Symmetry 2017, 9(9), 176; https://doi.org/10.3390/sym9090176 - 01 Sep 2017
Cited by 25 | Viewed by 4300
Abstract
Modern architectures make possible development in new algorithms for large data sets and distributed computing. The newly proposed versions can benefit both from faster computing on the multi core architectures, and intelligent programming techniques that use efficient procedures available in the latest programming [...] Read more.
Modern architectures make possible development in new algorithms for large data sets and distributed computing. The newly proposed versions can benefit both from faster computing on the multi core architectures, and intelligent programming techniques that use efficient procedures available in the latest programming studios. Frequently used algorithms to sort arrays of data in NoSQL databases is merge sort, where as NoSQL we understand any database without typical SQL programming interpreter. The author describes how to use the parallelization of the sorting processes for the modified method of sorting by merging for large data sets. The subject of this research is the claim that the parallelization of the sorting method is faster and beneficial for multi-core systems. Presented results show how the number of processors influences the sorting performance. The results are presented in theoretical assumptions and confirmed in practical benchmark tests. The method is compared to other sorting methods like quick sort, heap sort, and merge sort to show potential efficiency. Full article
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Article
The Orthogonality between Complex Fuzzy Sets and Its Application to Signal Detection
Symmetry 2017, 9(9), 175; https://doi.org/10.3390/sym9090175 - 31 Aug 2017
Cited by 25 | Viewed by 1869
Abstract
A complex fuzzy set is a set whose membership values are vectors in the unit circle in the complex plane. This paper establishes the orthogonality relation of complex fuzzy sets. Two complex fuzzy sets are said to be orthogonal if their membership vectors [...] Read more.
A complex fuzzy set is a set whose membership values are vectors in the unit circle in the complex plane. This paper establishes the orthogonality relation of complex fuzzy sets. Two complex fuzzy sets are said to be orthogonal if their membership vectors are perpendicular. We present the basic properties of orthogonality of complex fuzzy sets and various results on orthogonality with respect to complex fuzzy complement, complex fuzzy union, complex fuzzy intersection, and complex fuzzy inference methods. Finally, an example application of signal detection demonstrates the utility of the orthogonality of complex fuzzy sets. Full article
(This article belongs to the Special Issue Fuzzy Sets Theory and Its Applications)
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Review
Chiral Buckybowl Molecules
Symmetry 2017, 9(9), 174; https://doi.org/10.3390/sym9090174 - 30 Aug 2017
Cited by 9 | Viewed by 5828
Abstract
Buckybowls are polynuclear aromatic hydrocarbons that have a curved aromatic surface and are considered fragments of buckminsterfullerenes. The curved aromatic surface led to the loss of planar symmetry of the normal aromatic plane and may cause unique inherent chirality, so-called bowl chirality, which [...] Read more.
Buckybowls are polynuclear aromatic hydrocarbons that have a curved aromatic surface and are considered fragments of buckminsterfullerenes. The curved aromatic surface led to the loss of planar symmetry of the normal aromatic plane and may cause unique inherent chirality, so-called bowl chirality, which it is possible to thermally racemize through a bowl-to-bowl inversion process. In this short review, we summarize the studies concerning the special field of bowl chirality, focusing on recent practical aspects of attaining diastereo/enantioenriched chiral buckybowls through asymmetric synthesis, chiral optical resolution, selective chiral metal complexation, and chiral assembly formation. Full article
(This article belongs to the Special Issue Chiral Auxiliaries and Chirogenesis)
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Article
Constructions of Helicoidal Surfaces in Euclidean Space with Density
Symmetry 2017, 9(9), 173; https://doi.org/10.3390/sym9090173 - 28 Aug 2017
Cited by 9 | Viewed by 3391
Abstract
Our principal goal is to study the prescribed curvature problem in a manifold with density. In particular, we consider the Euclidean 3-space R3 with a positive density function eϕ, where ϕ=-x2-y2, [...] Read more.
Our principal goal is to study the prescribed curvature problem in a manifold with density. In particular, we consider the Euclidean 3-space R 3 with a positive density function e ϕ , where ϕ = - x 2 - y 2 , ( x , y , z ) R 3 and construct all the helicoidal surfaces in the space by solving the second-order non-linear ordinary differential equation with the weighted Gaussian curvature and the mean curvature functions. As a result, we give a classification of weighted minimal helicoidal surfaces as well as examples of helicoidal surfaces with some weighted Gaussian curvature and mean curvature functions in the space. Full article
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Article
Endpoint Security in Networks: An OpenMP Approach for Increasing Malware Detection Speed
Symmetry 2017, 9(9), 172; https://doi.org/10.3390/sym9090172 - 27 Aug 2017
Cited by 2 | Viewed by 2227
Abstract
Increasingly sophisticated antivirus (AV) software and the growing amount and complexity of malware demand more processing power from personal computers, specifically from the central processor unit (CPU). This paper conducted performance tests with Clam AntiVirus (ClamAV) and improved its performance through parallel processing [...] Read more.
Increasingly sophisticated antivirus (AV) software and the growing amount and complexity of malware demand more processing power from personal computers, specifically from the central processor unit (CPU). This paper conducted performance tests with Clam AntiVirus (ClamAV) and improved its performance through parallel processing on multiple cores using the Open Multi-Processing (OpenMP) library. All the tests used the same dataset constituted of 1.33 GB of data distributed among 2766 files of different sizes. The new parallel version of ClamAV implemented in our work achieved an execution time around 62% lower than the original software version, reaching a speedup of 2.6 times faster. The main contribution of this work is to propose and implement a new version of the ClamAV antivirus using parallel processing with OpenMP, easily portable to a variety of hardware platforms and operating systems. Full article
(This article belongs to the Special Issue Symmetry in Secure Cyber World)
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Article
A Security Generic Service Interface of Internet of Things (IoT) Platforms
Symmetry 2017, 9(9), 171; https://doi.org/10.3390/sym9090171 - 26 Aug 2017
Cited by 5 | Viewed by 3053
Abstract
Internet of Things (IoT) platforms are the key for the development of scalable IoT applications and services that connect real and virtual worlds between objects, systems, and people. However, as the IoT platform market represents a truly new market segment that was almost [...] Read more.
Internet of Things (IoT) platforms are the key for the development of scalable IoT applications and services that connect real and virtual worlds between objects, systems, and people. However, as the IoT platform market represents a truly new market segment that was almost non-existent a few years ago, the platforms are complex and changing quickly. These IoT platforms perform simple functions such as providing useful information, and others can provide services through collaborations with IoT devices. This situation needs a generic service interface, and results in a range of IoT architectures through not only the configuration setting of IoT devices and resources but also the varied environments of collaboration of each device. Due to these heterogeneities, it is quite challenging to develop applications working with diverse IoT services, and it is even more difficult to maintain such applications. Therefore, this paper presents a security generic service interface with the effective common characteristics of an IoT platform by defining a set of generic interfaces and adopting well-known design patterns. The generic interface solves the heterogeneity-driven problems and makes it possible to effectively adopt a platform-independent Generic Interface that could be operated in diverse IoT platforms. Full article
(This article belongs to the Special Issue Symmetry in Secure Cyber World)
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Article
Enantiomeric Separation of Tramadol and Its Metabolites: Method Validation and Application to Environmental Samples
Symmetry 2017, 9(9), 170; https://doi.org/10.3390/sym9090170 - 24 Aug 2017
Cited by 6 | Viewed by 3218
Abstract
The accurate assessment of racemic pharmaceuticals requires enantioselective analytical methods. This study presents the development and validation of an enantioselective liquid chromatography with a fluorescence detection method for the concomitant quantification of the enantiomers of tramadol and their metabolites, N-desmethyltramadol and O [...] Read more.
The accurate assessment of racemic pharmaceuticals requires enantioselective analytical methods. This study presents the development and validation of an enantioselective liquid chromatography with a fluorescence detection method for the concomitant quantification of the enantiomers of tramadol and their metabolites, N-desmethyltramadol and O-desmethyltramadol, in wastewater samples. Optimized conditions were achieved using a Lux Cellulose-4 column 150 × 4.6 mm, 3 µm isocratic elution, and 0.1% diethylamine in hexane and ethanol (96:4, v/v) at 0.7 mL min−1. The samples were extracted using 150 mg Oasis® mixed-mode cation exchange (MCX) cartridges. The method was validated using a synthetic effluent of a laboratory-scale aerobic granular sludge sequencing batch reactor. The method demonstrated to be selective, accurate, and linear (r2 > 0.99) over the range of 56 ng L−1 to 392 ng L−1. The detection and the quantification limits of each enantiomer were 8 ng L−1 and 28 ng L−1 for tramadol and N-desmethyltramadol, and 20 ng L−1 and 56 ng L−1 for O-desmethyltramadol. The feasibility of the method was demonstrated in a screening study in influent and effluent samples from a wastewater treatment plant. The results demonstrated the occurrence of tramadol enantiomers up to 325.1 ng L−1 and 357.9 ng L−1, in the effluent and influent samples, respectively. Both metabolites were detected in influents and effluents. Full article
(This article belongs to the Special Issue Chiral Separations)
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Article
An Extended VIKOR Method Using Intuitionistic Fuzzy Sets and Combination Weights for Supplier Selection
Symmetry 2017, 9(9), 169; https://doi.org/10.3390/sym9090169 - 24 Aug 2017
Cited by 49 | Viewed by 2966
Abstract
Supplier selection is a complex multiple criteria decision-making (MCDM) problem, which considers a number of alternative suppliers as well as conflicting and noncommensurable criteria. Considering the fact that it is difficult to precisely determine criteria weights and the ratings of alternatives on each [...] Read more.
Supplier selection is a complex multiple criteria decision-making (MCDM) problem, which considers a number of alternative suppliers as well as conflicting and noncommensurable criteria. Considering the fact that it is difficult to precisely determine criteria weights and the ratings of alternatives on each criterion in real-life situations, the VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) method has been modified for intuitionistic fuzzy data in this study for supplier evaluation and selection. Further, we take into account both subjective and objective weights of criteria in the decision-making process, as most supplier selection approaches consider only subjective criteria weights. Finally, two supplier selection examples are provided to illustrate the proposed intuitionistic fuzzy hybrid VIKOR (IFH-VIKOR) method, and its merits are highlighted by comparing it with other relevant approaches. Full article
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Article
An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization
Symmetry 2017, 9(9), 168; https://doi.org/10.3390/sym9090168 - 23 Aug 2017
Cited by 21 | Viewed by 2428
Abstract
Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a [...] Read more.
Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a more classical approach—the trend-following algorithm. During the experiments historical data from the Warsaw Stock Exchange is used in order to assess the performance of the compared algorithms. Finally, we draw some conclusions from these experiments, showing the strong and weak points of all the techniques. Full article
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