Symmetry doi: 10.3390/sym9100244

Authors: Kun Lan Simon Fong Wei Song Athanasios Vasilakos Richard Millham

Over the years, advanced IT technologies have facilitated the emergence of new ways of generating and gathering data rapidly, continuously, and largely and are associated with a new research and application branch, namely, data stream mining (DSM). Among those multiple scenarios of DSM, the Internet of Things (IoT) plays a significant role, with a typical meaning of a tough and challenging computational case of big data. In this paper, we describe a self-adaptive approach to the pre-processing step of data stream classification. The proposed algorithm allows different divisions with both variable numbers and lengths of sub-windows under a whole sliding window on an input stream, and clustering-based particle swarm optimization (CPSO) is adopted as the main metaheuristic search method to guarantee that its stream segmentations are effective and adaptive to itself. In order to create a more abundant search space, statistical feature extraction (SFX) is applied after variable partitions of the entire sliding window. We validate and test the effort of our algorithm with other temporal methods according to several IoT environmental sensor monitoring datasets. The experiments yield encouraging outcomes, supporting the reality that picking significant appropriate variant sub-window segmentations heuristically with an incorporated clustering technique merit would allow these to perform better than others.

]]>Symmetry doi: 10.3390/sym9100243

Authors: Michael Lewis

Facial symmetry is believed to have an evolutionary significance and so its detection should be robust in natural settings. Previous studies of facial symmetry detection have used front views of faces where the decision could be made on 2D image properties rather than 3D facial properties. These studies also employed comparative judgements, which could be influenced by attractiveness rather than symmetry. Two experiments explored the ability to detect typical levels of 3D facial asymmetry (contrasted with wholly symmetrical faces) from 2D projections of faces. Experiment 1 showed that asymmetry detection was impaired by inversion but even more impaired by 90 degrees rotation demonstrating the importance of the vertical reflection. Asymmetry detection was also reduced by yaw rotation of the head but still above-chance at 30 degrees rotation. Experiment 2 explored the effect of asymmetrical lighting and yaw rotation up to 45 degrees. Detection of asymmetry was affected by asymmetrical lighting and yaw rotation in a non-additive manner. The results are discussed in terms of the special role that faces and vertical symmetry play in visual perception.

]]>Symmetry doi: 10.3390/sym9100240

Authors: Peter Trusov Kirill Ostapovich

The products made by the forming of polycrystalline metals and alloys, which are in high demand in modern industries, have pronounced inhomogeneous distribution of grain orientations. The presence of specific orientation modes in such materials, i.e., crystallographic texture, is responsible for anisotropy of their physical and mechanical properties, e.g., elasticity. A type of anisotropy is usually unknown a priori, and possible ways of its determination is of considerable interest both from theoretical and practical viewpoints. In this work, emphasis is placed on the identification of elasticity classes of polycrystalline materials. By the newly introduced concept of “elasticity class” the union of congruent tensor subspaces of a special form is understood. In particular, it makes it possible to consider the so-called symmetry classification, which is widely spread in solid mechanics. The problem of identification of linear elasticity class for anisotropic material with elastic moduli given in an arbitrary orthonormal basis is formulated. To solve this problem, a general procedure based on constructing the hierarchy of approximations of elasticity tensor in different classes is formulated. This approach is then applied to analyze changes in the elastic symmetry of a representative volume element of polycrystalline copper during numerical experiments on severe plastic deformation. The microstructure evolution is described using a two-level crystal elasto-visco-plasticity model. The well-defined structures, which are indicative of the existence of essentially inhomogeneous distribution of crystallite orientations, were obtained in each experiment. However, the texture obtained in the quasi-axial upsetting experiment demonstrates the absence of significant macroscopic elastic anisotropy. Using the identification framework, it has been shown that the elasticity tensor corresponding to the resultant microstructure proves to be almost isotropic.

]]>Symmetry doi: 10.3390/sym9100241

Authors: Hisham Shehadeh Mohd ldris Ismail Ahmedy

In this paper, we propose an extended multi-objective version of single objective optimization algorithm called sperm swarm optimization algorithm. The proposed multi-objective optimization algorithm based on sperm fertilization procedure (MOSFP) operates based on Pareto dominance and a crowding factor, that crowd and filter out the list of the best sperms (global best values). We divide the sperm swarm into three equal parts, after that, different types of turbulence (mutation) operators are applied on these parts, such as uniform mutation, non-uniform mutation, and without any mutation. Our algorithm is compared against three well-known algorithms in the field of optimization. These algorithms are NSGA-II, SPEA2, and OMOPSO. These algorithms are compared using a very popular benchmark function suites called Zitzler-Deb-Thiele (ZDT) and Walking-Fish-Group (WFG). We also adopt three quality metrics to compare the convergence, accuracy, and diversity of these algorithms, including, inverted generational distance (IGD), spread (SP), and epsilon (∈). The experimental results show that the performance of the proposed MOSFP is highly competitive, which outperformed OMOPSO in solving problems such as ZDT3, WFG5, and WFG8. In addition, the proposed MOSFP outperformed both of NSGA-II or SPEA2 algorithms in solving all the problems.

]]>Symmetry doi: 10.3390/sym9100239

Authors: Zhuxin Xue Qing Dong Xiangtao Fan Qingwen Jin Hongdeng Jian Jian Liu

Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN) personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

]]>Symmetry doi: 10.3390/sym9100242

Authors: Ying-Hao Hung Yuh-Min Tseng Sen-Shan Huang

Certificateless signatures (CLS) are noticeable because they may resolve the key escrow problem in ID-based signatures and break away the management problem regarding certificate in conventional signatures. However, the security of the mostly previous CLS schemes relies on the difficulty of solving discrete logarithm or large integer factorization problems. These two problems would be solved by quantum computers in the future so that the signature schemes based on them will also become insecure. For post-quantum cryptography, lattice-based cryptography is significant due to its efficiency and security. However, no study on addressing the revocation problem in the existing lattice-based CLS schemes is presented. In this paper, we focus on the revocation issue and present the first revocable CLS (RCLS) scheme over lattices. Based on the short integer solution (SIS) assumption over lattices, the proposed lattice-based RCLS scheme is shown to be existential unforgeability against adaptive chosen message attacks. By performance analysis and comparisons, the proposed lattice-based RCLS scheme is better than the previously proposed lattice-based CLS scheme, in terms of private key size, signature length and the revocation mechanism.

]]>Symmetry doi: 10.3390/sym9100237

Authors: Raúl Parada Daniel Cárdenes-Tacoronte Carlos Monzo Joan Melià-Seguí

The number of connected devices is increasing worldwide. Not only in contexts like the Smart City, but also in rural areas, to provide advanced features like smart farming or smart logistics. Thus, wireless network technologies to efficiently allocate Internet of Things (IoT) and Machine to Machine (M2M) communications are necessary. Traditional cellular networks like Global System for Mobile communications (GSM) are widely used worldwide for IoT environments. Nevertheless, Low Power Wide Area Networks (LP-WAN) are becoming widespread as infrastructure for present and future IoT and M2M applications. Based also on a subscription service, the LP-WAN technology SIGFOXTM may compete with cellular networks in the M2M and IoT communications market, for instance in those projects where deploying the whole communications infrastructure is too complex or expensive. For decision makers to decide the most suitable technology for each specific application, signal coverage is within the key features. Unfortunately, besides simulated coverage maps, decision-makers do not have real coverage maps for SIGFOXTM, as they can be found for cellular networks. Thereby, we propose Internet of THings Area Coverage Analyzer (ITHACA), a signal analyzer prototype to provide automated signal coverage maps and analytics for LP-WAN. Experiments performed in the Gran Canaria Island, Spain (with both urban and complex topographic rural environments), returned a real SIGFOXTM service availability above 97% and above 11% more coverage with respect to the company-provided simulated maps. We expect that ITHACA may help decision makers to deploy the most suitable technologies for future IoT and M2M projects.

]]>Symmetry doi: 10.3390/sym9100236

Authors: Soohyun Cho

This paper presents an automatic modulation and coding scheme (MCS) level adaptation algorithm to embrace Internet of Things (IoT) devices by improving the area spectral efficiency of carrier-sense multiple access with collision avoidance (CSMA/CA) wireless networks. In the proposed algorithm, senders of CSMA/CA wireless networks use the signal to interference plus noise ratio of acknowledgment frames from their receivers to estimate channel statuses between the senders and the receivers. Using the estimated channel status of each receiver, senders control sending rates of traffic by adjusting MCS levels of packets destined for each receiver. We use Poisson point processes (PPPs) to model the locations of participating nodes (i.e., access points and wireless devices) in a given area. We evaluate the effectiveness of the proposed algorithm using an event-driven ns-2 simulator for various PPP densities of access points and wireless devices.

]]>Symmetry doi: 10.3390/sym9100235

Authors: Yanhui Guo Ümit Budak Abdulkadir Şengür Florentin Smarandache

A fundus image is an effective tool for ophthalmologists studying eye diseases. Retinal vessel detection is a significant task in the identification of retinal disease regions. This study presents a retinal vessel detection approach using shearlet transform and indeterminacy filtering. The fundus image’s green channel is mapped in the neutrosophic domain via shearlet transform. The neutrosophic domain images are then filtered with an indeterminacy filter to reduce the indeterminacy information. A neural network classifier is employed to identify the pixels whose inputs are the features in neutrosophic images. The proposed approach is tested on two datasets, and a receiver operating characteristic curve and the area under the curve are employed to evaluate experimental results quantitatively. The area under the curve values are 0.9476 and 0.9469 for each dataset respectively, and 0.9439 for both datasets. The comparison with the other algorithms also illustrates that the proposed method yields the highest evaluation measurement value and demonstrates the efficiency and accuracy of the proposed method.

]]>Symmetry doi: 10.3390/sym9100238

Authors: Xiuli Qi Chengxiang Yin Kai Cheng Xianglin Liao

Aiming at combining the good characteristics of a differential scale in representing human cognition and the favorable properties of interval judgments in expressing decision-makers’ uncertainty, this paper proposes the interval cognitive network process (I-CNP) to extend the primitive cognition network process (P-CNP) to handle interval judgments. The key points of I-CNP include a consistency definition for an interval pairwise opposite matrix (IPOM) and a method to derive interval utilities from an IPOM. This paper defines a feasible region-based consistency definition and a transitivity based consistency definition for an IPOM. Both of the two definitions are equivalent to the consistency definition for a crisp pairwise opposite matrix (POM) when an IPOM is reduced to a POM. Two methods that are able to derive interval utilities from both consistent and inconsistent IPOMs are developed based on the two definitions. Four numerical examples are used to illustrate the proposed methods and to compare I-CNP to interval analytic hierarchy process (IAHP). The results show that I-CNP reflects the decision-makers’ cognition better, and that the suggestions provided by I-CNP are more convincing. I-CNP provides new useful alternative tools for multi-attribute decision-making problems.

]]>Symmetry doi: 10.3390/sym9100234

Authors: Liang Wang Álvaro Labella Rosa M. Rodríguez Ying-Ming Wang Luis Martínez

After an emergency event (EE) happens, emergency decision making (EDM) is a common and effective way to deal with the emergency situation, which plays an important role in mitigating its level of harm. In the real world, it is a big challenge for an individual emergency manager (EM) to make a proper and comprehensive decision for coping with an EE. Consequently, many practical EDM problems drive group emergency decision making (GEDM) problems whose main limitations are related to the lack of flexibility in knowledge elicitation, disagreements in the group and the consideration of experts’ psychological behavior in the decision process. Hence, this paper proposes a novel GEDM approach that allows more flexibility for preference elicitation under uncertainty, provides a consensus process to avoid disagreements and considers experts’ psychological behavior by using the fuzzy TODIM method based on prospect theory. Eventually, a group decision support system (GDSS) is developed to support the whole GEDM process defined in the proposed method demonstrating its novelty, validity and feasibility.

]]>Symmetry doi: 10.3390/sym9100232

Authors: Matthew Mahowald

A conjecture of Aganagic and Vafa relates the open Gromov-Witten theory of X = O P 1 ( − 1 , − 1 ) to the augmentation polynomial of Legendrian contact homology. We describe how to use this conjecture to compute genus zero, one boundary component open Gromov-Witten invariants for Lagrangian submanifolds L K ⊂ X obtained from the conormal bundles of knots K ⊂ S 3 . This computation is then performed for two non-toric examples (the figure-eight and three-twist knots). For ( r , s ) torus knots, the open Gromov-Witten invariants can also be computed using Atiyah-Bott localization. Using this result for the unknot and the ( 3 , 2 ) torus knot, we show that the augmentation polynomial can be derived from these open Gromov-Witten invariants.

]]>Symmetry doi: 10.3390/sym9100231

Authors: Yidong Xu Wei Xue Yingsong Li Lili Guo Wenjing Shang

A novel localization method based on multiple signal classification (MUSIC) algorithm is proposed for positioning an electric dipole source in a confined underwater environment by using electric dipole-receiving antenna array. In this method, the boundary element method (BEM) is introduced to analyze the boundary of the confined region by use of a matrix equation. The voltage of each dipole pair is used as spatial-temporal localization data, and it does not need to obtain the field component in each direction compared with the conventional fields based localization method, which can be easily implemented in practical engineering applications. Then, a global-multiple region-conjugate gradient (CG) hybrid search method is used to reduce the computation burden and to improve the operation speed. Two localization simulation models and a physical experiment are conducted. Both the simulation results and physical experiment result provide accurate positioning performance, with the help to verify the effectiveness of the proposed localization method in underwater environments.

]]>Symmetry doi: 10.3390/sym9100233

Authors: Sooyoung Kang Seungjoo Kim

In the new era of IoT (Internet of Things), numerous gadgets and services include innovative IoT technologies that provide customers with convenience and improve their quality of life. Smart TVs are typical IoT devices that offer broadcasting services. However, they are susceptible to security intrusions via e-mail, media players, cameras, and internet connectivity. The frequency of hacking through malicious applications installed in Smart TV has rapidly increased. Therefore, appropriate countermeasures should be developed immediately. In April 2017, we (with LG electronics) received the ‘world-first’ Common Criteria EAL2 (Evaluation Assurance Level 2) certification for Smart TVs. As far as we know, no Smart TV has received a Common Criteria EAL2 security certification until now. This article describes our experience with the certification process and examines several security and reliability aspects of Smart TVs.

]]>Symmetry doi: 10.3390/sym9100230

Authors: Robert Bluhm

An overview is given of effective gravitational field theories with fixed background fields that break spacetime symmetry. The behavior of the background fields and the types of excitations that can occur depend on whether the symmetry breaking is explicit or spontaneous. For example, when the breaking is spontaneous, the background field is dynamical and massless Nambu–Goldstone and massive Higgs excitations can appear. However, if the breaking is explicit, the background is nondynamical, and in this case additional metric or vierbein excitations occur due to the loss of local symmetry, or these excitations can be replaced by dynamical scalar fields using a Stückelberg approach. The interpretation of Noether identities that must hold in each case differs, depending on the type of symmetry breaking, and this affects the nature of the consistency conditions that must hold. The Noether identities also shed light on why the Stückelberg approach works, and how it is able to restore the broken spacetime symmetry in a theory with explicit breaking.

]]>Symmetry doi: 10.3390/sym9100229

Authors: Yingsong Li Yanyan Wang Felix Albu Jingshan Jiang

A general zero attraction (GZA) proportionate normalized maximum correntropy criterion (GZA-PNMCC) algorithm is devised and presented on the basis of the proportionate-type adaptive filter techniques and zero attracting theory to highly improve the sparse system estimation behavior of the classical MCC algorithm within the framework of the sparse system identifications. The newly-developed GZA-PNMCC algorithm is carried out by introducing a parameter adjusting function into the cost function of the typical proportionate normalized maximum correntropy criterion (PNMCC) to create a zero attraction term. The developed optimization framework unifies the derivation of the zero attraction-based PNMCC algorithms. The developed GZA-PNMCC algorithm further exploits the impulsive response sparsity in comparison with the proportionate-type-based NMCC algorithm due to the GZA zero attraction. The superior performance of the GZA-PNMCC algorithm for estimating a sparse system in a non-Gaussian noise environment is proven by simulations.

]]>Symmetry doi: 10.3390/sym9100228

Authors: Hui-Chin Tang

In fuzzy decision problems, the ordering of fuzzy numbers is the basic problem. The fuzzy preference relation is the reasonable representation of preference relations by a fuzzy membership function. This paper studies Nakamura’s and Kołodziejczyk’s preference relations. Eight cases, each representing different levels of overlap between two triangular fuzzy numbers are considered. We analyze the ranking behaviors of all possible combinations of the decomposition and intersection of two fuzzy numbers through eight extensive test cases. The results indicate that decomposition and intersection can affect the fuzzy preference relations, and thereby the final ranking of fuzzy numbers.

]]>Symmetry doi: 10.3390/sym9100227

Authors: Stevo Stević

By using some solvability methods and the contraction mapping principle are investigated bounded, as well as periodic solutions to some classes of nonhomogeneous linear second-order difference equations on domains N 0 , Z ∖ N 2 and Z . The case when the coefficients of the equation are constant and the zeros of the characteristic polynomial associated to the corresponding homogeneous equation do not belong to the unit circle is described in detail.

]]>Symmetry doi: 10.3390/sym9100225

Authors: Mohamed Azzouz

Had magnetic monopoles been ubiquitous as electrons are, we would probably have had a different form of matter, and power plants based on currents of these magnetic charges would have been a familiar scene of modern technology. Magnetic dipoles do exist, however, and in principle one could wonder if we can use them to generate magnetic currents. In the present work, we address the issue of generating magnetic currents and magnetic thermal currents in electrically-insulating low-dimensional Heisenberg antiferromagnets by invoking the (broken) electricity-magnetism duality symmetry. The ground state of these materials is a spin-liquid state that can be described well via the Jordan–Wigner fermions, which permit an easy definition of the magnetic particle and thermal currents. The magnetic and magnetic thermal conductivities are calculated in the present work using the bond–mean field theory. The spin-liquid states in these antiferromagnets are either gapless or gapped liquids of spinless fermions whose flow defines a current just as the one defined for electrons in a Fermi liquid. The driving force for the magnetic current is a magnetic field with a gradient along the magnetic conductor. We predict the generation of a magneto-motive force and realization of magnetic circuits using low-dimensional Heisenberg antiferromagnets. The present work is also about claiming that what the experiments in spintronics attempt to do is trying to treat the magnetic degrees of freedoms on the same footing as the electronic ones.

]]>Symmetry doi: 10.3390/sym9100224

Authors: Bo Hu Lvqing Bi Sizhao Li Songsong Dai

We introduce a new class of operations called asymmetric equivalences. Several properties of asymmetric equivalence operations have been investigated. Based on the asymmetric equivalence, quasi-metric spaces are constructed on [0, 1]. Finally, we discuss symmetrization of asymmetric equivalences.

]]>Symmetry doi: 10.3390/sym9100226

Authors: Louis Kauffman Sofia Lambropoulou

We present the new skein invariants of classical links, H [ H ] , K [ K ] and D [ D ] , based on the invariants of links, H, K and D, denoting the regular isotopy version of the Homflypt polynomial, the Kauffman polynomial and the Dubrovnik polynomial. The invariants are obtained by abstracting the skein relation of the corresponding invariant and making a new skein algorithm comprising two computational levels: first producing unlinked knotted components, then evaluating the resulting knots. The invariants in this paper, were revealed through the skein theoretic definition of the invariants Θ d related to the Yokonuma–Hecke algebras and their 3-variable generalization Θ , which generalizes the Homflypt polynomial. H [ H ] is the regular isotopy counterpart of Θ . The invariants K [ K ] and D [ D ] are new generalizations of the Kauffman and the Dubrovnik polynomials. We sketch skein theoretic proofs of the well-definedness and topological properties of these invariants. The invariants of this paper are reformulated into summations of the generating invariants (H, K, D) on sublinks of the given link L, obtained by partitioning L into collections of sublinks. The first such reformulation was achieved by W.B.R. Lickorish for the invariant Θ and we generalize it to the Kauffman and Dubrovnik polynomial cases. State sum models are formulated for all the invariants. These state summation models are based on our skein template algorithm which formalizes the skein theoretic process as an analogue of a statistical mechanics partition function. Relationships with statistical mechanics models are articulated. Finally, we discuss physical situations where a multi-leveled course of action is taken naturally.

]]>Symmetry doi: 10.3390/sym9100223

Authors: Tzu-Chuen Lu Hui-Shih Leng

The concept of a dual-image based scheme in information sharing consists of concealing secret messages in two cover images; only someone who has both stego-images can extract the secret messages. In 2015, Lu et al. proposed a center-folding strategy where each secret symbol is folded into the reduced digit to reduce the distortion of the stego-image. Then, in 2016, Lu et al. used a frequency-based encoding strategy to reduce the distortion of the frequency of occurrence of the maximum absolute value. Because the folding strategy can obviously reduce the value, the proposed scheme includes the folding operation twice to further decrease the reduced digit. We use a frequency-based encoding strategy to encode a secret message and then use the block folding technique by performing the center-folding operation twice to embed secret messages. An indicator is needed to identify the sequence number of the folding operation. The proposed scheme collects several indicators to produce a combined code and hides the code in a pixel to reduce the size of the indicators. The experimental results show that the proposed method can achieve higher image quality under the same embedding rate or higher payload, which is better than other methods.

]]>Symmetry doi: 10.3390/sym9100222

Authors: Shengjie Qiang Bin Jia Qingxia Huang

Optimally organizing passengers boarding/deboarding an airplane offers a potential way to reduce the airplane turn time. The main contribution of our work is that we evaluate seven boarding strategies and two structured deboarding strategies by using a surrogate experimental test. Instead of boarding a real or mocked airplane, we carried out the experiment by organizing 40 participants to board a school bus with ten rows of four seats, symmetrically distributed on a single, central aisle. Experimental results confirm that the optimized strategies, i.e., Steffen and Steffen-lug, are superior to the traditional ones, i.e., Back-to-front, Window-to-aisle, and Random in time-saving and stability. However, the two structured deboarding strategies failed to reduce the deboarding time, and this result strongly suggests the prerequisites of applying such strategies only when, on average, passengers have a large amount of luggage. Besides, we further carried out a questionnaire survey of participants’ preferences on seat layout and discussed how those preferences influence the boarding time.

]]>Symmetry doi: 10.3390/sym9100221

Authors: Jiachen Xu Xiao Liu Ming Ma Anfeng Liu Tian Wang Changqin Huang

Cloud computing has emerged as today’s most exciting computing paradigm for providing services using a shared framework, which opens a new door for solving the problems of the explosive growth of digital resource demands and their corresponding convenience. With the exponential growth of the number of data types and data size in so-called big data work, the backbone network is under great pressure due to its transmission capacity, which is lower than the growth of the data size and would seriously hinder the development of the network without an effective approach to solve this problem. In this paper, an Intelligent Aggregation based on a Content Routing (IACR) scheme for cloud computing, which could reduce the amount of data in the network effectively and play a basic supporting role in the development of cloud computing, is first put forward. All in all, the main innovations in this paper are: (1) A framework for intelligent aggregation based on content routing is proposed, which can support aggregation based content routing; (2) The proposed IACR scheme could effectively route the high aggregation ratio data to the data center through the same routing path so as to effectively reduce the amount of data that the network transmits. The theoretical analyses experiments and results show that, compared with the previous original routing scheme, the IACR scheme can balance the load of the whole network, reduce the amount of data transmitted in the network by 41.8%, and reduce the transmission time by 31.6% in the same network with a more balanced network load.

]]>Symmetry doi: 10.3390/sym9100220

Authors: Muhammad Akram Tae Cho

Wireless sensor networks are supplied with limited energy resources and are usually installed in unattended and unfriendly environments. These networks are also highly exposed to security attacks aimed at draining the energy of the network to render it unresponsive. Adversaries launch counterfeit report injection attacks and false vote injection attacks through compromised sensor nodes. Several filtering solutions have been suggested for detecting and filtering false reports during the multi-hop forwarding process. However, almost all such schemes presuppose a conventional underlying protocol for data routing that do not consider the attack status or energy dissipation on the route. Each design provides approximately the equivalent resilience in terms of protection against compromised node. However, the energy consumption characteristics of each design differ. We propose a fuzzy adaptive path selection to save energy and avoid the emergence of favored paths. Fresh authentication keys are generated periodically, and these are shared with the filtering nodes to restrict compromised intermediate filtering nodes from the verification process. The scheme helps delay the emergence of hotspot problems near the base station and exhibits improved energy conserving behavior in wireless sensor networks. The proposed scheme provides an extended network lifetime and better false data filtering capacity.

]]>Symmetry doi: 10.3390/sym9100219

Authors: Ya-Fen Chen Yu-Jie Tan Cheng-Gang Shao

Local Lorentz invariance is an important component of General Relativity. Testing for Local Lorentz invariance can not only probe the foundation stone of General Relativity but also help to explore the unified theory for General Relativity and quantum mechanics. In this paper, we search the Local Lorentz invariance violation associated with operators of mass dimension d = 6 in the pure-gravity sector with short-range gravitational experiments. To enlarge the Local Lorentz invariance violation signal effectively, we design a new experiment in which the constraints of all fourteen violation coefficients may be improved by about one order of magnitude.

]]>Symmetry doi: 10.3390/sym9100218

Authors: Manuel Arrayás José Trueba

A class of vacuum electromagnetic fields in which the field lines are knotted curves are reviewed. The class is obtained from two complex functions at a particular instant t = 0 so they inherit the topological properties of red the level curves of these functions. We study the complete topological structure defined by the magnetic and electric field lines at t = 0 . This structure is not conserved in time in general, although it is possible to red find special cases in which the field lines are topologically equivalent for every value of t.

]]>Symmetry doi: 10.3390/sym9100217

Authors: Armando Martínez-Pérez Gabino Torres-Vega

We define a finite-differences derivative operation, on a non uniformly spaced partition, which has the exponential function as an exact eigenvector. We discuss some properties of this operator and we propose a definition for the components of a finite-differences momentum operator. This allows us to perform exact discrete calculations.

]]>Symmetry doi: 10.3390/sym9100216

Authors: Yan Guo Minxi Wang Xin Li

With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make e-commerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to get a list of original recommendation results. Combined with the customer’s feedback in an interactive manner, it then establishes the weights of corresponding recommendation algorithms. Finally, the synthetic formula of evidence theory is used to fuse the original results to obtain the final recommendation products. The recommendation performance of the proposed method is compared with that of traditional methods. The results of the experimental study through a Taobao online dress shop clearly show that the proposed method increases the efficiency of data mining in the consumer coverage, the consumer discovery accuracy and the recommendation recall. The hybrid recommendation algorithm complements the advantages of the existing recommendation algorithms in data mining. The interactive assigned-weight method meets consumer demand better and solves the problem of information overload. Meanwhile, our study offers important implications for e-commerce platform providers regarding the design of product recommendation systems.

]]>Symmetry doi: 10.3390/sym9100215

Authors: Cláudia Ribeiro Ana Ribeiro Alexandra Maia Maria Tiritan

In recent decades, the presence of micropollutants in the environment has been extensively studied due to their high frequency of occurrence, persistence and possible adverse effects to exposed organisms. Concerning chiral micropollutants in the environment, enantiomers are frequently ignored and enantiomeric composition often neglected. However, enantioselective toxicity is well recognized, highlighting the need to include enantioselectivity in environmental risk assessment. Additionally, the information about enantiomeric fraction (EF) is crucial since it gives insights about: (i) environmental fate (i.e., occurrence, distribution, removal processes and (bio)degradation); (ii) illicit discharges; (iii) consumption pattern (e.g., illicit drugs, pharmaceuticals used as recreational drugs, illicit use of pesticides); and (iv) enantioselective toxicological effects. Thus, the purpose of this paper is to provide a comprehensive review about the enantioselective occurrence of chiral bioactive compounds in aquatic environmental matrices. These include pharmaceuticals, illicit drugs, pesticides, polychlorinated biphenyls (PCBs) and polycyclic musks (PCMs). Most frequently analytical methods used for separation of enantiomers were liquid chromatography and gas chromatography methodologies using both indirect (enantiomerically pure derivatizing reagents) and direct methods (chiral stationary phases). The occurrence of these chiral micropollutants in the environment is reviewed and future challenges are outlined.

]]>Symmetry doi: 10.3390/sym9100214

Authors: Jolanta Dzwierzynska

The aim of this study is to develop an efficient and practical method of a direct mapping of a panoramic projection on an unfolded prism and pyramid polyhedral projection surface with the aid of a computer. Due to the fact that straight lines very often appear in any architectural form we formulate algorithms which utilize data about lines and draw panoramas as plots of functions in Mathcad software. The ability to draw panoramic images of lines enables drawing a wireframe image of an architectural object. The application of the multicenter projection, as well as the idea of shadow construction in the panoramic representation, aims at achieving a panoramic image close to human perception. The algorithms are universal as the application of changeable base elements of panoramic projection—horizon height, station point location, number of polyhedral walls—enables drawing panoramic images from various viewing positions. However, for more efficient and easier drawing, the algorithms should be implemented in some graphical package. The representation presented in the paper and the method of its direct mapping on a flat unfolded projection surface can find application in the presentation of architectural spaces in advertising and art when drawings are displayed on polyhedral surfaces and can be observed from multiple viewing positions.

]]>Symmetry doi: 10.3390/sym9100213

Authors: Enida Cero Jasmina Baraković Husić Sabina Baraković

The numerous and diverse applications of the Internet of Things (IoT) have the potential to change all areas of daily life of individuals, businesses, and society as a whole. The vision of a pervasive IoT spans a wide range of application domains and addresses the enabling technologies needed to meet the performance requirements of various IoT applications. In order to accomplish this vision, this paper aims to provide an analysis of literature in order to propose a new classification of IoT applications, specify and prioritize performance requirements of such IoT application classes, and give an insight into state-of-the-art technologies used to meet these requirements, all from telco’s perspective. A deep and comprehensive understanding of the scope and classification of IoT applications is an essential precondition for determining their performance requirements with the overall goal of defining the enabling technologies towards fifth generation (5G) networks, while avoiding over-specification and high costs. Given the fact that this paper presents an overview of current research for the given topic, it also targets the research community and other stakeholders interested in this contemporary and attractive field for the purpose of recognizing research gaps and recommending new research directions.

]]>Symmetry doi: 10.3390/sym9100212

Authors: Yaqing Liu Dantong Ouyang Yong Liu Rong Chen

With the trend of the increasing ageing population, more elderly people often encounter some problems in their daily lives. To enable these people to have more carefree lives, smart homes are designed to assist elderly people by recognizing their daily activities. Although different models and algorithms that use temporal and spatial features for activity recognition have been proposed, the rigid representations of these features damage the accuracy of activity recognition. In this paper, a two-stage approach is proposed to recognize the activities of a single resident. Firstly, in terms of temporal features, the approximate duration, start and end time are extracted from the activity records. Secondly, a set of activity records is clustered according to the records’ temporal features. Then, the classifiers are used to recognize the daily activities in each cluster according to the spatial features. Finally, two experiments are done to validate the recognition of daily activities in order to compare the proposed approach with a one-dimensional model. The results demonstrate that the proposed approach favorably outperforms the one-dimensional model. Two public datasets are used to evaluate the proposed approach. The experiment results show that the proposed approach achieves average accuracies of 80% and 89%, respectively.

]]>Symmetry doi: 10.3390/sym9100211

Authors: Zhe Tian Fushun Liu Zhixiong Li Reza Malekian Yingchun Xie

With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all these advanced technologies into a platform to meet the requirements of international and regional transportations. The purpose of this paper is to analyze how to benefit from the Internet of Vessels to improve the efficiency and safety of shipping, and promote the development of world transportation. In this paper, the IoV is introduced and its main architectures are outlined. Furthermore, the characteristics of the Internet of Vessels are described. Several important applications that illustrate the interaction of the Internet of Vessels’ components are proposed. Due to the development of the Internet of Vessels still being in its primary stage, challenges and prospects are identified and addressed. Finally, the main conclusions are drawn and future research priorities are provided for reference and as professional suggestions for future researchers in this field.

]]>Symmetry doi: 10.3390/sym9100210

Authors: Xiaowu Li Lin Wang Zhinan Wu Linke Hou Juan Liang Qiaoyang Li

Regarding the point projection and inversion problem, a classical algorithm for orthogonal projection onto curves and surfaces has been presented by Hu and Wallner (2005). The objective of this paper is to give a convergence analysis of the projection algorithm. On the point projection problem, we give a formal proof that it is second order convergent and independent of the initial value to project a point onto a planar parameter curve. Meantime, for the point inversion problem, we then give a formal proof that it is third order convergent and independent of the initial value.

]]>Symmetry doi: 10.3390/sym9100209

Authors: Zhuangbin Chen Ming Ma Xiao Liu Anfeng Liu Ming Zhao

With the development of smart devices and connection technologies, Wireless Sensor Networks (WSNs) are becoming increasingly intelligent. New or special functions can be obtained by receiving new versions of program codes to upgrade their software systems, forming the so-called smart Internet of Things (IoT). Due to the lossy property of wireless channels, data collection in WSNs still suffers from a long delay, high energy consumption, and many retransmissions. Thanks to wireless software-defined networks (WSDNs), software in sensors can now be updated to help them transmit data cooperatively, thereby achieving more reliable communication. In this paper, a Reliability Improved Cooperative Communication (RICC) data collection scheme is proposed to improve the reliability of random-network-coding-based cooperative communications in multi-hop relay WSNs without reducing the network lifetime. In WSNs, sensors in different positions can have different numbers of packets to handle, resulting in the unbalanced energy consumption of the network. In particular, nodes in non-hotspot areas have up to 90% of their original energy remaining when the network dies. To efficiently use the residual energy, in RICC, high data transmission power is adopted in non-hotspot areas to achieve a higher reliability at the cost of large energy consumption, and relatively low transmission power is adopted in hotspot areas to maintain the long network lifetime. Therefore, high reliability and a long network lifetime can be obtained simultaneously. The simulation results show that compared with other scheme, RICC can reduce the end-to-end Message Fail delivering Ratio (MFR) by 59.4%–62.8% under the same lifetime with a more balanced energy utilization.

]]>Symmetry doi: 10.3390/sym9100208

Authors: Jiqian Chen Jun Ye Shigui Du

In rock mechanics, the study of shear strength on the structural surface is crucial to evaluating the stability of engineering rock mass. In order to determine the shear strength, a key parameter is the joint roughness coefficient (JRC). To express and analyze JRC values, Ye et al. have proposed JRC neutrosophic numbers (JRC-NNs) and fitting functions of JRC-NNs, which are obtained by the classical statistics and curve fitting in the current method. Although the JRC-NNs and JRC-NN functions contain much more information (partial determinate and partial indeterminate information) than the crisp JRC values and functions in classical methods, the JRC functions and the JRC-NN functions may also lose some useful information in the fitting process and result in the function distortion of JRC values. Sometimes, some complex fitting functions may also result in the difficulty of their expressions and analyses in actual applications. To solve these issues, we can combine the neutrosophic numbers with neutrosophic statistics to realize the neutrosophic statistical analysis of JRC-NNs for easily analyzing the characteristics (scale effect and anisotropy) of JRC values. In this study, by means of the neutrosophic average values and standard deviations of JRC-NNs, rather than fitting functions, we directly analyze the scale effect and anisotropy characteristics of JRC values based on an actual case. The analysis results of the case demonstrate the feasibility and effectiveness of the proposed neutrosophic statistical analysis of JRC-NNs and can overcome the insufficiencies of the classical statistics and fitting functions. The main advantages of this study are that the proposed neutrosophic statistical analysis method not only avoids information loss but also shows its simplicity and effectiveness in the characteristic analysis of JRC.

]]>Symmetry doi: 10.3390/sym9100207

Authors: Shuang Guan Aiwu Zhao

Many of the existing autoregressive moving average (ARMA) forecast models are based on one main factor. In this paper, we proposed a new two-factor first-order ARMA forecast model based on fuzzy fluctuation logical relationships of both a main factor and a secondary factor of a historical training time series. Firstly, we generated a fluctuation time series (FTS) for two factors by calculating the difference of each data point with its previous day, then finding the absolute means of the two FTSs. We then constructed a fuzzy fluctuation time series (FFTS) according to the defined linguistic sets. The next step was establishing fuzzy fluctuation logical relation groups (FFLRGs) for a two-factor first-order autoregressive (AR(1)) model and forecasting the training data with the AR(1) model. Then we built FFLRGs for a two-factor first-order autoregressive moving average (ARMA(1,m)) model. Lastly, we forecasted test data with the ARMA(1,m) model. To illustrate the performance of our model, we used real Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Dow Jones datasets as a secondary factor to forecast TAIEX. The experiment results indicate that the proposed two-factor fluctuation ARMA method outperformed the one-factor method based on real historic data. The secondary factor may have some effects on the main factor and thereby impact the forecasting results. Using fuzzified fluctuations rather than fuzzified real data could avoid the influence of extreme values in historic data, which performs negatively while forecasting. To verify the accuracy and effectiveness of the model, we also employed our method to forecast the Shanghai Stock Exchange Composite Index (SHSECI) from 2001 to 2015 and the international gold price from 2000 to 2010.

]]>Symmetry doi: 10.3390/sym9100205

Authors: Ludwin Basilio Sergio Bermudo Jesús Leaños José Sigarreta

Let G = ( V , E ) be a simple graph with vertex set V and edge set E. Let D be a subset of V, and let B ( D ) be the set of neighbours of D in V ∖ D . The differential ∂ ( D ) of D is defined as | B ( D ) | − | D | . The maximum value of ∂ ( D ) taken over all subsets D ⊆ V is the differential ∂ ( G ) of G. For β ∈ ( − 1 , Δ ) , the β-differential ∂ β ( G ) of G is the maximum value of { | B ( D ) | − β | D | : D ⊆ V } . Motivated by an influential maximization problem, in this paper we study the β -differential of G.

]]>Symmetry doi: 10.3390/sym9100206

Authors: Carla Fernandes Maria Tiritan Madalena Pinto

Given the importance of chirality in the biological response, regulators, industries and researchers require chiral compounds in their enantiomeric pure form. Therefore, the approach to separate enantiomers in preparative scale needs to be fast, easy to operate, low cost and allow obtaining the enantiomers at high level of optical purity. A variety of methodologies to separate enantiomers in preparative scale is described, but most of them are expensive or with restricted applicability. However, the use of membranes have been pointed out as a promising methodology for scale-up enantiomeric separation due to the low energy consumption, continuous operability, variety of materials and supports, simplicity, eco-friendly and the possibility to be integrated into other separation processes. Different types of membranes (solid and liquid) have been developed and may provide applicability in multi-milligram and industrial scales. In this brief overview, the different types and chemical nature of membranes are described, showing their advantages and drawbacks. Recent applications of enantiomeric separations of pharmaceuticals, amines and amino acids were reported.

]]>Symmetry doi: 10.3390/sym9100204

Authors: Lorenz Demey Hans Smessaert

Aristotelian diagrams visualize the logical relations among a finite set of objects. These diagrams originated in philosophy, but recently, they have also been used extensively in artificial intelligence, in order to study (connections between) various knowledge representation formalisms. In this paper, we develop the idea that Aristotelian diagrams can be fruitfully studied as geometrical entities. In particular, we focus on four polyhedral Aristotelian diagrams for the Boolean algebra B 4 , viz. the rhombic dodecahedron, the tetrakis hexahedron, the tetraicosahedron and the nested tetrahedron. After an in-depth investigation of the geometrical properties and interrelationships of these polyhedral diagrams, we analyze the correlation (or lack thereof) between logical (Hamming) and geometrical (Euclidean) distance in each of these diagrams. The outcome of this analysis is that the Aristotelian rhombic dodecahedron and tetrakis hexahedron exhibit the strongest degree of correlation between logical and geometrical distance; the tetraicosahedron performs worse; and the nested tetrahedron has the lowest degree of correlation. Finally, these results are used to shed new light on the relative strengths and weaknesses of these polyhedral Aristotelian diagrams, by appealing to the congruence principle from cognitive research on diagram design.

]]>Symmetry doi: 10.3390/sym9100203

Authors: Dawid Połap Marcin Woz´niak

In the proposed article, we present a nature-inspired optimization algorithm, which we called Polar Bear Optimization Algorithm (PBO). The inspiration to develop the algorithm comes from the way polar bears hunt to survive in harsh arctic conditions. These carnivorous mammals are active all year round. Frosty climate, unfavorable to other animals, has made polar bears adapt to the specific mode of exploration and hunting in large areas, not only over ice but also water. The proposed novel mathematical model of the way polar bears move in the search for food and hunt can be a valuable method of optimization for various theoretical and practical problems. Optimization is very similar to nature, similarly to search for optimal solutions for mathematical models animals search for optimal conditions to develop in their natural environments. In this method. we have used a model of polar bear behaviors as a search engine for optimal solutions. Proposed simulated adaptation to harsh winter conditions is an advantage for local and global search, while birth and death mechanism controls the population. Proposed PBO was evaluated and compared to other meta-heuristic algorithms using sample test functions and some classical engineering problems. Experimental research results were compared to other algorithms and analyzed using various parameters. The analysis allowed us to identify the leading advantages which are rapid recognition of the area by the relevant population and efficient birth and death mechanism to improve global and local search within the solution space.

]]>Symmetry doi: 10.3390/sym9100200

Authors: Stevo Stević

This paper essentially presents the last and important steps in the study of (practical) solvability of two-dimensional product-type systems of difference equations of the following form z n = α z n - k a w n - l b , w n = β w n - m c z n - s d , n ∈ N 0 , where k , l , m , s ∈ N , a , b , c , d ∈ Z , and where α , β and the initial values are complex numbers. It is devoted to the most complex case which has not been considered so far (the case k = l = s = 1 and m = 3 ). Closed form formulas for solutions to the system are found in all possible cases. The structure of the solutions to the system is considered in detail. The following five cases: (1) b = 0 ; (2) c = 0 ; (3) d = 0 ; (4) a c ≠ 0 ; (5) a = 0 , b c d ≠ 0 , are considered separately. Some of the situations appear for the first time in the literature.

]]>Symmetry doi: 10.3390/sym9100202

Authors: Nicola Alchera Marco Bonici Nicola Maggiore

One application of the Cosmological Gravitational Lensing in General Relativity is the measurement of the Hubble constant H 0 using the time delay Δ t between multiple images of lensed quasars. This method has already been applied, obtaining a value of H 0 compatible with that obtained from the SNe 1A, but non-compatible with that obtained studying the anisotropies of the CMB. This difference could be a statistical fluctuation or an indication of new physics beyond the Standard Model of Cosmology, so it desirable to improve the precision of the measurements. At the current technological capabilities it is possible to obtain H 0 to a percent level uncertainty, so a more accurate theoretical model could be necessary in order to increase the precision about the determination of H 0 . The actual formula which relates Δ t with H 0 is approximated; in this paper we expose a proposal to go beyond the previous analysis and, within the context of a new model, we obtain a more precise formula than that present in the literature.

]]>Symmetry doi: 10.3390/sym9100201

Authors: Floyd Stecker

We discuss some of the tests of Lorentz symmetry made possible by astrophysical observations of ultrahigh energy cosmic rays, γ -rays and neutrinos. These are among the most sensitive tests of Lorentz invariance violation because they are the highest energy phenomena known to man.

]]>Symmetry doi: 10.3390/sym9100199

Authors: Álvaro Martínez-Pérez

A graph is chordal if every induced cycle has exactly three edges. A vertex separator set in a graph is a set of vertices that disconnects two vertices. A graph is δ -hyperbolic if every geodesic triangle is δ -thin. In this paper, we study the relation between vertex separator sets, certain chordality properties that generalize being chordal and the hyperbolicity of the graph. We also give a characterization of being quasi-isometric to a tree in terms of chordality and prove that this condition also characterizes being hyperbolic, when restricted to triangles, and having stable geodesics, when restricted to bigons.

]]>Symmetry doi: 10.3390/sym9100198

Authors: Lambert Jorba Romà Adillon

We propose a generalization of trapezoidal fuzzy numbers based on modal interval theory, which we name “modal interval trapezoidal fuzzy numbers”. In this generalization, we accept that the alpha cuts associated with a trapezoidal fuzzy number can be modal intervals, also allowing that two interval modalities can be associated with a trapezoidal fuzzy number. In this context, it is difficult to maintain the traditional graphic representation of trapezoidal fuzzy numbers and we must use the interval plane in order to represent our modal interval trapezoidal fuzzy numbers graphically. Using this representation, we can correctly reflect the modality of the alpha cuts. We define some concepts from modal interval analysis and we study some of the related properties and structures, proving, among other things, that the inclusion relation provides a lattice structure on this set. We will also provide a semantic interpretation deduced from the modal interval extensions of real continuous functions and the semantic modal interval theorem. The application of modal intervals in the field of fuzzy numbers also provides a new perspective on and new applications of fuzzy numbers.

]]>Symmetry doi: 10.3390/sym9090197

Authors: Kamran Siddique Zahid Akhtar Haeng-gon Lee Woongsup Kim Yangwoo Kim

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.

]]>Symmetry doi: 10.3390/sym9090195

Authors: Stevo Stević

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.

]]>Symmetry doi: 10.3390/sym9090196

Authors: Alexandra S. Maia Ana R. Ribeiro Paula M. L. Castro Maria Elizabeth Tiritan

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.

]]>Symmetry doi: 10.3390/sym9090194

Authors: Yuji Yamakawa Akio Namiki Masatoshi Ishikawa Makoto Shimojo

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.

]]>Symmetry doi: 10.3390/sym9090193

Authors: Shiyong Yin Jinsong Bao Yiming Zhang Xiaodi Huang

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.

]]>Symmetry doi: 10.3390/sym9090192

Authors: Jaehee Jung Jong Kim Young-Sik Jeong Gangman Yi

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.

]]>Symmetry doi: 10.3390/sym9090189

Authors: Mingyu Kim Jiwon Lee Changyu Jeon Jinmo Kim

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.

]]>Symmetry doi: 10.3390/sym9090190

Authors: João Ribeiro Maria Tiritan Madalena Pinto Carla Fernandes

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.

]]>Symmetry doi: 10.3390/sym9090188

Authors: Jean Taylor Erin Teich Pablo Damasceno Yoav Kallus Marjorie Senechal

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.

]]>Symmetry doi: 10.3390/sym9090191

Authors: Hongjun Guan Shuang Guan Aiwu Zhao

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.

]]>Symmetry doi: 10.3390/sym9090187

Authors: Haricharan Padmanabhan Maggie Kingsland Jason Munro Daniel Litvin Venkatraman Gopalan

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.

]]>Symmetry doi: 10.3390/sym9090186

Authors: Wei He Zhixiong Li Reza Malekian Xinglong Liu Zhihe Duan

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.

]]>Symmetry doi: 10.3390/sym9090183

Authors: You-Hong Li Jian-Qiang Wang Xue-Jun Wang Yue-Long Zhao Xing-Hua Lu Da-Long Liu

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.

]]>Symmetry doi: 10.3390/sym9090184

Authors: JongBeom Lim HeonChang Yu Joon-Min Gil

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.

]]>Symmetry doi: 10.3390/sym9090185

Authors: Yanhui Guo Yaman Akbulut Abdulkadir Şengür Rong Xia Florentin Smarandache

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.

]]>Symmetry doi: 10.3390/sym9090182

Authors: Natalie Uomini Rebecca Lawson

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.

]]>Symmetry doi: 10.3390/sym9090181

Authors: Haiping Ren Guofu Wang Laijun Luo

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.

]]>Symmetry doi: 10.3390/sym9090180

Authors: Yuxiang Li Yinliang Zhao Bin Liu

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.

]]>Symmetry doi: 10.3390/sym9090179

Authors: Yaman Akbulut Abdulkadir Sengur Yanhui Guo Florentin Smarandache

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.

]]>Symmetry doi: 10.3390/sym9090178

Authors: Qiang Guo Guoqing Ruan Jian Wan

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.

]]>Symmetry doi: 10.3390/sym9090176

Authors: Zbigniew Marszałek

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.

]]>Symmetry doi: 10.3390/sym9090177

Authors: Wei Zhang Yumei Xing Dong Qiu

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.

]]>Symmetry doi: 10.3390/sym9090175

Authors: Bo Hu Lvqing Bi Songsong Dai

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.

]]>Symmetry doi: 10.3390/sym9090174

Authors: Kuppusamy Kanagaraj Kangjie Lin Wanhua Wu Guowei Gao Zhihui Zhong Dan Su Cheng Yang

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.

]]>Symmetry doi: 10.3390/sym9090173

Authors: Dae Yoon Dong-Soo Kim Young Kim Jae Lee

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.

]]>Symmetry doi: 10.3390/sym9090172

Authors: Igor Forain Robson de Oliveira Albuquerque Ana Sandoval Orozco Luis García Villalba Tai-Hoon Kim

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.

]]>Symmetry doi: 10.3390/sym9090171

Authors: Mi Kim Nam Lee Jin Park

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.

]]>Symmetry doi: 10.3390/sym9090169

Authors: Jiansen Zhao Xiao-Yue You Hu-Chen Liu Song-Man Wu

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.

]]>Symmetry doi: 10.3390/sym9090170

Authors: Cátia Silva Cláudia Ribeiro Alexandra Maia Virgínia Gonçalves Maria Tiritan Carlos Afonso

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 &gt; 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.

]]>Symmetry doi: 10.3390/sym9090168

Authors: Rafał Dreżewski Krzysztof Doroz

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.

]]>Symmetry doi: 10.3390/sym9080167

Authors: Ismael Amezcua Valdovinos Jesus Perez Diaz Luis Garcia Villalba Tai-hoon Kim

The Transmission Control Protocol (TCP) is the most used transport protocol to exchange reliable data between network devices. A considerable number of extensions have been implemented into TCP to achieve better performance. In this paper, we will present, describe, implement, and analyze a new protocol extension called Bandwidth-Aggregation TCP (BATCP), which enables the concurrent use of network interfaces, to improve network performance on multi-homed nodes. BATCP allows the use of multiple TCP connections to accept multiple IP addresses from a multi-homed node, scheduling segments among them based on a scheduling algorithm. Our results show that BATCP achieves full exploitation of each network interface, achieving up to 100 % network utilization using two ADSL connections in real-world scenarios. MultiPath TCP (MPTCP) is currently being standardized, and achieves up to 96 % of network utilization when in ideal conditions. BATCP and MPTCP are the only protocols tested on real-world scenarios. Related work such as the Proxy Inverse Multiplexer, called PRISM, and bandwidth aggregation with Stream Control Transmission Protocol (SCTP) achieve 80 % utilization or less with network simulators.

]]>Symmetry doi: 10.3390/sym9080166

Authors: María Carmen Carnero

Abstract: Until the last few decades, maintenance has not been considered of special importance by organisations. Thus, the number of studies that assess maintenance performance in a country is still very small, despite the relevance this area has to the level of national competitiveness. This article describes a multicriteria model integrating the fuzzy analytic hierarchy process (FAHP) with multi-attribute utility theory (MAUT) to assess the maintenance performance of large, medium and small enterprises in Spain, before and after the recession, as well as the asymmetries in the state of maintenance between different activity sectors. The weightings are converted to utility functions which allow the final utility of an alternative to be calculated via a Multi-Attribute Utility Function. From the Spanish maintenance data for different industrial sectors in 2005 and 2010, 2400 discrete probability distributions have been produced. Finally, a Monte Carlo simulation is applied for the estimation of the uncertainty. The results show that the economic crisis experienced by Spain since 2008 has negatively affected the level of maintenance applied, rather than it being considered an area that could deliver cost reductions and improvements in productivity and quality to organisations.

]]>Symmetry doi: 10.3390/sym9080163

Authors: Dong Wang Hualing Ren Fubo Shao

Various distributed optimization methods have been developed for consensus optimization problems in multi-agent networks. Most of these methods only use gradient or subgradient information of the objective functions, which suffer from slow convergence rate. Recently, a distributed Newton method whose appeal stems from the use of second-order information and its fast convergence rate has been devised for the network utility maximization (NUM) problem. This paper contributes to this method by adjusting it to a special kind of consensus optimization problem in two different multi-agent networks. For networks with Hamilton path, the distributed Newton method is modified by exploiting a novel matrix splitting techniques. For general connected multi-agent networks, the algorithm is trimmed by combining the matrix splitting technique and the spanning tree for this consensus optimization problems. The convergence analyses show that both modified distributed Newton methods enable the nodes across the network to achieve a global optimal solution in a distributed manner. Finally, the distributed Newton method is applied to solve a problem which is motivated by the Kuramoto model of coupled nonlinear oscillators and the numerical results illustrate the performance of the proposed algorithm.

]]>Symmetry doi: 10.3390/sym9080164

Authors: Jin Park Jong Park

Blockchain has drawn attention as the next-generation financial technology due to its security that suits the informatization era. In particular, it provides security through the authentication of peers that share virtual cash, encryption, and the generation of hash value. According to the global financial industry, the market for security-based blockchain technology is expected to grow to about USD 20 billion by 2020. In addition, blockchain can be applied beyond the Internet of Things (IoT) environment; its applications are expected to expand. Cloud computing has been dramatically adopted in all IT environments for its efficiency and availability. In this paper, we discuss the concept of blockchain technology and its hot research trends. In addition, we will study how to adapt blockchain security to cloud computing and its secure solutions in detail.

]]>Symmetry doi: 10.3390/sym9080160

Authors: Aifang Xie

In this work, by Zadeh’s extension principle, we extend representable uninorms and their fuzzy implications (coimplications) to type-2 fuzzy sets. Emphatically, we investigate in which algebras of fuzzy truth values the extended operations are type-2 uninorms and type-2 fuzzy implications (coimplications), respectively.

]]>Symmetry doi: 10.3390/sym9080165

Authors: Miloslav Znojil František Růžička Konstantin Zloshchastiev

Schrödinger equations with non-Hermitian, but PT -symmetric quantum potentials V ( x ) found, recently, a new field of applicability in classical optics. The potential acquired there a new physical role of an “anomalous” refraction index. This turned attention to the nonlinear Schrödinger equations in which the interaction term becomes state-dependent, V ( x ) → W ( ψ ( x ) , x ) . Here, the state-dependence in W ( ψ ( x ) , x ) is assumed logarithmic, and some of the necessary mathematical assumptions, as well as some of the potential phenomenological consequences of this choice are described. Firstly, an elementary single-channel version of the nonlinear logarithmic model is outlined in which the complex self-interaction W ( ψ ( x ) , x ) is regularized via a deformation of the real line of x into a self-consistently constructed complex contour C. The new role played by PT -symmetry is revealed. Secondly, the regularization is sought for a multiplet of equations, coupled via the same nonlinear self-interaction coupling of channels. The resulting mathematical structures are shown to extend the existing range of physics covered by the logarithmic Schrödinger equations.

]]>Symmetry doi: 10.3390/sym9080161

Authors: Shikai Guo Rong Chen Hui Li

Crowdsourcing is an appealing and economic solution to software application testing because of its ability to reach a large international audience. Meanwhile, crowdsourced testing could have brought a lot of bug reports. Thus, in crowdsourced software testing, the inspection of a large number of test reports is an enormous but essential software maintenance task. Therefore, automatic prediction of the severity of crowdsourced test reports is important because of their high numbers and large proportion of noise. Most existing approaches to this problem utilize supervised machine learning techniques, which often require users to manually label a large number of training data. However, Android test reports are not labeled with their severity level, and manual labeling is time-consuming and labor-intensive. To address the above problems, we propose a Knowledge Transfer Classification (KTC) approach based on text mining and machine learning methods to predict the severity of test reports. Our approach obtains training data from bug repositories and uses knowledge transfer to predict the severity of Android test reports. In addition, our approach uses an Importance Degree Reduction (IDR) strategy based on rough set to extract characteristic keywords to obtain more accurate reduction results. The results of several experiments indicate that our approach is beneficial for predicting the severity of android test reports.

]]>Symmetry doi: 10.3390/sym9080162

Authors: Haibin Liu Xinyang Deng Wen Jiang

Failure mode and effects analysis (FMEA) is a popular and useful approach applied to examine potential failures in different products, designs, processes, and services. As a vital index, the risk priority number (RPN) can determine the risk priorities of failure modes by some risk factors such as occurrence (O), severity (S), and detection (D). However, in FMEA, the traditional risk priority number approach has some shortcomings, especially in setting the weight of risk factors. This paper presents an improved risk priority number approach based on a fuzzy measure and fuzzy integral. A fuzzy measure is used to reflect the importance of the individual indicators and the indicator set and a fuzzy integral is a nonlinear function defined on the basis of fuzzy measure. The weights of risk factors given by domain experts are seen as fuzzy densities to generate a λ -fuzzy measure which can reflect the weights’ difference and relevance about risk factors. Then, the Choquet integral is used to fuse every value of risk factors about failure modes so as to obtain the comprehensive evaluation result. The result can reflect the comprehensive risk level, so it has a definite physical significance. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach in the paper.

]]>Symmetry doi: 10.3390/sym9080158

Authors: Zia Bashir Jarosław Wątróbski Tabasam Rashid Wojciech Sałabun Jawad Ali

The classical matrix theory is deficient to express the vagueness of the real life. The fuzzy set theory has been successfully applied to bridge this gap. Much work has already been done on a two-person zero sum matrix game with fuzzy goals. In continuation, this paper is dedicated to define and study a multi-criteria two-person zero sum game with intuitionistic fuzzy goals. It is shown that solving such games is equivalent to solving two crisp multi object linear programming problems. Our work generalizes the previous study on a multi-criteria game with fuzzy goals by adopting the approach of linear programming with intuitionistic fuzzy sets. Finally, an illustrative numerical example is provided to elaborate the proposed approach.

]]>Symmetry doi: 10.3390/sym9080157

Authors: Lili Guo Shanya Cong

Heterogeneous networks (HetNets) are regarded as a promising approach to handle the deluge of mobile data traffic. With the co-channel deployment of small cells, the coverage and capacity of the network will be improved. However, the conventional maximum-received-power (MRP) user association scheme and cross-tier interference issue significantly diminish the performance gain provided by small cells. In this paper, we propose a novel location-aware cross-tier cooperation (LA-CTC) scheme for jointly achieving load balancing and interference mitigation in two-tier HetNets. In detail, we define an inner region for each macro base station (MBS) where the femto base stations (FBSs) will be deactivated, and thereby the users within the inner region will only be served by the MBS. Subsequently, for the users located in the outer region, the proposed scheme only uses coordinated multipoint (CoMP) transmission by two tiers of BSs to eliminate the excessive cross-tier interference suffered by offloaded users, whereas users with good locations are served directly by either a MBS or a FBS. Using tools of stochastic geometry, we derived the analytical expressions for the coverage probability and average rate of a randomly chosen user. Meanwhile, the analytical results were validated through Monte Carlo simulations. The numerical results show that the proposed scheme can improve the performance of networks significantly. Moreover, we compare the performance of the proposed scheme with that of the conventional MRP scheme, the cell range expansion (CRE) scheme and the location-aware cross-tier CoMP transmission (LA-CTCT) scheme in the literature. Numerical comparisons revealed that the proposed LA-CTC scheme outperforms the other three schemes.

]]>Symmetry doi: 10.3390/sym9080156

Authors: Jianwei Gao Ru Yi

In this paper, we develop a new linguistic aggregation operator based on the cloud model for solving linguistic group decision-making problem. First, an improved generating cloud method is proposed so as to transform linguistic variables into clouds, which modifies the limitation of the classical generating cloud method. We then address some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the weights. Combining the cloud support degree with power aggregation operator, we develop a new cloud aggregation operator dubbed the cloud generalized power ordered weighted average (CGPOWA) operator. We study the properties of the CGPOWA operator and investigate its family including a wide range of aggregation operators such as the CGPA operator, CPOWA operator, CPOWGA operator, CPWQA operator, CWAA and CWGA operator. Furthermore, a new approach for linguistic group decision-making is presented on the basis of the improved generating cloud method and CGPOWA operator. Finally, an illustrative example is provided to examine the effectiveness and validity of the proposed approach.

]]>Symmetry doi: 10.3390/sym9080159

Authors: Wei Zhang Yumei Xing Dong Qiu

A multi-objective bi-matrix game model based on fuzzy goals is established in this paper. It is shown that the equilibrium solution of such a game model problem can be translated into the optimal solution of a multi-objective, non-linear programming problem. Finally, the results of this paper are demonstrated through a numerical example.

]]>Symmetry doi: 10.3390/sym9080155

Authors: Vladimir D. Ivashchuk

The review is devoted to exact solutions with hidden symmetries arising in a multidimensional gravitational model containing scalar fields and antisymmetric forms. These solutions are defined on a manifold of the form M = M0 x M1 x . . . x Mn , where all Mi with i &gt;= 1 are fixed Einstein (e.g., Ricci-flat) spaces. We consider a warped product metric on M. Here, M0 is a base manifold, and all scale factors (of the warped product), scalar fields and potentials for monomial forms are functions on M0 . The monomial forms (of the electric or magnetic type) appear in the so-called composite brane ansatz for fields of forms. Under certain restrictions on branes, the sigma-model approach for the solutions to field equations was derived in earlier publications with V.N.Melnikov. The sigma model is defined on the manifold M0 of dimension d0 ≠ 2 . By using the sigma-model approach, several classes of exact solutions, e.g., solutions with harmonic functions, S-brane, black brane and fluxbrane solutions, are obtained. For d0 = 1 , the solutions are governed by moduli functions that obey Toda-like equations. For certain brane intersections related to Lie algebras of finite rank—non-singular Kac–Moody (KM) algebras—the moduli functions are governed by Toda equations corresponding to these algebras. For finite-dimensional semi-simple Lie algebras, the Toda equations are integrable, and for black brane and fluxbrane configurations, they give rise to polynomial moduli functions. Some examples of solutions, e.g., corresponding to finite dimensional semi-simple Lie algebras, hyperbolic KM algebras: H2(q, q) , AE3, HA(1)2, E10 and Lorentzian KM algebra P10 , are presented.

]]>Symmetry doi: 10.3390/sym9080153

Authors: Jiqian Chen Jun Ye Shigui Du

A refined single-valued/interval neutrosophic set is very suitable for the expression and application of decision-making problems with both attributes and sub-attributes since it is described by its refined truth, indeterminacy, and falsity degrees. However, existing refined single-valued/interval neutrosophic similarity measures and their decision-making methods are scarcely studied in existing literature and cannot deal with this decision-making problem with the weights of both attributes and sub-attributes in a refined interval and/or single-valued neutrosophic setting. To solve the issue, this paper firstly introduces a refined simplified neutrosophic set (RSNS), which contains the refined single-valued neutrosophic set (RSVNS) and refined interval neutrosophic set (RINS), and then proposes vector similarity measures of RSNSs based on the Jaccard, Dice, and cosine measures of simplified neutrosophic sets in vector space, and the weighted Jaccard, Dice, and cosine measures of RSNSs by considering weights of both basic elements and sub-elements in RSNS. Further, a decision-making method with the weights of both attributes and sub-attributes is developed based on the weighted Jaccard, Dice, and cosine measures of RSNSs under RSNS (RINS and/or RSVNS) environments. The ranking order of all the alternatives and the best one can be determined by one of weighted vector similarity measures between each alternative and the ideal solution (ideal alternative). Finally, an actual example on the selecting problem of construction projects illustrates the application and effectiveness of the proposed method.

]]>Symmetry doi: 10.3390/sym9080154

Authors: Jing Fu Jun Ye

When a physician carries out the clinical survey of a patient with benign prostatic hyperplasia (BPH) symptoms to reach the initial evaluation/diagnosis of BPH, the existing initial evaluation method of BPH based on the international prostate symptom score (I-PSS) usually uses the objective evaluation/diagnosis method with crisp values without considering fuzzy information. However, this common evaluation/diagnosis method may lead to the loss of a great deal of useful incomplete, uncertain, and inconsistent information in the clinical survey and initial evaluation process of the BPH symptoms for a patient, resulting in an unreasonable evaluation and diagnosis distortion of the BPH symptoms. To overcome this drawback, this paper aims to propose new exponential similarity measures (ESMs) between simplified neutrosophic sets (SNSs), including single-valued neutrosophic ESMs and interval neutrosophic ESMs, and their initial evaluation/diagnosis method of the BPH symptoms with simplified neutrosophic information. Finally, two evaluation/diagnosis examples of the BPH symptoms are provided to demonstrate the effectiveness and rationality of the proposed method.

]]>Symmetry doi: 10.3390/sym9080152

Authors: Donghwoon Kwon Suwoo Park Jeong-Tak Ryu

A smart connected car in conjunction with the Internet of Things (IoT) is an emerging topic. The fundamental concept of the smart connected car is connectivity, and such connectivity can be provided by three aspects, such as Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X). To meet the aspects of V2V and V2I connectivity, we developed modules in accordance with international standards with respect to On-Board Diagnostics II (OBDII) and 4G Long Term Evolution (4G-LTE) to obtain and transmit vehicle information. We also developed software to visually check information provided by our modules. Information related to a user’s driving, which is transmitted to a cloud-based Distributed File System (DFS), was then analyzed for the purpose of big data analysis to provide information on driving habits to users. Yet, since this work is an ongoing research project, we focus on proposing an idea of system architecture and design in terms of big data analysis. Therefore, our contributions through this work are as follows: (1) Develop modules based on Controller Area Network (CAN) bus, OBDII, and 4G-LTE; (2) Develop software to check vehicle information on a PC; (3) Implement a database related to vehicle diagnostic codes; (4) Propose system architecture and design for big data analysis.

]]>Symmetry doi: 10.3390/sym9080151

Authors: Sui-Zhi Luo Peng-Fei Cheng Jian-Qiang Wang Yuan-Ji Huang

Project delivery system selection is an essential part of project management. In the process of choosing appropriate transaction model, many factors should be under consideration, such as the capability and experience of proprietors, project implementation risk, and so on. How to make their comprehensive evaluations and select the optimal delivery system? This paper proposes a decision-making approach based on an extended linguistic preference structure: simplified neutrosophic linguistic preference relations (SNLPRs). The basic elements in SNLPRs are simplified neutrosophic linguistic numbers (SNLNs). First, several distance measures of SNLNs are introduced. A distance-based consistency index is provided to measure the consistency degree of a simplified neutrosophic linguistic preference relation (SNLPR). When the SNLPR is not acceptably consistent, a consistency-improving automatic iterative algorithm may be used. Afterwards, a decision-making method with SNLPRs is developed. The example of its application in project delivery systems’ selection is offered, and a comparison analysis is given in the end as well.

]]>Symmetry doi: 10.3390/sym9080149

Authors: Weizhang Liang Guoyan Zhao Hao Wu

The investment in and development of mineral resources play an important role in the national economy. A good mining project investment can improve economic efficiency and increase social wealth. Faced with the complexity and uncertainty of a mine’s circumstances, there is great significance in evaluating investment risk scientifically. In order to solve practical engineering problems, this paper presents an extended TOPSIS method combined with linguistic neutrosophic numbers (LNNs). Firstly, considering that there are several qualitative risk factors of mining investment projects, the paper describes evaluation information by means of LNNs. The advantage of LNNs is that major original information is reserved with linguistic truth, indeterminacy, and false membership degrees. After that, a number of distance measures are defined. Furthermore, a common status is that the decision makers can’t determine the importance degrees of every risk factor directly for a few reasons. With respect to this situation, the paper offers a weight model based on maximizing deviation to obtain the criteria weight vector objectively. Subsequently, a decision-making approach through improving classical TOPSIS with LNNs comes into being. Next, a case study of the proposed method applied in metallic mining projects investment is given. Some comparison analysis is also submitted. At last, the discussions and conclusions are finished.

]]>Symmetry doi: 10.3390/sym9080150

Authors: Yuval Ben-Abu

Potassium channels are integral membrane proteins that selectively transport K+ ions across cell membranes. They function through a pair of gates, which work in tandem to allow the passage of the ions through the channel pore in a coupled system, to which I refer to here as the “gate linker”. The functional mutation effects, as described in the literature, suggest that the gate linker functions analogously to a triad of coiled springs arranged in series. Accordingly, I constructed a physical model of harmonic oscillators and analyzed it mechanically and mathematically. The operation of this model indeed corresponds to the phenomena observed in the mutations study. The harmonic oscillator model shows that the strength of the gate linker is crucial for gate coupling and may account for the velocity, direction, and efficiency of ion transfer through the channel. Such a physical perspective of the gating process suggests new lines of investigation regarding the coupling mode of potassium channels and may help to explain the importance of the gate linker to channel function.

]]>Symmetry doi: 10.3390/sym9080148

Authors: Nazife Koca Mehmet Koca

Vertices and symmetries of regular and irregular chiral polyhedra are represented by quaternions with the use of Coxeter graphs. A new technique is introduced to construct the chiral Archimedean solids, the snub cube and snub dodecahedron together with their dual Catalan solids, pentagonal icositetrahedron and pentagonal hexecontahedron. Starting with the proper subgroups of the Coxeter groups W ( A 1 ⊕ A 1 ⊕ A 1 ) , W ( A 3 ) , W ( B 3 ) and W ( H 3 ) , we derive the orbits representing the respective solids, the regular and irregular forms of a tetrahedron, icosahedron, snub cube, and snub dodecahedron. Since the families of tetrahedra, icosahedra and their dual solids can be transformed to their mirror images by the proper rotational octahedral group, they are not considered as chiral solids. Regular structures are obtained from irregular solids depending on the choice of two parameters. We point out that the regular and irregular solids whose vertices are at the edge mid-points of the irregular icosahedron, irregular snub cube and irregular snub dodecahedron can be constructed.

]]>Symmetry doi: 10.3390/sym9080147

Authors: Qingsong Ai Yanan Zhang Weili Qi Quan Liu and Kun Chen

Since surface electromyograghic (sEMG) signals are non-invasive and capable of reflecting humans’ motion intention, they have been widely used for the motion recognition of upper limbs. However, limited research has been conducted for lower limbs, because the sEMGs of lower limbs are easily affected by body gravity and muscle jitter. In this paper, sEMG signals and accelerometer signals are acquired and fused to recognize the motion patterns of lower limbs. A curve fitting method based on median filtering is proposed to remove accelerometer noise. As for movement onset detection, an sEMG power spectral correlation coefficient method is used to detect the start and end points of active signals. Then, the time-domain features and wavelet coefficients of sEMG signals are extracted, and a dynamic time warping (DTW) distance is used for feature extraction of acceleration signals. At last, five lower limbs’ motions are classified and recognized by using Gaussian kernel-based linear discriminant analysis (LDA) and support vector machine (SVM) respectively. The results prove that the fused feature-based classification outperforms the classification with only sEMG signals or accelerometer signals, and the fused feature can achieve 95% or higher recognition accuracy, demonstrating the validity of the proposed method.

]]>Symmetry doi: 10.3390/sym9080146

Authors: Xiaowu Li Lin Wang Zhinan Wu Linke Hou Juan Liang Qiaoyang Li

To compute the minimum distance between a point and a parametric surface, three well-known first-order algorithms have been proposed by Hartmann (1999), Hoschek, et al. (1993) and Hu, et al. (2000) (hereafter, the First-Order method). In this paper, we prove the method’s first-order convergence and its independence of the initial value. We also give some numerical examples to illustrate its faster convergence than the existing methods. For some special cases where the First-Order method does not converge, we combine it with Newton’s second-order iterative method to present the hybrid second-order algorithm. Our method essentially exploits hybrid iteration, thus it performs very well with a second-order convergence, it is faster than the existing methods and it is independent of the initial value. Some numerical examples confirm our conclusion.

]]>Symmetry doi: 10.3390/sym9080145

Authors: Sebastian Ocklenburg Jutta Peterburs Janet Mertzen Judith Schmitz Onur Güntürkün Gina Grimshaw

Hemispheric asymmetries are a major organizational principle in human emotion processing, but their interaction with prefrontal control processes is not well understood. To this end, we determined whether hemispheric differences in response inhibition depend on the emotional valence of the stimulus being inhibited. Participants completed a lateralised Go/Nogo task, in which Nogo stimuli were neutral or emotional (either positive or negative) images, while Go stimuli were scrambled versions of the same pictures. We recorded the N2 and P3 event-related potential (ERP) components, two common electrophysiological measures of response inhibition processes. Behaviourally, participants were more accurate in withholding responses to emotional than to neutral stimuli. Electrophysiologically, Nogo-P3 responses were greater for emotional than for neutral stimuli, an effect driven primarily by an enhanced response to positive images. Hemispheric asymmetries were also observed, with greater Nogo-P3 following left versus right visual field stimuli. However, the visual field effect did not interact with emotion. We therefore find no evidence that emotion-related asymmetries affect response inhibition processes.

]]>