Symmetry doi: 10.3390/sym10110641

Authors: Mansour Sattam Aldosari Muhammad Aslam Nasrullah Khan Chi-Hyuck Jun

In this paper, a new variable control chart is proposed using multiple dependent-state repetitive sampling by assuming that the data follows a normal distribution having a symmetry property. Its efficiency will be evaluated in terms of in-control and out-of-control average run lengths. The results showed that the proposed chart is better than the existing variable control chart to detect an early shift in the process. An industrial example is given to illustrate the proposed chart in the industry.

]]>Symmetry doi: 10.3390/sym10110640

Authors: Xu Libo Li Xingsen Pang Chaoyi Guo Yan

In this paper, a new approach and framework based on the interval dependent degree for multi-criteria group decision-making (MCGDM) problems with simplified neutrosophic sets (SNSs) is proposed. Firstly, the simplified dependent function and distribution function are defined. Then, they are integrated into the interval dependent function which contains interval computing and distribution information of the intervals. Subsequently, the interval transformation operator is defined to convert simplified neutrosophic numbers (SNNs) into intervals, and then the interval dependent function for SNNs is deduced. Finally, an example is provided to verify the feasibility and effectiveness of the proposed method, together with its comparative analysis. In addition, uncertainty analysis, which can reflect the dynamic change of the final result caused by changes in the decision makers’ preferences, is performed in different distribution function situations. That increases the reliability and accuracy of the result.

]]>Symmetry doi: 10.3390/sym10110639

Authors: Ahmad Ali Yu Ming Sagnik Chakraborty Saima Iram Tapas Si

Present research in the domain of wireless sensor network (WSN) has unearthed that energy restraint of sensor nodes (SNs) encumbers their perpetual performance. Of late, the encroachment in the vicinity of wireless power transfer (WPT) technology has achieved pervasive consideration from both industry and academia to cater the sensor nodes (SNs) letdown in the wireless rechargeable sensor network (WRSNs). The fundamental notion of wireless power transfer is to replenish the energy of sensor nodes using a single or multiple wireless charging devices (WCDs). Herein, we present a jointly optimization model to maximize the charging efficiency and routing restraint of the wireless charging device (WCD). At the outset, we intend an unswerving charging path algorithm to compute the charging path of the wireless charging device. Moreover, Particle swarm optimization (PSO) algorithm has designed with the aid of a virtual clustering technique during the routing process to equilibrate the network lifetime. Herein clustering algorithm, the enduring energy of the sensor nodes is an indispensable parameter meant for the assortment of cluster head (CH). Furthermore, compare the proposed approach to corroborate its pre-eminence over the benchmark algorithm in diverse scenarios. The simulation results divulge that the proposed work is enhanced concerning the network lifetime, charging performance and the enduring energy of the sensor nodes.

]]>Symmetry doi: 10.3390/sym10110638

Authors: Susmit Bagchi

The probabilistic algorithms are widely applied in designing computational applications such as distributed systems and probabilistic databases, to determine distributed consensus in the presence of random failures of nodes or networks. In distributed computing, symmetry breaking is performed by employing probabilistic algorithms. In general, probabilistic symmetry breaking without any bias is preferred. Thus, the designing of randomized and probabilistic algorithms requires modeling of associated probability spaces to generate control-inputs. It is required that discrete measures in such spaces are computable and tractable in nature. This paper proposes the construction of composite discrete measures in real as well as complex metric spaces. The measures are constructed on different varieties of continuous smooth curves having distinctive non-linear profiles. The compositions of discrete measures consider arbitrary functions within metric spaces. The measures are constructed on 1-D interval and 2-D surfaces and, the corresponding probability metric product is defined. The associated sigma algebraic properties are formulated. The condensation measure of the uniform contraction map is constructed as axioms. The computational evaluations of the proposed composite set of measures are presented.

]]>Symmetry doi: 10.3390/sym10110637

Authors: Tie Hong SongZhu Mei ZhiYing Wang JiangChun Ren

Many scholars have attempted to use an encryption method to resolve the problem of data leakage in data outsourcing storage. However, encryption methods reduce data availability and are inefficient. Vertical fragmentation perfectly solves this problem. It was first used to improve the access performance of the relational database, and nowadays some researchers employ it for privacy protection. However, there are some problems that remain to be solved with the vertical fragmentation method for privacy protection in the relational database. First, current vertical fragmentation methods for privacy protection require the user to manually define privacy constraints, which is difficult to achieve in practice. Second, there are many vertical fragmentation solutions that can meet privacy constraints; however, there are currently no quantitative evaluation criteria evaluating how effectively solutions can protect privacy more effectively. In this article, we introduce the concept of information entropy to quantify privacy in vertical fragmentation, so we can automatically discover privacy constraints. Based on this, we propose a privacy protection model with a minimum entropy fragmentation algorithm to achieve minimal privacy disclosure of vertical fragmentation. Experimental results show that our method is suitable for privacy protection with a lower overhead.

]]>Symmetry doi: 10.3390/sym10110636

Authors: Azadeh Khameneh Adem Kiliçman

Aggregation operators are important tools for solving multi-attribute group decision-making (MAGDM) problems. The main challenging issue for aggregating data in a MAGDM problem is how to develop a symmetric aggregation operator expressing the decision makers’ behavior. In the literature, there are some methods dealing with this difficulty; however, they lack an effective approach for multi-polar inputs. In this study, a new aggregation operator for m-polar fuzzy soft sets (M-pFSMWM) reflecting different agreement scenarios within a group is presented to proceed MAGDM problems in which both attributes and experts have different weights. Moreover, some desirable properties of M-pFSMWM operator, such as idempotency, monotonicity, and commutativity (symmetric), that means being invariant under any permutation of the input arguments, are studied. Further, m-polar fuzzy soft induced ordered weighted average (M-pFSIOWA) operator and m-polar fuzzy soft induced ordered weighted geometric (M-pFSIOWG) operator, which are extensions of IOWA and IOWG operators, respectively, are developed. Two algorithms are also designed based on the proposed operators to find the final solution in MAGDM problems with weighted multi-polar fuzzy soft information. Finally, the efficiency of the proposed methods is illustrated by some numerical examples. The characteristic comparison of the proposed aggregation operators shows the M-pFSMWM operator is more adaptable for solving MAGDM problems in which different cases of agreement affect the final outcome.

]]>Symmetry doi: 10.3390/sym10110635

Authors: Abdul Jawad Kazuharu Bamba Muhammad Younas Saba Qummer Shamaila Rani

The cosmic expansion phenomenon is being studied through the interaction of newly proposed dark energy models (Tsallis, R&eacute;nyi and Sharma-Mittal holographic dark energy (HDE) models) with cold dark matter in the framework of loop quantum cosmology. We investigate different cosmic implications such as equation of state parameter, squared sound speed and cosmological plane (&omega; d - &omega; d &prime; , &omega; d and &omega; d &prime; represent the equation of state (EoS) parameter and its evolution, respectively). It is found that EoS parameter exhibits quintom like behavior of the universe for all three models of HDE. The squared speed of sound represents the stable behavior of R&eacute;nyi HDE and Sharma-Mittal HDE at the latter epoch while unstable behavior for Tsallis HDE. Moreover, &omega; d - &omega; d &prime; plane lies in the thawing region for all three HDE models.

]]>Symmetry doi: 10.3390/sym10110634

Authors: Yunjae Kim Byung Moon Kim Jin-Woo Park

Changhee polynomials were introduced by Kim, and the generalizations of these polynomials have been characterized. In our paper, we investigate various interesting symmetric identities for Carlitz&rsquo;s type q-Changhee polynomials under the symmetry group of order n arising from the fermionic p-adic q-integral on Z p .

]]>Symmetry doi: 10.3390/sym10110633

Authors: Jinsheng Gao Xiaomin Zhu Anbang Liu Qingyang Meng Runtong Zhang

This paper shows the results of our study on the pick-and-place optimization problem. To solve this problem efficiently, an iterated hybrid local search algorithm (IHLS) which combines local search with integer programming is proposed. In the section of local search, the greedy algorithm with distance weight strategy and the convex-hull strategy is developed to determine the pick-and-place sequence; in the section of integer programming, an integer programming model is built to complete the feeder assignment problem. The experimental results show that the IHLS algorithm we proposed has high computational efficiency. Furthermore, compared with the genetic algorithm and the memetic algorithm, the IHLS is less time-consuming and more suitable in solving a large-scale problem.

]]>Symmetry doi: 10.3390/sym10110632

Authors: Fidel Aznar Mar Pujol Ramon Rizo Francisco A. Pujol Carlos Rizo

Building an ad-hoc network in emergency situations can be crucial as a primary tool or even when used prior to subsequent operations. The use of mini and micro Unmanned Aerial Vehicles (UAVs) is increasing because of the wide range of possibilities they offer. Moreover, they have been proven to bring sustainability to many applications, such as agriculture, deforestation and wildlife conservation, among others. Therefore, creating a UAV network for an unknown environment is an important task and an active research field. In this article, a mobility model for the creation of ad-hoc networks using UAVs will be presented. This model will be based on pheromones for robust navigation. We will focus mainly on developing energy-efficient behavior, which is essential for this type of vehicle. Although there are in the literature several models of mobility for ad-hoc network creation, we find that either they are not adapted to the specific energy requirements of UAVs or the proposed motion models are unrealistic or not sufficiently robust for final implantation. We will present and analyze the operation of a distributed swarm behavior able to create an ad-hoc network. Then, an analytical model of the swarm energy consumption will be proposed. This model will provide a mechanism to effectively predict the energy consumption needed for the deployment of the network prior to its implementation. Determining the use of the mobility behavior is a requirement to establish and maintain a communication channel for the required time. Finally, this analytical model will be experimentally validated and compared to the Random Waypoint (RWP) mobility strategy.

]]>Symmetry doi: 10.3390/sym10110631

Authors: Ahmed M. Al-Sammna Marwan Hadri Azmi Tharek Abd Rahman

This paper considers the channel modeling and prediction for ultra-wideband (UWB) channels. The sparse property of UWB channels is exploited, and an efficient prediction framework is developed by introducing two simplified UWB channel impulse response (CIR) models, namely, the windowing-based on window delay (WB-WD) and the windowing-based on bin delay (WB-BD). By adopting our proposed UWB windowing-based CIR models, the recursive least square (RLS) algorithm is used to predict the channel coefficients. By using real CIR coefficients generated from measurement campaign data conducted in outdoor environments, the modeling and prediction performance results and the statistical properties of the root mean square (RMS) delay spread values are presented. Our proposed framework improves the prediction performances with lower computational complexity compared with the performance of the recommended ITU-R UWB-CIR model. It is shown that our proposed framework can achieved 15% lower prediction error with a complexity reduction by a factor of 12.

]]>Symmetry doi: 10.3390/sym10110630

Authors: Won Choi Vladimir Shin Il Song

This paper focuses on estimation of a nonlinear functional of state vector (NFS) in discrete-time linear stochastic systems. The NFS represents a nonlinear multivariate functional of state variables, which can indicate useful information of a target system for control. The optimal mean-square estimator of a general NFS represents a function of the Kalman estimate and its error covariance. The polynomial functional of state vector is studied in detail. In this case an optimal estimation algorithm has a closed-form computational procedure. The novel mean-square quadratic estimator is derived. For a general NFS we propose to use the unscented transformation to calculate an optimal estimate. The obtained results are demonstrated on theoretical and practical examples with different types of NFS. Comparative analysis with suboptimal estimators for NFS is presented. The subsequent application of the proposed estimators to linear discrete-time systems demonstrates their practical effectiveness.

]]>Symmetry doi: 10.3390/sym10110629

Authors: Yanjun Wang Lidong Wang Huijuan Wang Xinghua Feng

An aggregation operator performs the task of fusing multiple sources of information, which plays a pivotal part in realizing a collective opinion in most decision-making activities. Considering the increasing complexity of decision-making situations, it is imperative to extend aggregation operators for fusing uncertain information with the different forms of attribute values. This study focuses on the development of picture fuzzy sets and aims to design a managerial decision-making solving method. Some operational principles of hesitant picture 2-tuple linguistic variables on account of the Archimedean t-norm and t-conorm are initiated, on which two hesitant picture 2-tuple linguistic weighted operators are established by taking various weight forms. Moreover, we explore the aggregation operators’ idempotency, boundedness, and monotonicity, as well as analyze some particular forms of these operators. Furthermore, these aggregation operators are employed to design a method of deriving an overall performance from evaluation of experts with hesitant picture 2-tuple linguistic terms. An example of selecting service outsourcing supplier is carried out to show the procedures of decision-making with a detailed comparative analysis.

]]>Symmetry doi: 10.3390/sym10110628

Authors: Yong-An Jung Young-Hwan You

Recently, the application of digital cable transmission standards as a second generation digital transmission system for cable systems (DVB-C2) in addition to MPEG-2 video compression has offered ways to provide a variety of digital high definition television (HDTV) programs. In the DVB-C2 system, the use of an orthogonal frequency division multiplexing (OFDM) modulation enables the delivery of innovative video-on-demand (VOD) and HDTV services. In this paper, a computationally-efficientleast-squares estimation of carrier frequency offset and sampling frequency offset is proposed in the OFDM-based DVB-C2 system. To obtain the noise averaging effect in the synchronization process, we adopt a block-by-block correlation, where observation symbols within two correlation blocks are added and the result is correlated. The use of block-by-block correlation improves the estimation performance and relieves the computational overhead. To optimize the performance of the block-by-block estimation method, the mean squared error is theoretically calculated. It is confirmed from simulation results that the performance of the proposed method is enhanced with a low complexity, in comparison with the existing methods.

]]>Symmetry doi: 10.3390/sym10110627

Authors: Daniel Chalupa Jan Mikulka

The rather impressive extension library of medical image-processing platform 3D Slicer lacks a wide range of machine-learning toolboxes. The authors have developed such a toolbox that incorporates commonly used machine-learning libraries. The extension uses a simple graphical user interface that allows the user to preprocess data, train a classifier, and use that classifier in common medical image-classification tasks, such as tumor staging or various anatomical segmentations without a deeper knowledge of the inner workings of the classifiers. A series of experiments were carried out to showcase the capabilities of the extension and quantify the symmetry between the physical characteristics of pathological tissues and the parameters of a classifying model. These experiments also include an analysis of the impact of training vector size and feature selection on the sensitivity and specificity of all included classifiers. The results indicate that training vector size can be minimized for all classifiers. Using the data from the Brain Tumor Segmentation Challenge, Random Forest appears to have the widest range of parameters that produce sufficiently accurate segmentations, while optimal Support Vector Machines’ training parameters are concentrated in a narrow feature space.

]]>Symmetry doi: 10.3390/sym10110626

Authors: Zhibin Guan Kang Liu Yan Ma Xu Qian Tongkai Ji

Image caption generation is a fundamental task to build a bridge between image and its description in text, which is drawing increasing interest in artificial intelligence. Images and textual sentences are viewed as two different carriers of information, which are symmetric and unified in the same content of visual scene. The existing image captioning methods rarely consider generating a final description sentence in a coarse-grained to fine-grained way, which is how humans understand the surrounding scenes; and the generated sentence sometimes only describes coarse-grained image content. Therefore, we propose a coarse-to-fine-grained hierarchical generation method for image captioning, named SDA-CFGHG, to address the two problems above. The core of our SDA-CFGHG method is a sequential dual attention that is used to fuse different grained visual information with sequential means. The advantage of our SDA-CFGHG method is that it can achieve image captioning in a coarse-to-fine-grained way and the generated textual sentence can capture details of the raw image to some degree. Moreover, we validate the impressive performance of our method on benchmark datasets&mdash;MS COCO, Flickr&mdash;with several popular evaluation metrics&mdash;CIDEr, SPICE, METEOR, ROUGE-L, and BLEU.

]]>Symmetry doi: 10.3390/sym10110625

Authors: Li Chen

The goal of this paper is to solve the computational problem of one kind rational polynomials of classical Gauss sums, applying the analytic means and the properties of the character sums. Finally, we will calculate a meaningful recursive formula for it.

]]>Symmetry doi: 10.3390/sym10110624

Authors: Rafal Doroz

The paper proposes a method of automatic knuckle image acquisition for continuous verification systems. The developed acquisition method is dedicated for verification systems in which the person being verified uses a computer keyboard. This manner of acquisition enables registration of the knuckle image without interrupting the user&rsquo;s work for the time of acquisition. This is an important advantage, unprecedented in the currently known methods. The process of the automatic location of the finger knuckle can be considered as a pattern recognition approach and is based on the analysis of symmetry and similarity between the reference knuckle patterns and live camera image. The effectiveness of the aforesaid approach has been tested experimentally. The test results confirmed its high effectiveness. The effectiveness of the proposed method was also determined in a case where it is a part of a multi-biometric method.

]]>Symmetry doi: 10.3390/sym10110623

Authors: Hengqing Ge Guibin Chen Haichun Yu Huabao Chen Fengping An

This work suggests a theoretical principle about the oscillation signal decomposition, which is based on the requirement of a pure oscillation component, in which the mean zero is extracted from the signal. Using this principle, the validity and robustness of the empirical mode decomposition (EMD) method are first proved mathematically. This work also presents a modified version of EMD by the interpolation solution, which is able to improve the frequency decomposition of the signal. The result shows that it can provide a primary theoretical basis for the development of EMD. The simulation signal verifies the effectiveness of the EMD algorithm. At the same time, compared with the existing denoising algorithm, it has achieved good results in the denoising of rolling bearing fault signals. It contributes to the development and improvement of adaptive signal processing theory in the field of fault diagnosis. It provides practical value research results for the rapid development of adaptive technology in the field of fault diagnosis.

]]>Symmetry doi: 10.3390/sym10110622

Authors: Jinsu Kang Jeonghoon Seo Yoojae Won

Recently, the rapid development of mobile devices and communication technologies has dramatically increased the demand for location-based services that provide users with location-oriented information and services. User location in outdoor spaces is measured with high accuracy using GPS. However, because the indoor reception of GPS signals is not smooth, this solution is not viable in indoor spaces. Many on-going studies are exploring new approaches for indoor location measurement. One popular technique involves using the received signal strength indicator (RSSI) values from the Bluetooth Low Energy (BLE) beacons to measure the distance between a mobile device and the beacons and then determining the position of the user in an indoor space by applying a positioning algorithm such as the trilateration method. However, it remains difficult to obtain accurate data because RSSI values are unstable owing to the influence of elements in the surrounding environment such as weather, humidity, physical barriers, and interference from other signals. In this paper, we propose an indoor location tracking system that improves performance by correcting unstable RSSI signals received from BLE beacons. We apply a filter algorithm based on the average filter and the Kalman filter to reduce the error range of results calculated using the RSSI values.

]]>Symmetry doi: 10.3390/sym10110621

Authors: Majdoleen Qamar Nasruddin Hassan

Neutrosophic triplet structure yields a symmetric property of truth membership on the left, indeterminacy membership in the centre and false membership on the right, as do points of object, centre and image of reflection. As an extension of a neutrosophic set, the Q-neutrosophic set was introduced to handle two-dimensional uncertain and inconsistent situations. We extend the soft expert set to generalized Q-neutrosophic soft expert set by incorporating the idea of soft expert set to the concept of Q-neutrosophic set and attaching the parameter of fuzzy set while defining a Q-neutrosophic soft expert set. This pattern carries the benefits of Q-neutrosophic sets and soft sets, enabling decision makers to recognize the views of specialists with no requirement for extra lumbering tasks, thus making it exceedingly reasonable for use in decision-making issues that include imprecise, indeterminate and inconsistent two-dimensional data. Some essential operations namely subset, equal, complement, union, intersection, AND and OR operations and additionally several properties relating to the notion of generalized Q-neutrosophic soft expert set are characterized. Finally, an algorithm on generalized Q-neutrosophic soft expert set is proposed and applied to a real-life example to show the efficiency of this notion in handling such problems.

]]>Symmetry doi: 10.3390/sym10110620

Authors: Min-Chul Shin Hae-Do Hwang Seung-Hyun Yoon Jieun Lee

We present a new method for constructing a parametric blending surface that smoothly connects two triangular meshes. A user selects a subregion on each triangular mesh. The local parameterizations of two selected regions are found by using geodesic polar coordinates, and a base surface on each triangular mesh is constructed by two boundary curves on parametric domain. Finally, two base surfaces are smoothly blended for generating a blending surface. The shape of a blending surface can easily be controlled by several shape parameters or by directly manipulating surface point. We demonstrate the effectiveness of our technique by showing several modeling examples.

]]>Symmetry doi: 10.3390/sym10110619

Authors: Jia-Bao Liu Haidar Ali Muhammad Shafiq Usman Munir

A Topological index also known as connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. In QSAR/QSPR study, physico-chemical properties and topological indices such as Randi c ´ , atom-bond connectivity (ABC) and geometric-arithmetic (GA) index are used to predict the bioactivity of chemical compounds. Graph theory has found a considerable use in this area of research. In this paper, we study HDCN1(m,n) and HDCN2(m,n) of dimension m , n and derive analytical closed results of general Randi c ´ index R α ( G ) for different values of α . We also compute the general first Zagreb, ABC, GA, A B C 4 and G A 5 indices for these Hex derived cage networks for the first time and give closed formulas of these degree-based indices.

]]>Symmetry doi: 10.3390/sym10110618

Authors: Qingxiang Meng Long Yan Yulong Chen Qiang Zhang

A columnar joint network is a natural fracture pattern with high symmetry, which leads to the anisotropy mechanical property of columnar basalt. For a better understanding the mechanical behavior, a novel modeling method for columnar jointed rock mass through field investigation is proposed in this paper. Natural columnar jointed networks lies between random and centroidal Voronoi tessellations. This heterogeneity of columnar cells in shape and area can be represented using the coefficient of variation, which can be easily estimated. Using the bisection method, a modified Lloyd&rsquo;s algorithm is proposed to generate a Voronoi diagram with a specified coefficient of variation. Modelling of the columnar jointed rock mass using six parameters is then presented. A case study of columnar basalt at Baihetan Dam is performed to demonstrate the feasibility of this method. The results show that this method is applicable in the modeling of columnar jointed rock mass as well as similar polycrystalline materials.

]]>Symmetry doi: 10.3390/sym10110617

Authors: Dmitry Victorovich Dolgy Dae San Kim Taekyun Kim Jongkyum Kwon

This paper treats the connection problem of expressing sums of finite products of Chebyshev polynomials of the third and fourth kinds in terms of five classical orthogonal polynomials. In fact, by carrying out explicit computations each of them are expressed as linear combinations of Hermite, generalized Laguerre, Legendre, Gegenbauer, and Jacobi polynomials which involve some terminating hypergeometric functions F 0 2 , F 1 2 , and F 2 3 .

]]>Symmetry doi: 10.3390/sym10110616

Authors: Jia Zhao Gang Sun

A recommender system can effectively solve the problem of information overload in the era of big data. Recent research on recommender systems, specifically Collaborative Filtering, has focused on Matrix Factorization methods, which have been shown to have excellent performance. However, these methods do not pay attention to the influence of a user&rsquo;s rating characteristics, which are especially important for the accuracy of prediction or recommendation. Therefore, in order to get better performance, we propose a novel method based on matrix factorization. We consider that the user&rsquo;s rating score is composed of two parts: the real score, which is decided by the user&rsquo;s preferences; and the bias score, which is decided by the user&rsquo;s rating characteristics. We then analyze the user&rsquo;s historical behavior to find his rating characteristics by using the matrix factorization technique and use them to adjust the final prediction results. Finally, by comparing with the latest algorithms on the open datasets, we verified that the proposed method can significantly improve the accuracy of recommender systems and achieve the best performance in terms of prediction accuracy criterion over other state-of-the-art methods.

]]>Symmetry doi: 10.3390/sym10110615

Authors: Barera Sarwar Imran Sarwar Bajwa Shabana Ramzan Bushra Ramzan Mubeen Kausar

Typical fire monitoring and warning systems use a single smoke detector that is connected to a fire management system to give early warnings before the fire spreads out up to a damaging level. However, it is found that only smoke detector-based fire monitoring systems are not efficient and intelligent since they generate false warnings in case of a person is smoking, etc. There is need of a multi-sensor based intelligent and smart fire monitoring system that employs various parameters, such as presence of flame, temperature of the room, smoke, etc. To achieve such a smart solution, a multi-sensor solution is required that can intelligently use the data of sensors and generate true warnings for further fire control and management. This paper presents an intelligent Fire Monitoring and Warning System (FMWS) that is based on Fuzzy Logic to identify the true existence of dangerous fire and send alert to Fire Management System (FMS). This paper discusses design and application of a Fuzzy Logic Fire Monitoring and Warning System that also sends an alert message using Global System for Mobile Communication (GSM) technology. The system is based on tiny, low cost, and very small in size sensors to ensure that the solution is reproduceable. Simulation work is done in MATLAB ver. 7.1 (The MathWorks, Natick, MA, USA) and the results of the experiments are satisfactory.

]]>Symmetry doi: 10.3390/sym10110614

Authors: Feng Qi Gauhar Rahman Sardar Hussain Wei-Shih Du Kottakkaran Nisar

In the article, the authors present several inequalities of the Čebyšev type for conformable k-fractional integral operators.

]]>Symmetry doi: 10.3390/sym10110613

Authors: Muhammad Gulistan Shah Nawaz Nasruddin Hassan

In this paper, we extended the idea of a neutrosophic triplet set to non-associative semihypergroups and define neutrosophic triplet LA-semihypergroup. We discuss some basic results and properties. At the end, we provide an application of the proposed structure in Football.

]]>Symmetry doi: 10.3390/sym10110612

Authors: Xianzhong Jian Chen Lv Ruzhi Wang

The fixed-pattern noise (FPN) caused by nonuniform optoelectronic response limits the sensitivity of an infrared imaging system and severely reduces the image quality. Therefore, nonuniform correction of infrared images is very important. In this paper, we propose a deep filter neural network to solve the problems of network underfitting and complex training with convolutional neural network (CNN) applications in nonuniform correction. Our work is mainly based on the idea of deep learning, where the nonuniform image noise features are fully learned from a large number of simulated training images. The network is designed by introducing the filter and the subtraction structure. The background interference of the image is removed by the filter, so the learning model is gathered in the nonuniform noise. The subtraction structure is used to further reduce the input-to-output mapping range, which effectively simplifies the training process. The results from the test on infrared images shows that our algorithm is superior to the state-of-the-art algorithm in visual effects and quantitative measurements, providing a new method for deep learning in nonuniformity correction of single images.

]]>Symmetry doi: 10.3390/sym10110611

Authors: Michal Novák Štepán Křehlík Irina Cristea

In the algebra of single-valued structures, cyclicity is one of the fundamental properties of groups. Therefore, it is natural to study it also in the algebra of multivalued structures (algebraic hyperstructure theory). However, when one considers the nature of generalizing this property, at least two (or rather three) approaches seem natural. Historically, all of these had been introduced and studied by 1990. However, since most of the results had originally been published in journals without proper international impact and later—without the possibility to include proper background and context-synthetized in books, the current way of treating the concept of cyclicity in the algebraic hyperstructure theory is often rather confusing. Therefore, we start our paper with a rather long introduction giving an overview and motivation of existing approaches to the cyclicity in algebraic hyperstructures. In the second part of our paper, we relate these to E L -hyperstructures, a broad class of algebraic hyperstructures constructed from (pre)ordered (semi)groups, which were defined and started to be studied much later than sources discussed in the introduction were published.

]]>Symmetry doi: 10.3390/sym10110610

Authors: Senquan Yang Pu Li HaoXiang Wen Yuan Xie Zhaoshui He

Color image segmentation is very important in the field of image processing as it is commonly used for image semantic recognition, image searching, video surveillance or other applications. Although clustering algorithms have been successfully applied for image segmentation, conventional clustering algorithms such as K-means clustering algorithms are not sufficiently robust to illumination changes, which is common in real-world environments. Motivated by the observation that the RGB value distributions of the same color under different illuminations are located in an identical hyperline, we formulate color classification as a hyperline clustering problem. We then propose a K-hyperline clustering algorithm-based color image segmentation approach. Experiments on both synthetic and real images demonstrate the outstanding performance and robustness of the proposed algorithm as compared to existing clustering algorithms.

]]>Symmetry doi: 10.3390/sym10110609

Authors: Marina Bardamova Anton Konev Ilya Hodashinsky Alexander Shelupanov

This paper concerns several important topics of the Symmetry journal, namely, pattern recognition, computer-aided design, diversity and similarity. We also take advantage of the symmetric and asymmetric structure of a transfer function, which is responsible to map a continuous search space to a binary search space. A new method for design of a fuzzy-rule-based classifier using metaheuristics called Gravitational Search Algorithm (GSA) is discussed. The paper identifies three basic stages of the classifier construction: feature selection, creating of a fuzzy rule base and optimization of the antecedent parameters of rules. At the first stage, several feature subsets are obtained by using the wrapper scheme on the basis of the binary GSA. Creating fuzzy rules is a serious challenge in designing the fuzzy-rule-based classifier in the presence of high-dimensional data. The classifier structure is formed by the rule base generation algorithm by using minimum and maximum feature values. The optimal fuzzy-rule-based parameters are extracted from the training data using the continuous GSA. The classifier performance is tested on real-world KEEL (Knowledge Extraction based on Evolutionary Learning) datasets. The results demonstrate that highly accurate classifiers could be constructed with relatively few fuzzy rules and features.

]]>Symmetry doi: 10.3390/sym10110608

Authors: Wei Fang Wei-Hua Liu Jia-Bao Liu Fu-Yuan Chen Zhen-Mu Hong Zheng-Jiang Xia

The definition of a Detour&ndash;Harary index is &omega; H ( G ) = 1 2 &sum; u , v &isin; V ( G ) 1 l ( u , v | G ) , where G is a simple and connected graph, and l ( u , v | G ) is equal to the length of the longest path between vertices u and v. In this paper, we obtained the maximum Detour&ndash;Harary index about unicyclic graphs, bicyclic graphs, and cacti, respectively.

]]>Symmetry doi: 10.3390/sym10110607

Authors: Jianwei Lu Yixuan Xu Mingle Chen Ye Luo

Fundus vessel analysis is a significant tool for evaluating the development of retinal diseases such as diabetic retinopathy and hypertension in clinical practice. Hence, automatic fundus vessel segmentation is essential and valuable for medical diagnosis in ophthalmopathy and will allow identification and extraction of relevant symmetric and asymmetric patterns. Further, due to the uniqueness of fundus vessel, it can be applied in the field of biometric identification. In this paper, we remold fundus vessel segmentation as a task of pixel-wise classification task, and propose a novel coarse-to-fine fully convolutional neural network (CF-FCN) to extract vessels from fundus images. Our CF-FCN is aimed at making full use of the original data information and making up for the coarse output of the neural network by harnessing the space relationship between pixels in fundus images. Accompanying with necessary pre-processing and post-processing operations, the efficacy and efficiency of our CF-FCN is corroborated through our experiments on DRIVE, STARE, HRF and CHASE DB1 datasets. It achieves sensitivity of 0.7941, specificity of 0.9870, accuracy of 0.9634 and Area Under Receiver Operating Characteristic Curve (AUC) of 0.9787 on DRIVE datasets, which surpasses the state-of-the-art approaches.

]]>Symmetry doi: 10.3390/sym10110606

Authors: Selçuk Baş

This paper presents a new type of spacelike magnetic curves associated with the Sabban vector field defined in the Minkowski space. In this approach, some geometrical and physical features of the moving charged particle corresponding to the spacelike magnetic curves are identified. An entire characterization is developed for spacelike spherical magnetic curves, denoting particularly the changes of their energy with respect to time, the influence of the magnetic force on them, and the existence condition for the uniformity of these curves.

]]>Symmetry doi: 10.3390/sym10110605

Authors: Sang-Ick Kang Sangmin Lee

The competition of speech recognition technology related to smartphones is now getting into full swing with the widespread internet of thing (IoT) devices. For robust speech recognition, it is necessary to detect speech signals in various acoustic environments. Speech/music classification that facilitates optimized signal processing from classification results has been extensively adapted as an essential part of various electronics applications, such as multi-rate audio codecs, automatic speech recognition, and multimedia document indexing. In this paper, we propose a new technique to improve robustness of a speech/music classifier for an enhanced voice service (EVS) codec adopted as a voice-over-LTE (VoLTE) speech codec using long short-term memory (LSTM). For effective speech/music classification, feature vectors implemented with the LSTM are chosen from the features of the EVS. To overcome the diversity of music data, a large scale of data is used for learning. Experiments show that LSTM-based speech/music classification provides better results than the conventional EVS speech/music classification algorithm in various conditions and types of speech/music data, especially at lower signal-to-noise ratio (SNR) than conventional EVS algorithm.

]]>Symmetry doi: 10.3390/sym10110604

Authors: Shawn Witte Michelle Flanner Mariel Vazquez

Proper identification of oriented knots and 2-component links requires a precise link nomenclature. Motivated by questions arising in DNA topology, this study aims to produce a nomenclature unambiguous with respect to link symmetries. For knots, this involves distinguishing a knot type from its mirror image. In the case of 2-component links, there are up to sixteen possible symmetry types for each link type. The study revisits the methods previously used to disambiguate chiral knots and extends them to oriented 2-component links with up to nine crossings. Monte Carlo simulations are used to report on writhe, a geometric indicator of chirality. There are ninety-two prime 2-component links with up to nine crossings. Guided by geometrical data, linking number, and the symmetry groups of 2-component links, canonical link diagrams for all but five link types (9 5 2, 9 34 2, 9 35 2, 9 39 2, and 9 41 2) are proposed. We include complete tables for prime knots with up to ten crossings and prime links with up to nine crossings. We also prove a result on the behavior of the writhe under local lattice moves.

]]>Symmetry doi: 10.3390/sym10110603

Authors: Santoso Wibowo Srimannarayana Grandhi

This paper presents a fuzzy multicriteria analysis model for evaluating the performance of Internet of Things (IoT)-based supply chains. The inherent uncertainty and imprecision of the performance evaluation process was handled by using intuitionistic fuzzy numbers. A new fuzzy multicriteria group decision making algorithm based on the technique ordered preference by similarity to the ideal solution (TOPSIS) approach, and the concept of similarity measures was developed for determining the overall performance of each alternative. The advantage of the proposed fuzzy multicriteria analysis model is that it can overcome the limitations of the existing approaches in an intuitionistic fuzzy environment. The fuzzy multicriteria group decision-making model provides organizations with the ability to evaluate the performance of their IoT-based supply chains for improving their competitiveness. An example is presented to highlight the usefulness of the proposed model for tackling a real world IoT performance evaluation problem.

]]>Symmetry doi: 10.3390/sym10110602

Authors: Donghai Liu Xiaohong Chen Dan Peng

This paper proposes a neutrosophic hesitant fuzzy linguistic term set (NHFLTS) based on hesitant fuzzy linguistic term set (HFLTS) and neutrosophic set (NS), which can express the inconsistent and uncertainty information flexibly in multiple criteria decision making problems. The basic operational laws of NHFLTS based on linguistic scale function are also discussed. Then we propose the generalized neutrosophic hesitant fuzzy linguistic distance measure and discuss its properties. Furthermore, a new similarity measure of NHFLTS combines the generalized neutrosophic hesitant fuzzy linguistic distance measure and the cosine function is given. A corresponding cosine distance measure between NHFLTSs is proposed according to the relationship between the similarity measure and the distance measure, and we develop the technique for order preference by similarity to an ideal solution (TOPSIS) method to the obtained cosine distance measure. The main advantages of the proposed NHFLTS is defined on linguistic scale function, the decision makers can flexibly convert the linguistic information to semantic values, and the proposed cosine distance measure between NHFLTSs with TOPSIS method can deal with the related decision information not only from the point of view of algebra, but also from the point of view of geometry. Finally, the reasonableness and effectiveness of the proposed method is demonstrated by the illustrative example, which is also compared to the other existing methods.

]]>Symmetry doi: 10.3390/sym10110601

Authors: Orest D. Artemovych Alexander A. Balinsky Denis Blackmore Anatolij K. Prykarpatski

The Lie algebraic scheme for constructing Hamiltonian operators is differential-algebraically recast and an effective approach is devised for classifying the underlying algebraic structures of integrable Hamiltonian systems. Lie&ndash;Poisson analysis on the adjoint space to toroidal loop Lie algebras is employed to construct new reduced pre-Lie algebraic structures in which the corresponding Hamiltonian operators exist and generate integrable dynamical systems. It is also shown that the Balinsky&ndash;Novikov type algebraic structures, obtained as a Hamiltonicity condition, are derivations on the Lie algebras naturally associated with differential toroidal loop algebras. We study nonassociative and noncommutive algebras and the related Lie-algebraic symmetry structures on the multidimensional torus, generating via the Adler&ndash;Kostant&ndash;Symes scheme multi-component and multi-dimensional Hamiltonian operators. In the case of multidimensional torus, we have constructed a new weak Balinsky&ndash;Novikov type algebra, which is instrumental for describing integrable multidimensional and multicomponent heavenly type equations. We have also studied the current algebra symmetry structures, related with a new weakly deformed Balinsky&ndash;Novikov type algebra on the axis, which is instrumental for describing integrable multicomponent dynamical systems on functional manifolds. Moreover, using the non-associative and associative left-symmetric pre-Lie algebra theory of Zelmanov, we also explicate Balinsky&ndash;Novikov algebras, including their fermionic version and related multiplicative and Lie structures.

]]>Symmetry doi: 10.3390/sym10110600

Authors: Genghua Yu Zhigang Chen Jia Wu Jian Wu

The amount of data has skyrocketed in Fifth-generation (5G) networks. How to select an appropriate node to transmit information is important when we analyze complex data in 5G communication. We could sophisticate decision-making methods for more convenient data transmission, and opportunistic complex social networks play an increasingly important role. Users can adopt it for information sharing and data transmission. However, the encountering of nodes in mobile opportunistic network is random. The latest probabilistic routing method may not consider the social and cooperative nature of nodes, and could not be well applied to the large data transmission problem of social networks. Thus, we quantify the social and cooperative relationships symmetrically between the mobile devices themselves and the nodes, and then propose a routing algorithm based on an improved probability model to predict the probability of encounters between nodes (PEBN). Since our algorithm comprehensively considers the social relationship and cooperation relationship between nodes, the prediction result of the target node can also be given without encountering information. The neighbor nodes with higher probability are filtered by the prediction result. In the experiment, we set the node&rsquo;s selfishness randomly. The simulation results show that compared with other state-of-art transmission models, our algorithm has significantly improved the message delivery rate, hop count, and overhead.

]]>Symmetry doi: 10.3390/sym10110599

Authors: Huafeng Zhang Quanxin Sun

Railway special line shunting safety is a complicated systemic topic, which is full of uncertainty and dynamic; safety is determined by numerous aspects, including human, management, environmental, and equipment factors. Many railway risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools gives unsatisfactory results because the risk data are incomplete or involve high levels of uncertainty. Because risk assessment technology has its own applicability that it may not suitable for the three sub-processes of risk assessment, it is difficult to obtain ideal effects by using a single tool in the risk assessment process. This paper presents an integrated approach for conducting special-line shunting risk assessment, using fishbone diagram analysis, fuzzy reasoning approaches, and a fuzzy analytical hierarchy tool, which can evaluate both qualitative and quantitative risk data efficiently and effectively. The outcomes of risk assessment are represented as risk degrees and risk levels, providing railway safety risk managers and engineers with tools to improve their safety management standards. A case study is used to demonstrate the proposed methodology. The results reveal that the proposed model can effectively and efficiently assess risks associated with a special-line shunting system, yielding more reliable and realistic solutions.

]]>Symmetry doi: 10.3390/sym10110598

Authors: Nabilah Abughazalah Naveed Yaqoob

This paper concerns three relationship between the recently proposed cubic sets and finite state machines. The notions of cubic finite state machine (cubic FSM), a subsystem of cubic FSM and cartesian composition (direct product, P-(R-) union, and P-(R-) intersection) of two subsystems of cubic FSMs are introduced. We study the cartesian composition, direct product and union of two subsystems of cubic FSMs is a subsystem of a cubic FSM. We provide many examples on each case. We consider conditions for subsystem of cubic FSM to be both an internal cubic subsystem of cubic FSM and an external cubic subsystem of cubic FSM.

]]>Symmetry doi: 10.3390/sym10110597

Authors: Yi-Hui Xu Jin-Lin Liu

We derive several properties such as convolution and partial sums of multivalent analytic functions associated with an operator involving Srivastava&ndash;Tomovski generalization of the Mittag&ndash;Leffler function.

]]>Symmetry doi: 10.3390/sym10110596

Authors: Fabian Kislat

Theories of quantum gravity suggest that Lorentz invariance, the fundamental symmetry of the Theory of Relativity, may be broken at the Planck energy scale. While any deviation from conventional Physics must be minuscule in particular at attainable energies, this hypothesis motivates ever more sensitive tests of Lorentz symmetry. In the photon sector, astrophysical observations, in particular polarization measurements, are a very powerful tool because tiny deviations from Lorentz invariance will accumulate as photons propagate over cosmological distances. The Standard-Model Extension (SME) provides a theoretical framework in the form of an effective field theory that describes low-energy effects due to a more fundamental quantum gravity theory by adding additional terms to the Standard Model Lagrangian. These terms can be ordered by the mass dimension d of the corresponding operator and lead to a wavelength, polarization, and direction dependent phase velocity of light. Lorentz invariance violation leads to an energy-dependent change of the Stokes vector as photons propagate, which manifests itself as a rotation of the polarization angle in measurements of linear polarization. In this paper, we analyze optical polarization measurements from 63 Active Galactic Nuclei (AGN) and Gamma-ray Bursts (GRBs) to search for Lorentz violating signals. We use both spectropolarimetric measurements, which directly constrain the change of linear polarization angle, as well as broadband spectrally integrated measurements. In the latter, Lorentz invariance violation manifests itself by reducing the observed net polarization fraction. Any observation of non-vanishing linear polarization thus leads to constraints on the magnitude of Lorentz violating effects. We derive the first set limits on each of the 10 individual birefringent coefficients of the minimal SME with d = 4 , with 95% confidence limits on the order of 10&minus;34 on the dimensionless coefficients.

]]>Symmetry doi: 10.3390/sym10110595

Authors: Guiyue Kou Xinghu Li Yan Wang Mouyou Lin Yuping Zeng Xiaopin Yang Yanyan Yang Zhimei Gan

The airflow dynamics observed during a cough process in a CT-scanned respiratory airway model were numerically analyzed using the computational fluid dynamics (CFD) method. The model and methodology were validated by a comparison with published experimental results. The influence of the cough peak flow rate on airflow dynamics and flow distribution was studied. The maximum velocity, wall pressure, and wall shear stress increased linearly as the cough peak flow increased. However, the cough peak flow rate had little influence on the flow distribution of the left and right main bronchi during the cough process. This article focuses on the mathematical and numerical modelling for human cough process in bioengineering.

]]>Symmetry doi: 10.3390/sym10110594

Authors: Tri D. T. Nguyen Tien-Dung Nguyen Van Dung Nguyen Xuan-Qui Pham Eui-Nam Huh

By bringing the computation and storage resources close proximity to the mobile network edge, mobile edge computing (MEC) is a key enabling technology for satisfying the Internet of Vehicles (IoV) infotainment applications&rsquo; requirements, e.g., video streaming service (VSA). However, the explosive growth of mobile video traffic brings challenges for video streaming providers (VSPs). One known issue is that a huge traffic burden on the vehicular network leads to increasing VSP costs for providing VSA to mobile users (i.e., autonomous vehicles). To address this issue, an efficient resource sharing scheme between underutilized vehicular resources is a promising solution to reduce the cost of serving VSA in the vehicular network. Therefore, we propose a new VSA model based on the lower cost of obtaining data from vehicles and then minimize the VSP&rsquo;s cost. By using existing data resources from nearby vehicles, our proposal can reduce the cost of providing video service to mobile users. Specifically, we formulate our problem as mixed integer nonlinear programming (MINP) in order to calculate the total payment of the VSP. In addition, we introduce an incentive mechanism to encourage users to rent its resources. Our solution represents a strategy to optimize the VSP serving cost under the quality of service (QoS) requirements. Simulation results demonstrate that our proposed mechanism is possible to achieve up to 21% and 11% cost-savings in terms of the request arrival rate and vehicle speed, in comparison with other existing schemes, respectively.

]]>Symmetry doi: 10.3390/sym10110593

Authors: Hongran Zhang Runtong Zhang Huiqun Huang Wang

As an extension of the intuitionistic fuzzy set (IFS), the recently proposed picture fuzzy set (PFS) is more suitable to describe decision-makers&rsquo; evaluation information in decision-making problems. Picture fuzzy aggregation operators are of high importance in multi-attribute decision-making (MADM) within a picture fuzzy decision-making environment. Hence, in this paper our main work is to introduce novel picture fuzzy aggregation operators. Firstly, we propose new picture fuzzy operational rules based on Dombi t-conorm and t-norm (DTT). Secondly, considering the existence of a broad and widespread correlation between attributes, we use Heronian mean (HM) information aggregation technology to fuse picture fuzzy numbers (PFNs) and propose new picture fuzzy aggregation operators. The proposed operators not only fuse individual attribute values, but also have a good ability to model the widespread correlation among attributes, making them more suitable for effectively solving increasingly complicated MADM problems. Hence, we introduce a new algorithm to handle MADM based on the proposed operators. Finally, we apply the newly developed method and algorithm in a supplier selection issue. The main novelties of this work are three-fold. Firstly, new operational laws for PFSs are proposed. Secondly, novel picture fuzzy aggregation operators are developed. Thirdly, a new approach for picture fuzzy MADM is proposed.

]]>Symmetry doi: 10.3390/sym10110592

Authors: Mohammad Abudayah Omar Alomari Al Ezeh Ezeh

The geodetic number of a graph is an important graph invariant. In 2002, Atici showed the geodetic set determination of a graph is an NP-Complete problem. In this paper, we compute the geodetic set and geodetic number of an important class of graphs called the k-th power of a cycle. This class of graphs has various applications in Computer Networks design and Distributed computing. The k-th power of a cycle is the graph that has the same set of vertices as the cycle and two different vertices in the k-th power of this cycle are adjacent if the distance between them is at most k.

]]>Symmetry doi: 10.3390/sym10110591

Authors: Jinke Wang Changfa Shi Yuanzhi Cheng Xiancheng Zhou Shinichi Tamura

In this paper, a novel 3D vector field convolution (VFC)-based B-spline deformation model is proposed for accurate and robust cartilage segmentation. Firstly, the anisotropic diffusion method is utilized for noise reduction, and the Sinc interpolation method is employed for resampling. Then, to extract the rough cartilage, features derived from Hessian matrix are chosen to enhance the cartilage, followed by binarizing the images via an optimal thresholding method. Finally, the proposed VFC-based B-spline deformation model is used to refine the rough segmentation. In the experiments, the proposed method was evaluated and demonstrated on 46 magnetic resonance images (MRI) (including 20 hip joints and 26 knee joints), and the results were compared with three state-of-the-art cartilage segmentation methods. Both qualitative and quantitative segmentation results indicate that the proposed method can be deployed for accurate and robust cartilage segmentation. Furthermore, from the segmentation results, patient-specific 3D models of the patient&rsquo;s anatomy can be derived, which then can be utilized in a wide range of clinical applications, such as 3D visualization for surgical planning and guidance.

]]>Symmetry doi: 10.3390/sym10110590

Authors: Xiaohui Wu Jie Qian Juanjuan Peng Changchun Xue

Single valued trapezoidal neutrosophic numbers (SVTNNs) are very useful tools for describing complex information, because of their advantage in describing the information completely, accurately and comprehensively for decision-making problems. In the paper, a method based on SVTNNs is proposed for dealing with multi-criteria group decision-making (MCGDM) problems. Firstly, the new operations SVTNNs are developed for avoiding evaluation information aggregation loss and distortion. Then the possibility degrees and comparison of SVTNNs are proposed from the probability viewpoint for ranking and comparing the single valued trapezoidal neutrosophic information reasonably and accurately. Based on the new operations and possibility degrees of SVTNNs, the single valued trapezoidal neutrosophic power average (SVTNPA) and single valued trapezoidal neutrosophic power geometric (SVTNPG) operators are proposed to aggregate the single valued trapezoidal neutrosophic information. Furthermore, based on the developed aggregation operators, a single valued trapezoidal neutrosophic MCGDM method is developed. Finally, the proposed method is applied to solve the practical problem of the most appropriate green supplier selection and the rank results compared with the previous approach demonstrate the proposed method&rsquo;s effectiveness.

]]>Symmetry doi: 10.3390/sym10110589

Authors: Marcin Ciecholewski Jan H. Spodnik

Accurate 3D computer models of the brain, and also of parts of its structure such as the corpus callosum (CC) are increasingly used in routine clinical diagnostics. This study presents comparative research to assess the utility and performance of three active contour methods (ACMs) for segmenting the CC from magnetic resonance (MR) images of the brain, namely: an edge-based active contour model using an inflation/deflation force with a damping coefficient (EM), the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method and the Distance Regularized Level Set Evolution (DRLSE) method. The pre-processing methods applied during research work were to improve the contrast, reduce noise and thus help segment the CC better. In this project, 3D CC models reconstructed based on the segmentations of cross-sections of MR images were also visualised. The results, as measured by quantitative tests of the similarity indice (SI) and overlap value (OV) are the best for the EM model (SI = 92%, OV = 82%) and are comparable to or better than those for other methods taken from a literature review. Furthermore, the properties of the EM model consisting in its ability to both expand and shrink at the same time allow segmentations to be better fitted in subsequent CC slices then in state-of-the art ACMs such as DRLSE or SBGFRLS. The CC contours from previous and subsequent iterations produced by the EM model can be used for initiation in subsequent or previous frames of MR images, which makes the segmentation process easier, particularly as the CC area can increase or decrease in subsequent MR image frames.

]]>Symmetry doi: 10.3390/sym10110588

Authors: Bo Du Hong Zhou

In this study, we apply a robust optimization approach to a p-center facility location problem under uncertainty. Based on a symmetric interval and a multiple allocation strategy, we use three types of uncertainty sets to formulate the robust problem: box uncertainty, ellipsoidal uncertainty, and cardinality-constrained uncertainty. The equivalent robust counterpart models can be solved to optimality using Gurobi. Comprehensive numerical experiments have been conducted by comparing the performance of the different robust models, which illustrate the pattern of robust solutions, and allocating a demand node to multiple facilities can reduce the price of robustness, and reveal that alternative models of uncertainty can provide robust solutions with different conservativeness.

]]>Symmetry doi: 10.3390/sym10110587

Authors: Jun Wang Pengcheng Luo Xinwu Hu Xiaonan Zhang

Uncertainty should be taken into account when establishing multiobjective task assignment models for multiple unmanned combat aerial vehicles (UCAVs) due to errors in the target information acquired by sensors, implicit preferences of the commander for operational objectives, and partially known weights of sensors. In this paper, we extend the stochastic multicriteria acceptability analysis-2 (SMAA-2) method and combine it with integer linear programming to achieve multiobjective task assignment for multi-UCAV under multiple uncertainties. We first represent the uncertain target information as normal distribution interval numbers so that the values of criteria (operational objectives) concerned can be computed based on the weighted arithmetic averaging operator. Thus, we obtain multiple criteria value matrices for each UCAV. Then, we propose a novel aggregation method to generate the final criteria value matrix based on which the holistic acceptability indices are computed by the extended SMAA-2 method. On this basis, we convert the task assignment model with uncertain parameters into an integer linear programming model without uncertainty so as to implement task assignment using the integer linear programming method. Finally, we conduct a case study and demonstrate the feasibility of the proposed method in solving the multiobjective task assignment problem multi-UCAV under multiple uncertainties.

]]>Symmetry doi: 10.3390/sym10110586

Authors: Željko Stević Željko Stjepanović Zdravko Božičković Dillip Kumar Das Dragiša Stanujkić

The application of information technology in all areas represents a significant facilitation of all business processes and activities. A competitive business system is hardly imaginable without adequate information technology. Therefore, this paper evaluates the conditions for the implementation of barcode technology in a warehouse system of a company for the manufacture of brown paper. SWOT (Strengths, Weaknesses, Opportunities, Threats) matrix was formed with a total of 27 elements based on which the benefits of the implementation of barcode technology in the warehouse system need to be analysed. For this purpose, a new fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been developed to evaluate all elements in SWOT matrix. In addition, a part of the new developed approach includes new fuzzy scales for criterion assessment that are adapted to the methodology required by the fuzzy PIPRECIA method. To determine the consistency of the method, Spearman and Pearson correlation coefficients are applied. The results obtained in this study show that weaknesses are most noticeable in the current system. By implementing barcode technology, it is possible to create opportunities defined in SWOT matrix, which, in a very efficient way, allow elimination of the current weaknesses of the system.

]]>Symmetry doi: 10.3390/sym10110585

Authors: Eleonora Di Valentino Sarah Bridle

This paper provides a snapshot of the formal S 8 &equiv; &sigma; 8 &Omega; m / 0.3 tension between Planck 2015 and the Kilo Degree Survey of450 deg 2 of imaging data (KiDS-450) or the Canada France Hawaii Lensing Survey (CFHTLenS). We find that the Cosmic Microwave Bckground (CMB) and cosmic shear datasets are in tension in the standard &Lambda; Cold Dark Matter ( &Lambda; CDM) model, and that adding massive neutrinos does not relieve the tension. If we include an additional scaling parameter on the CMB lensing amplitude A l e n s , we find that this can put in agreement the Planck 2015 with the cosmic shear data. A l e n s is a phenomenological parameter that is found to be more than 2 &sigma; higher than the expected value in the Planck 2015 data, suggesting an higher amount of lensing in the power spectra, not supported by the trispectrum analysis.

]]>Symmetry doi: 10.3390/sym10110584

Authors: Ana Reyes-Menendez Jose Ramon Saura Pedro R. Palos-Sanchez Jose Alvarez-Garcia

An increase in users&rsquo; online searches, the social concern for an efficient management of resources such as water, and the appearance of more and more digital platforms for sustainable purposes to conduct online searches lead us to reflect more on the users&rsquo; behavioral intention with respect to search engines that support sustainable projects like water management projects. Another issue to consider is the factors that determine the adoption of such search engines. In the present study, we aim to identify the factors that determine the intention to adopt a search engine, such as Lilo, that favors sustainable water management. To this end, a model based on the Theory of Planned Behavior (TPB) is proposed. The methodology used is the Structural Equation Modeling (SEM) analysis with the Analysis of Moment Structures (AMOS). The results demonstrate that individuals who intend to use a search engine are influenced by hedonic motivations, which drive their feeling of contentment with the search. Similarly, the success of search engines is found to be closely related to the ability a search engine grants to its users to generate a social or environmental impact, rather than users&rsquo; trust in what they do or in their results. However, according to our results, habit is also an important factor that has both a direct and an indirect impact on users&rsquo; behavioral intention to adopt different search engines.

]]>Symmetry doi: 10.3390/sym10110581

Authors: Weilong Yang Yue Hu Cong Hu Mei Yang

With the gradual expansion of high buildings and underground spaces, deep foundation pits have been widely used in these engineering projects, but if they are not well-designed, safety problems occur. Proper deep foundation pit design requires proper exit distribution. However, calculating an adequate number of exit distributions for evaluation is difficult due to the numerous influential factors existing in the deep foundation pit environment. To this end, this paper presents a prototype of a decision-making system that uses agent-based modeling to simulate deep foundation pit evacuation in the presence of collapse disaster. By modeling the collapse occurrence process and agent escape process, an agent-based evacuation model is built, and a modified simulation-based particle swarm optimization algorithm is used to solve the optimization problem of exit distribution. Extensive experiments are conducted to verify the system, and the results show that the system provides a feasible framework for deep foundation pit evacuation.

]]>Symmetry doi: 10.3390/sym10110583

Authors: Jianhong Xiang Huihui Yue Xiangjun Yin Guoqing Ruan

Sparse-signal recovery in noisy conditions is a problem that can be solved with current compressive-sensing (CS) technology. Although current algorithms based on L 1 regularization can solve this problem, the L 1 regularization mechanism cannot promote signal sparsity under noisy conditions, resulting in low recovery accuracy. Based on this, we propose a regularized reweighted composite trigonometric smoothed L 0 -norm minimization (RRCTSL0) algorithm in this paper. The main contributions of this paper are as follows: (1) a new smoothed symmetric composite trigonometric (CT) function is proposed to fit the L 0 -norm; (2) a new reweighted function is proposed; and (3) a new L 0 regularization objective function framework is constructed based on the idea of T i k h o n o v regularization. In the new objective function framework, Contributions (1) and (2) are combined as sparsity regularization terms, and errors as deviation terms. Furthermore, the conjugate-gradient (CG) method is used to optimize the objective function, so as to achieve accurate recovery of sparse signal and image under noisy conditions. The numerical experiments on both the simulated and real data verify that the proposed algorithm is superior to other state-of-the-art algorithms, and achieves advanced performance under noisy conditions.

]]>Symmetry doi: 10.3390/sym10110582

Authors: Nafaa Chbili Shamma Al Dhaheri Mei Y. Tahnon Amna A. E. Abunamous

In this paper, we study the way the symmetries of a given graph are reflected in its characteristic polynomials. Our aim is not only to find obstructions for graph symmetries in terms of its polynomials but also to measure how faithful these algebraic invariants are with respect to symmetry. Let p be an odd prime and &Gamma; be a finite graph whose automorphism group contains an element h of order p. Assume that the finite cyclic group generated by h acts semi-freely on the set of vertices of &Gamma; with fixed set F. We prove that the characteristic polynomial of &Gamma; , with coefficients in the finite field of p elements, is the product of the characteristic polynomial of the induced subgraph &Gamma; [ F ] by one of &Gamma; \ F . A similar congruence holds for the characteristic polynomial of the Laplacian matrix of &Gamma; .

]]>Symmetry doi: 10.3390/sym10110580

Authors: Xiao-Dong Yang Li-Kun Xiao Chun-Lin Chen Cai-Fen Wang

With the rapid popularization of the Internet of Things (IoT) in our daily lives, the communication security and identity privacy of IoT devices must be ensured. However, traditional authentication mechanisms utilized in IoT cannot completely ensure a user&rsquo;s privacy when his/her messages are routed via an untrusted intermediate device. Strong designated-verifier proxy re-signature (SDVPRS) is a new cryptographic technology that combines the advantages of strong designated verifier signature and proxy re-signature. Therefore, SDVPRS is considered to be a better approach to maintain data integrity and protect the identity privacy of the signer in a resource-limited IoT device. Nevertheless, designing a secure SDVPRS scheme without random oracles is still a challenging task. In this paper, we mainly focus on such a construction by providing a new method. We first provide the formal definition of SDVPRS and its security model. Then, we present the first SDVPRS scheme, which is bidirectional, multi-use and non-transferable, and we prove its security under the standard complexity assumptions in the standard model. The analysis results show that our SDVPRS scheme can not only protect the privacy of the signer&rsquo;s identity, but also provide non-delegatability for signature verification. We present an example of potential application to environmental monitoring systems using our SDVPRS scheme.

]]>Symmetry doi: 10.3390/sym10110579

Authors: Lei Jin Haiyan Fu Younggy Kim Li Wang Huiyan Cheng Guohe Huang

In this study, a new &alpha;-representation of the inexact T2 fuzzy sets programming model (&alpha;-RITF2SP) is proposed for water resources planning under uncertainties. The developed model is a hybrid of inexact type-2 (T2) fuzzy sets (FSs) optimal programming based on &alpha;-cuts and &alpha;-planes (z-slices) algorithms, and both can be used in problems of water resource management without a loss of generality. Therefore, this novel method represents a complementary method to combine both of these algorithms to make inexact T2FSs methods easier and faster for users under uncertainties. This method provides not only a reduction in computations when computing fuzzy functions, but also a map of the primary variable of T2FSs in the secondary membership function. The &alpha;-RITF2SP is applied to a real case study of the operation of water resource systems in the southern Min River basin that involves three cities: Xiamen, Zhangzhou, and Quanzhou. The results of the water allocations and benefits have been analyzed. The symptoms of results indicate the higher profit with a higher wastewater treatment rate. It also represents that this model has enhanced abilities and it is relevant and practical as well as can serve as a guide for the development of this regional economy.

]]>Symmetry doi: 10.3390/sym10110578

Authors: Chunxin Bo Xiaohong Zhang Songtao Shao Florentin Smarandache

After the neutrosophic set (NS) was proposed, NS was used in many uncertainty problems. The single-valued neutrosophic set (SVNS) is a special case of NS that can be used to solve real-word problems. This paper mainly studies multigranulation neutrosophic rough sets (MNRSs) and their applications in multi-attribute group decision-making. Firstly, the existing definition of neutrosophic rough set (we call it type-I neutrosophic rough set (NRSI) in this paper) is analyzed, and then the definition of type-II neutrosophic rough set (NRSII), which is similar to NRSI, is given and its properties are studied. Secondly, a type-III neutrosophic rough set (NRSIII) is proposed and its differences from NRSI and NRSII are provided. Thirdly, single granulation NRSs are extended to multigranulation NRSs, and the type-I multigranulation neutrosophic rough set (MNRSI) is studied. The type-II multigranulation neutrosophic rough set (MNRSII) and type-III multigranulation neutrosophic rough set (MNRSIII) are proposed and their different properties are outlined. We found that the three kinds of MNRSs generate tcorresponding NRSs when all the NRs are the same. Finally, MNRSIII in two universes is proposed and an algorithm for decision-making based on MNRSIII is provided. A car ranking example is studied to explain the application of the proposed model.

]]>Symmetry doi: 10.3390/sym10110575

Authors: He Wang Hua Song

For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then, ABC algorithm is utilized to determine a proper threshold shrinking IMF coefficients instead of traditional threshold function. Furthermore, a neighborhood search strategy is introduced into ABC algorithm to balance its exploration and exploitation ability. Simulation experiments are conducted on four benchmark signals, and a comparative study for the proposed method and state-of-the-art methods are carried out. The compared results demonstrate that signal to noise ratio (SNR) and root mean square error (RMSE) are obtained by the proposed method. The conduction of which is finished on actual grain flow signal that is with noise for the demonstration of the effect in actual practice.

]]>Symmetry doi: 10.3390/sym10110577

Authors: Martiros Khurshudyan Asatur Zh. Khurshudyan

In this paper, we study various cosmological models involving new nonlinear forms of interaction between cold dark matter (DM) and dark energy (DE) assuming that DE is a barotropic fluid. The interactions are nonlinear either due to log ( &rho; d e / &rho; d m ) or log ( &rho; d m / &rho; d e ) parameterizations, respectively. The main purpose of this paper is to demonstrate the applicability of the forms of suggested interactions to the problem of modern cosmology known as accelerated expansion of the Universe. Using the differential age of old galaxies expressed in terms of H ( z ) data, the peak position of baryonic acoustic oscillations (known as BAO data), the SN Ia data with strong gravitational lensing data, we obtain the best fit values of the model parameters for each case. Besides, using O m analysis and S 3 parameter from the statefinder hierarchy analysis, we also demonstrate that the considered models are clearly different from the &Lambda; CDM model. We obtain that the models predict Hubble parameter values consistent to the estimations from gravitational lensing, which probes the expansion out to z &le; 1.7 . We show that, with considered models, we can also explain PLANCK 2015 and PLANCK 2018 experiment results.

]]>Symmetry doi: 10.3390/sym10110576

Authors: Naadiya Khuda Bux Mingming Lu Jianxin Wang Saajid Hussain Yazan Aljeroudi

In today&rsquo;s world, millions of transactions are connected to online businesses, and the main challenging task is ensuring the privacy of sensitive information. Sensitive association rules hiding (SARH) is an important goal of privacy protection algorithms. Various approaches and algorithms have been developed for sensitive association rules hiding, differentiated according to their hiding performance through utility preservation, prevention of ghost rules, and computational complexity. A meta-heuristic algorithm is a good candidate to solve the problem of SARH due to its selective and parallel search behavior, avoiding local minima capability. This paper proposes simple genetic encoding for SARH. The proposed algorithm formulates an objective function that estimates the effect on nonsensitive rules and offers recursive computation to reduce them. Three benchmark datasets were used for evaluation. The results show an improvement of 81% in execution time, 23% in utility, and 5% in accuracy.

]]>Symmetry doi: 10.3390/sym10110574

Authors: Zengxian Li Hui Gao Guiwu Wei

In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

]]>Symmetry doi: 10.3390/sym10110573

Authors: Xiaohong Zhang Rajab Ali Borzooei Young Bae Jun

The concept of quantum B-algebra was introduced by Rump and Yang, that is, unified algebraic semantics for various noncommutative fuzzy logics, quantum logics, and implication logics. In this paper, a new notion of q-filter in quantum B-algebra is proposed, and quotient structures are constructed by q-filters (in contrast, although the notion of filter in quantum B-algebra has been defined before this paper, but corresponding quotient structures cannot be constructed according to the usual methods). Moreover, a new, more general, implication algebra is proposed, which is called basic implication algebra and can be regarded as a unified frame of general fuzzy logics, including nonassociative fuzzy logics (in contrast, quantum B-algebra is not applied to nonassociative fuzzy logics). The filter theory of basic implication algebras is also established.

]]>Symmetry doi: 10.3390/sym10110572

Authors: Omid Akbarzadeh Noor Asmawati Mohd Zabidi Yasmin Abdul Wahab Nor Aliya Hamizi Zaira Zaman Chowdhury Zulkifli Merican Aljunid Merican Marlinda Ab Rahman Shamima Akhter Elisa Rasouli Mohd Rafie Johan

Pre-treating the multi-walled carbon nanotubes (CNTs) support by refluxing in 35 vol% nitric acid followed by heating at the temperature of 600 to 900 &deg;C resulted in the formation of defects on the CNTs. Increasing the temperature of the pre-treatment of the CNTs from 600 &deg;C to 900 &deg;C, enhanced the fraction of cobalt-oxide nanoparticles encapsulated in the channels of CNTs from 31% to 70%. The performance of Co/CNTs in Fischer-Tropsch synthesis (FTS) was evaluated in a fixed-bed micro-reactor at a temperature of 240 &deg;C and a pressure of 2.0 MPa. The highest CO conversion obtained over Co/CNTs.A.900 was 59% and it dropped by ~3% after 130 h of time-on-stream. However, maximum CO conversion using Co/CNTs.A.600 catalysts was 28% and it decreased rapidly by about 54% after 130 h of time-on-stream. These findings show that the combined acid and thermal pre-treatment of CNTs support at 900 &deg;C has improved the stability and activity of the Co/CNTs catalyst in FTS.

]]>Symmetry doi: 10.3390/sym10110571

Authors: Eligijus Sakalauskas Aleksejus Mihalkovich

This paper is a continuation of our previous publication of enhanced matrix power function (MPF) as a conjectured one-way function. We are considering a problem introduced in our previous paper and prove that tis problem is NP-Complete. The proof is based on the dual interpretation of well known multivariate quadratic (MQ) problem defined over the binary field as a system of MQ equations, and as a general satisfiability (GSAT) problem. Due to this interpretation the necessary constraints to MPF function for cryptographic protocols construction can be added to initial GSAT problem. Then it is proved that obtained GSAT problem is NP-Complete using Schaefer dichotomy theorem. Referencing to this result, GSAT problem by polynomial-time reduction is reduced to the sub-problem of enhanced MPF, hence the latter is NP-Complete as well.

]]>Symmetry doi: 10.3390/sym10110570

Authors: Xuhui Ye Gongping Wu Le Huang Fei Fan Yongxiang Zhang

Inspection images of power transmission line provide vision interaction for the operator and the environmental perception for the cable inspection robot (CIR). However, inspection images are always contaminated by severe outdoor working conditions such as uneven illumination, low contrast, and speckle noise. Therefore, this paper proposes a novel method based on Retinex and fuzzy enhancement to improve the image quality of the inspection images. A modified multi-scale Retinex (MSR) is proposed to compensate the uneven illumination by processing the low frequency components after wavelet decomposition. Besides, a fuzzy enhancement method is proposed to perfect the edge information and improve contrast by processing the high frequency components. A noise reduction procedure based on soft threshold is used to avoid the noise amplification. Experiments on the self-built standard test dataset show that the algorithm can improve the image quality by 3&ndash;4 times. Compared with several other methods, the experimental results demonstrate that the proposed method can obtain better enhancement performance with more homogeneous illumination and higher contrast. Further research will focus on improving the real-time performance and parameter adaptation of the algorithm.

]]>Symmetry doi: 10.3390/sym10110569

Authors: Mario L. Ruz Juan Garrido Francisco Vazquez Fernando Morilla

Engineering education and, particularly, control engineering, has shown growth in research and development activities during last years. Currently, proportional&ndash;integral (PI) and proportional&ndash;integral&ndash;derivative (PID) controllers are the most commonly used in industrial process applications. Nonetheless, it is reported that many of them are badly tuned. From an educational perspective, it is crucial for the student to understand the importance of tuning a control loop correctly. This paper presents an interactive tool focused on the study of PI controllers. The tool provides a set of tuning rules for both open-loop stable and unstable first order plus time delay processes. The different tuning rules can be compared interactively by the user, allowing a critical analysis of basic concepts about stability, robustness, and performance in PI control loops. In addition to educational purposes, the tool has been developed, taking into account practical considerations, such as simulation with a controller discrete implementation, process input saturations, and windup effect. We evaluated students&rsquo; achievement in the final examination in the Automatic Control course of the Electronics Engineering degree. Students showed significant improvement in their understanding of PI controller design. A survey and a practical case study were performed to evaluate the effectiveness of the proposed tool.

]]>Symmetry doi: 10.3390/sym10110568

Authors: Wassim M. Haddad

In this paper, we analyze the spatiotemporal mean field model developed by Liley et al. in order to advance our understanding of the wide effects of pharmacological agents and anesthetics. Specifically, we use the spatiotemporal mean field model for capturing the electrical activity in the neocortex to computationally study the emergence of &alpha; - and &gamma; -band rhythmic activity in the brain. We show that &alpha; oscillations in the solutions of the model appear globally across the neocortex, whereas &gamma; oscillations can emerge locally as a result of a bifurcation in the dynamics of the model. We solve the dynamic equations of the model using a finite element solver package and show that our results verify the predictions made by bifurcation analysis.

]]>Symmetry doi: 10.3390/sym10110567

Authors: Marco Enríquez Sara Cruz y Cruz

Using the Hubbard representation for S U ( 2 ) , we write the time-evolution operator of a two-level system in the disentangled form. This allows us to map the corresponding dynamical law into a set of nonlinear coupled equations. In order to find exact solutions, we use an inverse approach and find families of time-dependent Hamiltonians whose off-diagonal elements are connected with the Ermakov equation. A physical model with the so-obtained Hamiltonians is discussed in the context of the nuclear magnetic resonance phenomenon.

]]>Symmetry doi: 10.3390/sym10110566

Authors: Chao-Hong Tang Hong-Xu Li

By using Bochner transform, Stepanov almost periodic functions inherit some basic properties directly from almost periodic functions. Recently, this old work was extended to time scales. However, we show that Bochner transform is not valid on time scales. Then we present a revised version, called Bochner-like transform, for time scales, and prove that a function is Stepanov almost periodic if and only if its Bochner-like transform is almost periodic on time scales. Some basic properties including the composition theorem of Stepanov almost periodic functions are obtained by applying Bochner-like transform. Our results correct the recent results where Bochner transform is used on time scales. As an application, we give some results on dynamic equations with Stepanov almost periodic terms.

]]>Symmetry doi: 10.3390/sym10110565

Authors: Qinping Zhu Zhichun Mu

Occlusion over ear surfaces results in performance degradation of ear registration and recognition systems. In this paper, we propose an occlusion-resistant three-dimensional (3D) ear recognition system consisting of four primary components: (1) an ear detection component, (2) a local feature extraction and matching component, (3) a holistic matching component, and (4) a decision-level fusion algorithm. The ear detection component is implemented based on faster region-based convolutional neural networks. In the local feature extraction and matching component, a symmetric space-centered 3D shape descriptor based on the surface patch histogram of indexed shapes (SPHIS) is used to generate a set of keypoints and a feature vector for each keypoint. Then, a two-step noncooperative game theory (NGT)-based method is proposed. The proposed symmetric game-based method is effectively applied to determine a set of keypoints that satisfy the rigid constraints from initial keypoint correspondences. In the holistic matching component, a proposed variant of breed surface voxelization is used to calculate the holistic registration error. Finally, the decision-level fusion algorithm is applied to generate the final match scores. Evaluation results from experiments conducted show that the proposed method produces competitive results for partial occlusion on a dataset consisting of natural and random occlusion.

]]>Symmetry doi: 10.3390/sym10110564

Authors: Thanh Vo Trang Nguyen C. T. Le

Race recognition (RR), which has many applications such as in surveillance systems, image/video understanding, analysis, etc., is a difficult problem to solve completely. To contribute towards solving that problem, this article investigates using a deep learning model. An efficient Race Recognition Framework (RRF) is proposed that includes information collector (IC), face detection and preprocessing (FD&amp;P), and RR modules. For the RR module, this study proposes two independent models. The first model is RR using a deep convolutional neural network (CNN) (the RR-CNN model). The second model (the RR-VGG model) is a fine-tuning model for RR based on VGG, the famous trained model for object recognition. In order to examine the performance of our proposed framework, we perform an experiment on our dataset named VNFaces, composed specifically of images collected from Facebook pages of Vietnamese people, to compare the accuracy between RR-CNN and RR-VGG. The experimental results show that for the VNFaces dataset, the RR-VGG model with augmented input images yields the best accuracy at 88.87% while RR-CNN, an independent and lightweight model, yields 88.64% accuracy. The extension experiments conducted prove that our proposed models could be applied to other race dataset problems such as Japanese, Chinese, or Brazilian with over 90% accuracy; the fine-tuning RR-VGG model achieved the best accuracy and is recommended for most scenarios.

]]>Symmetry doi: 10.3390/sym10110562

Authors: Muhammad Aslam Nasrullah Khan Muhammad Zahir Khan

Existing variance control charts are designed under the assumptions that no uncertain, fuzzy and imprecise observations or parameters are in the population or the sample. Neutrosophic statistics, which is the extension of classical statistics, has been widely used when there is uncertainty in the data. In this paper, we will originally design S 2 control chart under the neutrosophic interval methods. The complete structure of the neutrosophic S 2 control chart will be given. The necessary measures of neutrosophic S 2 will be given. The neutrosophic coefficient of S 2 control chart will be determined through the neutrosophic algorithm. Some tables are given for practical use. The efficiency of the proposed control chart is shown over the S 2 control chart designed under the classical statistics in neutrosophic average run length (NARL). A real example is also added to illustrate the proposed control chart. From the comparison in the simulation study and case study, it is concluded that the proposed control chart performs better than the existing control chart under uncertainty.

]]>Symmetry doi: 10.3390/sym10110563

Authors: Chunxiang Zong Yuchao Tang Yeol Je Cho

The three-operator splitting algorithm is a new splitting algorithm for finding monotone inclusion problems of the sum of three maximally monotone operators, where one is cocoercive. As the resolvent operator is not available in a closed form in the original three-operator splitting algorithm, in this paper, we introduce an inexact three-operator splitting algorithm to solve this type of monotone inclusion problem. The theoretical convergence properties of the proposed iterative algorithm are studied in general Hilbert spaces under mild conditions on the iterative parameters. As a corollary, we obtain general convergence results of the inexact forward-backward splitting algorithm and the inexact Douglas-Rachford splitting algorithm, which extend the existing results in the literature.

]]>Symmetry doi: 10.3390/sym10110561

Authors: Jian-Zhen Luo Chun Shan Jun Cai Yan Liu

Fuzzing is regarded as the most promising method for protocol vulnerabilities discovering in network security of Internet of Things (IoT). However, one fatal drawback of existing fuzzing methods is that a huge number of test files are required to maintain a high test coverage. In this paper, a novel method based on protocol reverse engineering is proposed to reduce the amount of test files for fuzzing. The proposed method uses techniques in the field of protocol reverse engineering to identify message formats of IoT application-layer protocol and create test files by generating messages with error fields according to message formats. The protocol message treated as a sequence of bytes is assumed to obey a statistic process with change-points indicating the boundaries of message fields. Then, a multi-change-point detection procedure is introduced to identify change-points of byte sequences according to their statistic properties and divide them into segments according to their change-points. The message segments are further processed via a position-based occurrence probability test analysis to identify keyword fields, data fields and uncertain fields. Finally, a message generation procedure with mutation operation on message fields is applied to construct test files for fuzzing test. The results show that the proposed method can effectively find out the message fields and significantly reduce the amount of test files for fuzzing test.

]]>Symmetry doi: 10.3390/sym10110560

Authors: Badr Alqahtani Andreea Fulga Erdal Karapınar

In this paper, we analyze two discontinuous self-mappings that satisfy Sehgal-type inequalities in the setup of complete b-metric space. The main results of the paper cover and extend a few existing results in the corresponding literature. Furthermore, we give some illustrative examples to verify the effectiveness and strength of our derived results. Thereafter, as an application, we consider the obtained result to aggregate the existence and uniqueness of the solution for nonlinear Fredholm integral equations.

]]>Symmetry doi: 10.3390/sym10110559

Authors: Gamal G.L. Nashed

In this study, we derive, in the framework of mimetic theory, charged and non-charged black hole solutions for spherically symmetric as well as flat horizon spacetimes. The asymptotic behavior of those black holes behave as flat or (A)dS spacetimes and coincide with the solutions derived before in general relativity theory. Using the field equations of non-linear electrodynamics mimetic theory we derive new black hole solutions with monopole and quadrupole terms. The quadruple term of those black holes is related by a constant so that its vanishing makes the solutions coincide with the linear Maxwell black holes. We study the singularities of those solutions and show that they possess stronger singularity than the ones known in general relativity. Among many things, we study the horizons as well as the heat capacity to see if the black holes derived in this study have thermodynamical stability or not.

]]>Symmetry doi: 10.3390/sym10110558

Authors: Christian Corda

We show that, based on important reasons, differently from some recent claim in the literature, the YARK theory of gravity can reproduce neither the LIGO &ldquo;GW150914 signal&rdquo;, nor the other LIGO detections of gravitational waves (GWs).

]]>Symmetry doi: 10.3390/sym10110557

Authors: Jiaru Li Fangwei Zhang Qiang Li Jing Sun Janney Yee Shuhong Wang Shujun Xiao

The subject of this study is to explore the role of cardinality of hesitant fuzzy element (HFE) in distance measures on hesitant fuzzy sets (HFSs). Firstly, three parameters, i.e., credibility factor, conservative factor, and a risk factor are introduced, thereafter, a series of novel distance measures on HFSs are proposed using these three parameters. These newly proposed distance measures handle the relationship between the cardinal number and the element values of hesitant fuzzy set well, and are suitable to combine subjective and objective decision-making information. When using these functions, decision makers with different risk preferences are allowed to give different values for these three parameters. In particular, this study transfers the hesitance degree index to a credibility of the values in HFEs, which is consistent with people&rsquo;s intuition. Finally, the practicability of the newly proposed distance measures is verified by two examples.

]]>Symmetry doi: 10.3390/sym10110556

Authors: Faouzi Ben Rebah Wissem Mnif Saifeldin M. Siddeeg

Microorganisms such as bacteria, fungi, and microalgae have been used to produce bioflocculants with various structures. These polymers are active substances that are biodegradable, environmentally harmless, and have flocculation characteristics. Most of the developed microbial bioflocculants displayed significant flocculating activity (FA &gt; 70&ndash;90%) depending on the strain used and on the operating parameters. These biopolymers have been investigated and successfully used for wastewater depollution in the laboratory. In various cases, selected efficient microbial flocculants could reduce significantly suspended solids (SS), turbidity, chemical oxygen demand (COD), total nitrogen (Nt), dye, and heavy metals, with removal percentages exceeding 90% depending on the bioflocculating materials and on the wastewater characteristics. Moreover, bioflocculants showed acceptable results for sludge conditioning (accepted levels of dry solids, specific resistance to filtration, moisture, etc.) compared to chemicals. This paper explores various bioflocculants produced by numerous microbial strains. Their production procedures and flocculating performance will be included. Furthermore, their efficiency in the depollution of wastewater will be discussed.

]]>Symmetry doi: 10.3390/sym10110555

Authors: Umar Yusuf Batsari Poom Kumam Kanokwan Sitthithakerngkiet

In this paper, the existence and uniqueness of globally stable fixed points of asymptotically contractive mappings in complete b-metric spaces were studied. Also, we investigated the existence of fixed points under the setting of a continuous mapping. Furthermore, we introduce a contraction mapping that generalizes that of Banach, Kanan, and Chatterjea. Using our new introduced contraction mapping, we establish some results on the existence and uniqueness of fixed points. In obtaining some of our results, we assume that the space is associated with a partial order, and the b-metric function has the regularity property. Our results improve, and generalize some current results in the literature.

]]>Symmetry doi: 10.3390/sym10110554

Authors: Yong-An Jung Young-Hwan You

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is appealing for the provision of high spectral efficiency in digital terrestrial broadcast systems. To fully obtain its advantageous features, it is very important to remove the frequency mismatch between the transmitter and the receiver. In this paper, we present the performance analysis of joint estimation of carrier and sampling frequency offsets in the MIMO-OFDM-based advanced television systems committee (ATSC) 3.0 system. In the MIMO-OFDM ATSC system, the continual pilot (CP) is primarily utilized to perform frequency synchronization. To efficiently suppress an unwanted bias introduced by the presence of random-likely located CPs, an optimal pilot subset is selected to form the basis of least squares frequency-offset estimation. A closed-form mean squared error is derived in the context of MIMO-OFDM, considering the multipath fading channel. We show via computer simulations and numerical analysis that the proposed estimation method achieves higher estimation accuracy than the existing estimation method.

]]>Symmetry doi: 10.3390/sym10110553

Authors: Xinran Ning Yang Xu Guanfeng Wu Huimin Fu

Due to scale and complexity of first-order formulas, simplifications play a very important role in first-order theorem proving, in which removal of clauses and literals identified as redundant is a significant component. In this paper, four types of clauses with the local redundancy property were proposed, separately called a set-blocked clause (SBC), extended set-blocked clause (E-SBC), equality-set-blocked clause (ESBC) and extended equality-set-blocked clause (E-ESBC). The former two are redundant clauses in first-order formulas without equality while the latter two are redundant clauses in first-order formulas with equality. In addition, to prove the correctness of the four proposals, the redundancy of the four kinds of clauses were proved. It was guaranteed eliminating clauses with the four forms has no effect on the satisfiability or the unsatisfiability of original formulas. In the end, effectiveness and confluence properties of corresponding clause elimination methods were analyzed and compared.

]]>Symmetry doi: 10.3390/sym10110552

Authors: Zuoxun Wang Rongwei Guo

The hybrid synchronization problem of a class of chaotic systems is investigated in this paper. Firstly, the existence of hybrid synchronization problems in such systems is proved theoretically by a proposed necessary and sufficient condition. That is, the hybrid synchronization problem is equivalent to solve a group of nonlinear algebraic equations about &alpha; . It is interesting that one value of &alpha; indicates one type of synchronization. Secondly, all solutions for the hybrid synchronization problem are obtained by finding solutions of all the above equations about &alpha; . Thirdly, an universal control method is proposed to realize such hybrid synchronization problems. Finally, illustrative examples are provided to verify the validity and effectiveness of the obtained results.

]]>Symmetry doi: 10.3390/sym10110551

Authors: Marianna Jacyna Mariusz Izdebski Emilian Szczepański Paweł Gołda

The article investigates the problem of task assignment of vehicles for a production company. The presented problem is a complex decision-making issue which has not been analyzed in the literature before. Two stages must be passed through in order to solve the task assignment problem of the vehicles for the production company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that is needed to perform these tasks. The task in the analyzed problem is defined as transporting the cargo from the suppliers to the warehouses and from the warehouses to the production company. The number of the tasks depends on the type of the vehicle which carries out a given task. In order to solve the presented problem, the mathematical model has been developed, i.e., decision variables, constraints, and criterion functions. There are three types of decision variables occurring in the model, which means that this problem is quite complex. The first type of the decision variables determines the volume of the cargo which flows among the facilities on a given working day, the second type of the decision variables determines the use of a given type of the vehicle in the task, and the third type of the decision variables determines the number of the vehicles which perform the task. The criterion functions take the following form: the fuel consumption costs, the transition costs of the cargo via the warehouses, the purchase costs of the cargo, and the task completion time. In order to solve the task assignment problem of the vehicles, a genetic algorithm has been developed. The proposed method of task assignment solution is unique due to the coding method of individuals and related recombination procedures. The construction stages of this algorithm are presented. The algorithm has been verified by the use of the real input data. The developed model and method of its solution are unique in the application to the service of manufacturing enterprises. Due to the high efficiency and multi-aspect approach, it can be applied in enterprises of various industries as support for decision-makers in the optimization of resources.

]]>Symmetry doi: 10.3390/sym10110550

Authors: Jingkui Li Ruoying Wang He Tian Yanan Wang Dawei Qi

In order to improve the mechanical properties of the wood surface and explore the mechanical effect of wood veneer surface metallization, the 31-year-old Pinus sylvestris is taken as the research object and Cu is deposited on the wood surface by magnetron sputtering to achieve wood veneer metallization. Based on X-ray diffraction (XRD) and nanoindentation, a research on the gradual process of the structures and mechanical properties of wood veneer metallization was carried out. The results indicate that wood veneer metallization does not affect the crystallization zone of wood, there are still wood cellulose characteristic peaks and the crystalline structure of the wood cellulose is not damaged; the thickness of the copper thin film increases with the increase of the deposition time, the cellulose characteristic peak strength gradually decrease, and the relative crystallinity also decreases; the characteristic diffraction peaks of Cu (111), Cu (200), and Cu (220) appear near the diffraction angle 2&theta; which is equal to 43.3&deg;, 50.4&deg;, and 74.1&deg;, and the diffraction peak intensity increases with increase of deposition time, the copper film of the metal wood veneer crystallizes well; the load&ndash;displacement of wood veneer decreases significantly with the increase of deposition time, while the moduli of elasticity and hardness increase rapidly. The load&ndash;displacement of the samples which were coated for 15 min decreased by 80%, while the moduli of elasticity and hardness of these samples increased by 24.1 times and 17.3 times, respectively. From the results of Scanning Electron Microscope (SEM) measurement of the metallization of wood veneer, it can be seen that the uniform and continuous copper film can be formed on the wood veneer surface by using the magnetron sputtering method. This paper provides a basis for wood veneer surface metallization, which is of great significance for the functional improvement of wood, the expansion of wood application fields, and the enhancement of added value.

]]>Symmetry doi: 10.3390/sym10110549

Authors: Zilong Song Shiwei He Baifeng An

This paper investigated, for the first time, the game and coordination of a dual-channel, three-layered, green fresh produce supply chain, with regard to its economic, social, and environmental performance. Considering that the market demand is dual-channel priced and sensitive to the degree of greenness and the freshness-level, four game models, under different scenarios have been established. These included a centralized scenario, a decentralized scenario, and two contractual scenarios. The equilibrium solutions under the four scenarios were characterized. From the perspective of a sustainable development, the economic, social, and environmental performance of the supply chain was analyzed. To enhance the supply chain performance, two contract mechanisms were designed and the conditions for a multi-win outcome were obtained. Accordingly, many propositions and management implications were provided. The results showed that, (1) compared to the centralized supply chain case, the performance of the decentralized supply chain case is inferior; (2) in addition to increasing the concentration of the supply chain decisions, the two contracts proposed can effectively coordinate the green supply chain and improve its sustainable performance; and (3) the performance of the supply chain is positively driven by the consumers&rsquo; sensitivity to greenness degree and the freshness level of fresh produce. This paper fills a research gap and helps the participants of the channel recognize the operational decision principle of a complex green supply chain, in order to achieve a higher and a long-term sustainable-development performance.

]]>Symmetry doi: 10.3390/sym10110548

Authors: Chia-Nan Wang Chih-Chiang Su Van Thanh Nguyen

The demands for energy in general and electrical power in particular in the process of industrialization&ndash;modernization in Vietnam are increasing. Although other renewable energy sources such as wind and solar power have been prioritized, they cannot compensate for the shortages of electricity in Vietnam; moreover, traditional energy sources in Vietnam are not endless and will soon reach exhaustion. Nowadays, the government has chosen a solution to maximize domestic energy resources, i.e., develop renewable energy combined with importing coal and gas in appropriate proportions with the construction of nuclear power plants (NPP), which may be the optimal solution to ensure energy security, environmental protection, and sustainable development. However, site selection for construction of a nuclear power plant is one of the most difficult decisions that management faces. Thus, the authors proposed multicriteria decision-making (MCDM), including a fuzzy analytic network process (FANP) and technique for order preference by similarity of an ideal solution (TOPSIS) for NPP location selection in Vietnam. In the first stages of this research, the weight of all criteria and subcriteria will be calculated by an ANP model using fuzzy logic. A TOPSIS model is proposed for ranking all potential locations in the final stage. The results reveal that Binh Thuan is the best place for building an NPP in Vietnam. The contributions of this research include a fuzzy multicriteria decision-making (F-MCDM) approach for NPP site selection in Vietnam. This research also utilizes the evolution of a new approach that is flexible and practical for the decision-maker and provides useful guidelines for NPP site selection in countries around the world.

]]>Symmetry doi: 10.3390/sym10110547

Authors: Zahra Asebriy Said Raghay Omar Bencharef

Mathematical learning from digital libraries and the web is a challenging problem for people with visual impairments and blindness. In this paper, we focus on developing the mathematical learning skills of braille users with a new assistive technology developed to retrieve semantically mathematical information from the web. This kind of research is still in the study phase. This paper presents an overview of assistive technologies for braille users followed by a description of the proposed system, which works in four phases. In the first phase, we translate a query math formula in braille into MathML code, and then we extract the structural and semantic meaning from the MathML expressions using multilevel presentation. In the classification phase, we choose a multilevel similarity measure based on K-Nearest Neighbors to evaluate the relevance between expressions. Finally, the query result is converted to braille math expressions. Experiments based on our database show that the new system provides more efficient results in responding to user queries.

]]>Symmetry doi: 10.3390/sym10110546

Authors: Luca Visinelli

Understanding the nature of the Dark Matter (DM) is one of the current challenges in modern astrophysics and cosmology. Knowing the properties of the DM particle would shed light on physics beyond the Standard Model and even provide us with details of the early Universe. In fact, the detection of such a relic would bring us information from the pre-Big Bang Nucleosynthesis (BBN) period, an epoch from which we have no direct data, and could even hint at inflation physics. In this work, we assume that the expansion rate of the Universe after inflation is governed by the kinetic energy of a scalar field ϕ , in the so-called &ldquo;kination&rdquo; model. Adding to previous work on the subject, we assume that the ϕ field decays into both radiation and DM particles, which we take to be Weakly Interacting Massive Particles (WIMPs). The present abundance of WIMPs is then fixed during the kination period through either a thermal &ldquo;freeze-out&rdquo; or &ldquo;freeze-in&rdquo; mechanism, or through a non-thermal process governed by the decay of ϕ . We explore the parameter space of this theory with the requirement that the present WIMP abundance provides the correct relic budget. Requiring that BBN occurs during the standard cosmological scenario sets a limit on the temperature at which the kination period ends. Using this limit and assuming the WIMP has a mass m &chi; = 100 GeV, we obtain that the thermally averaged WIMP annihilation cross section has to satisfy the constraints 4 &times; 10 &minus; 16 GeV &minus; 2 ≲ &lang; &sigma; v &rang; ≲ 2 &times; 10 &minus; 5 GeV &minus; 2 in order for having at least one of the production mechanism to yield the observed amount of DM. This result shows how the properties of the WIMP particle, if ever measured, can yield information on the pre-BBN content of the Universe.

]]>Symmetry doi: 10.3390/sym10110545

Authors: Gang Hu Cuicui Bo Junli Wu Guo Wei Fei Hou

The modeling of free-form engineering complex curves is an important subject in product modeling, graphics, and computer aided design/computer aided manufacturing (CAD/CAM). In this paper, we propose a novel method to construct free-form complex curves using shape-adjustable generalized B&eacute;zier (or SG-B&eacute;zier, for short) curves with constraints of geometric continuities. In order to overcome the difficulty that most of the composite curves in engineering cannot often be constructed by using only a single curve, we propose the necessary and sufficient conditions for G1 and G2 continuity between two adjacent SG-B&eacute;zier curves. Furthermore, the detailed steps of smooth continuity for two SG-B&eacute;zier curves, and the influence rules of shape parameters on the composite curves, are studied. We also give some important applications of SG-B&eacute;zier curves. The modeling examples show that our methods in this paper are very effective, can easily be performed, and can provide an alternative powerful strategy for the design of complex curves.

]]>Symmetry doi: 10.3390/sym10110544

Authors: Yong-An Jung Young-Hwan You

The HomePlug Green PHY (HomePlug GP) specification provides an attractive solution to enable smart grid power line communication (PLC) applications by using robust orthogonal frequency division multiplexing (ROBO) mode. This paper proposes a computationally efficient sampling frequency offset (SFO) estimation technique in the HomePlug GP system without relying on pilot symbols. For this purpose, the proposed estimation scheme utilizes the redundant information contained within the repeat coding in the HomePlug GP ROBO mode, thus eliminating the need of dedicated pilots. Computer simulations are conducted to assess the performance of the proposed SFO estimation scheme and to compare it with the conventional decision-directed (DD) estimation schemes. Simulations indicate that the repeat coded ROBO signals are effectively used for the proposed estimation scheme, which provides an affordable estimation accuracy while reducing the complexity compared to the conventional DD estimation schemes.

]]>Symmetry doi: 10.3390/sym10110543

Authors: Jianfeng Lu Weiling Cheng Shanqing Zhang Li Li Zaorang Yang Chin-Chen Chang

Recently, more and more research has focused on the beautification technology of QR (Quick Response) codes. In this paper, a novel algorithm based on the XOR (exclusive OR) mechanism of hybrid basis vector matrices and a background image synthetic strategy is proposed. The hybrid basis vector matrices include the reverse basis vector matrix (RBVM) and positive basis vector matrix (PBVM). Firstly, the RBVM and PBVM are obtained by the Gauss&ndash;Jordan elimination method, according to the characteristics of the RS code. Secondly, the modification of the parity area of the QR code can be applied with the XOR operation of the RBVM, and the XOR operation of the PBVM is used to change the data area of the QR code. So, the QR code can be modified to be very close to the background image without impacting the error-correction ability. Finally, in order to further decrease the difference between the QR code and the background image, a new synthesis strategy is adopted in order to obtain a better aesthetic effect. The experimental results show that it obtains a better visual effect without the sacrificing recognition rate.

]]>Symmetry doi: 10.3390/sym10110542

Authors: Yoshihiro Ueda

In this article, we introduce a new approach to obtain the property of the dissipative structure for a system of differential equations. If the system has a viscosity or relaxation term which possesses symmetric property, Shizuta and Kawashima in 1985 introduced the suitable stability condition called in this article Classical Stability Condition for the corresponding eigenvalue problem of the system, and derived the detailed relation between the coefficient matrices of the system and the eigenvalues. However, there are some complicated physical models which possess a non-symmetric viscosity or relaxation term and we cannot apply Classical Stability Condition to these models. Under this situation, our purpose in this article is to extend Classical Stability Condition for complicated models and to make the relation between the coefficient matrices and the corresponding eigenvalues clear. Furthermore, we shall explain the new dissipative structure through the several concrete examples.

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