Symmetry

18 pages, 1127 KiB

Open AccessFeature PaperArticle

The Fuzzified Natural Transformation between Categorial Functors and Its Selected Categorial Aspects

by Krystian Jobczyk

Symmetry 2020, 12(9), 1578; https://doi.org/10.3390/sym12091578 - 22 Sep 2020

Cited by 1 | Viewed by 2164

The natural transformation constitutes one of the most important entity of category theory and it introduces a piece of sophisticated dynamism to the categorial structures. Each natural transformation forms a unique mapping between the so-called functors, which live between categories. In the most [...] Read more.

The natural transformation constitutes one of the most important entity of category theory and it introduces a piece of sophisticated dynamism to the categorial structures. Each natural transformation forms a unique mapping between the so-called functors, which live between categories. In the most simple contexts, natural transformations may be recognized by commutativity of diagrams, which determine them. In fact, the natural transformation does not form any single mapping, but a pair of two components, which–together with the commutativity condition itself–introduces a kind of a symmetry to the functor diagrams. Meanwhile, the general form of the natural transformation may be predicted by means the so-called Yoneda’s lemma in each scenario based on two-valued logic. Meanwhile, the situation may be radically different if we deal with multi-diagrams (instead of the single ones) and if we exchange the two-valued scenario for a multi-valued or fuzzy one. Due to this background–the paper introduces a new concept of multi-fuzzy natural transformation. Its definition exploits the notion of fuzzy natural transformation. Moreover, a multi-fuzzy Yoneda’s lemma is formulated and proved. Finally, some references of these constructions to coding theory are elucidated in last parts of the paper. Full article

(This article belongs to the Special Issue Fuzzy Mathematics Applied to Science, Engineering and Sustainability Issues)

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9 pages, 1607 KiB

Open AccessArticle

Teaching Theory of Probability and Statistics during the Covid-19 Emergency

by Andrea Jahodova Berkova and Radek Nemec

Symmetry 2020, 12(9), 1577; https://doi.org/10.3390/sym12091577 - 22 Sep 2020

Cited by 7 | Viewed by 4469

Abstract

The state of emergency caused by the covid-19 pandemic has shown that teaching at this time is not easy. Teachers have to make more use of distance education and students have to adapt to that. Classic face-to-face study is not possible but asymmetric [...] Read more.

The state of emergency caused by the covid-19 pandemic has shown that teaching at this time is not easy. Teachers have to make more use of distance education and students have to adapt to that. Classic face-to-face study is not possible but asymmetric communication between the teacher and his students may be replaced by greater student independence and greater student effort. Within the subject theory of probability and statistics, a questionnaire was created to find how students manage distance education. It has been found out that they use the prepared tutorial videos and online assignments (in WeBWork platform) the most. They expressed that distance education prepared by the teacher can replace face-to-face study, but this form of learning is much more demanding and therefore they prefer classic face-to-face study. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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25 pages, 396 KiB

Open AccessArticle

Mitigation of Privacy Threats due to Encrypted Traffic Analysis through a Policy-Based Framework and MUD Profiles

by Gianmarco Baldini, José L. Hernandez-Ramos, Slawomir Nowak, Ricardo Neisse and Mateusz Nowak

Symmetry 2020, 12(9), 1576; https://doi.org/10.3390/sym12091576 - 22 Sep 2020

Cited by 6 | Viewed by 2951

Abstract

It has been proven in research literature that the analysis of encrypted traffic with statistical analysis and machine learning can reveal the type of activities performed by a user accessing the network, thus leading to privacy risks. In particular, different types of traffic [...] Read more.

It has been proven in research literature that the analysis of encrypted traffic with statistical analysis and machine learning can reveal the type of activities performed by a user accessing the network, thus leading to privacy risks. In particular, different types of traffic (e.g., skype, web access) can be identified by extracting time based features and using them in a classifier. Such privacy attacks are asymmetric because a limited amount of resources (e.g., machine learning algorithms) can extract information from encrypted traffic generated by cryptographic systems implemented with a significant amount of resources. To mitigate privacy risks, studies in research literature have proposed a number of techniques, but in most cases only a single technique is applied, which can lead to limited effectiveness. This paper proposes a mitigation approach for privacy risks related to the analysis of encrypted traffic which is based on the integration of three main components: (1) A machine learning component which proactively analyzes the encrypted traffic in the network to identify potential privacy threats and evaluate the effectiveness of various mitigation techniques (e.g., obfuscation), (2) a policy based component where policies are used to enforce privacy mitigation solutions in the network and (3) a network node profile component based on the Manufacturer Usage Description (MUD) standard to enable changes in the network nodes in the cases where the first two components are not effective in mitigating the privacy risks. This paper describes the different components and how they interact in a potential deployment scenario. The approach is evaluated on the public dataset ISCXVPN2016 and the results show that the privacy threat can be mitigated significantly by removing completely the identification of specific types of traffic or by decreasing the probability of their identification as in the case of VOIP by 50%, Chat by 40% and Browsing by 33%, thus reducing significantly the privacy risk. Full article

(This article belongs to the Special Issue Special issue on Symmetry and Asymmetry in IoT and CPS Security and Privacy)

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16 pages, 5372 KiB

Open AccessArticle

Adaptive Mechanism Model for the Prevention of SLA Violation in the Context of COPD Patient Monitoring

by Konan-Marcelin Kouamé, Hamid Mcheick and Hicham Ajami

Symmetry 2020, 12(9), 1575; https://doi.org/10.3390/sym12091575 - 22 Sep 2020

Cited by 4 | Viewed by 2353

Abstract

In this paper, we introduce a new kind of Service Level Agreement(SLA) Template to better control dynamically quality of medical monitoring platform service. Our approach is based on Health care system and Health Information Technology (HIT) research area, specifically the field of telemonitoring [...] Read more.

In this paper, we introduce a new kind of Service Level Agreement(SLA) Template to better control dynamically quality of medical monitoring platform service. Our approach is based on Health care system and Health Information Technology (HIT) research area, specifically the field of telemonitoring system for patients who suffer from chronic obstructive pulmonary disease (COPD). According to WHO statistics, COPD is the third leading cause of death worldwide. To this end, several solutions or platforms exist today to monitor COPD. Most of these platforms manage large volume of patient data. This can bring about quality and lost data problems. To address these issues, control mechanisms must be proposed and designed to improve the quality of service (QoS) on these platforms. A platform with continuously monitored QoS can save patients’ lives and reduce data quality risk. In this article, we propose an ontology that uses SLAs data from COPD monitoring platforms with dynamic data from a patient context. We dynamically calculate the number of patient data incidents and the number of service request incidents from two dynamic contexts: SLA and the patient context. If the number of incidents is higher than what is expected in the SLA, then alerts are sent to the interface parties in real time. Finally, the contribution of this article is the proposed virtual SLA template to better control SLA violation and improve quality of medical monitoring platforms services. Full article

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13 pages, 448 KiB

Open AccessArticle

Nematic and Smectic Phases: Dynamics and Phase Transition

by Aurélien Bailly-Reyre and Hung T. Diep

Symmetry 2020, 12(9), 1574; https://doi.org/10.3390/sym12091574 - 22 Sep 2020

Cited by 3 | Viewed by 4724

Abstract

We study in this paper the dynamics of molecules leading to the formation of nematic and smectic phases using a mobile 6-state Potts spin model with Monte Carlo simulation. Each Potts state represents a molecular orientation. We show that, with the choice of [...] Read more.

We study in this paper the dynamics of molecules leading to the formation of nematic and smectic phases using a mobile 6-state Potts spin model with Monte Carlo simulation. Each Potts state represents a molecular orientation. We show that, with the choice of an appropriate microscopic Hamiltonian describing the interaction between individual molecules modeled by 6-state Potts spins, we obtain the structure of the smectic phase by cooling the molecules from the isotropic phase to low temperatures: molecules are ordered in independent equidistant layers. The isotropic-smectic phase transition is found to have a first-order character. The nematic phase is also obtained with the choice of another microscopic Hamiltonian. The isotropic-nematic phase transition is a second-order one. The real-time dynamics of the molecules leading to the liquid-crystal ordering in each case is shown by a video. Full article

(This article belongs to the Special Issue Symmetry and Symmetry Breaking: Phase Transitions and Critical Phenomena)

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43 pages, 1117 KiB

Open AccessArticle

Antisymmetric Tensor Fields in Modified Gravity: A Summary

by Tanmoy Paul

Symmetry 2020, 12(9), 1573; https://doi.org/10.3390/sym12091573 - 22 Sep 2020

Cited by 9 | Viewed by 2554

Abstract

We provide various aspects of second rank antisymmetric Kalb–Ramond (KR) field in modified theories of gravity. The KR field energy density is found to decrease with the expansion of our universe at a faster rate in comparison to radiation and matter components. Thus [...] Read more.

We provide various aspects of second rank antisymmetric Kalb–Ramond (KR) field in modified theories of gravity. The KR field energy density is found to decrease with the expansion of our universe at a faster rate in comparison to radiation and matter components. Thus as the universe evolves and cools down, the contribution of the KR field on the evolutionary process reduces significantly, and at present it almost does not affect the universe evolution. However the KR field has a significant contribution during early universe; in particular, it affects the beginning of inflation as well as increases the amount of primordial gravitational radiation and hence enlarges the value of tensor-to-scalar ratio in respect to the case when the KR field is absent. In regard to the KR field couplings, it turns out that in four dimensional higher curvature inflationary model the couplings of the KR field to other matter fields is given by

1 / M_{P l}

(where

M_{P l}

is known as the “reduced Planck mass” defined by

M_{P l} = \frac{1}{\sqrt{8 π G}}

with G is the “Newton’s constant”) i.e., same as the usual gravity–matter coupling; however in the context of higher dimensional higher curvature model the KR couplings get an additional suppression over

1 / M_{P l}

. Thus in comparison to the four dimensional model, the higher curvature braneworld scenario gives a better explanation of why the present universe carries practically no footprint of the Kalb–Ramond field. The higher curvature term in the higher dimensional gravitational action acts as a suitable stabilizing agent in the dynamical stabilization mechanism of the extra dimensional modulus field from the perspective of effective on-brane theory. Based on the evolution of KR field, one intriguing question can be—“sitting in present day universe, how do we confirm the existence of the Kalb–Ramond field which has considerably low energy density (with respect to the other components) in our present universe but has a significant impact during early universe?” We try to answer this question by the phenomena “cosmological quantum entanglement” which indeed carries the information of early universe. Finally, we briefly discuss some future perspectives of Kalb–Ramond cosmology at the end of the paper. Full article

(This article belongs to the Special Issue Symmetry: Feature Papers 2020)

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21 pages, 8730 KiB

Open AccessArticle

Parameterized Design and Dynamic Analysis of a Reusable Launch Vehicle Landing System with Semi-Active Control

by Chen Wang, Jinbao Chen, Shan Jia and Heng Chen

Symmetry 2020, 12(9), 1572; https://doi.org/10.3390/sym12091572 - 22 Sep 2020

Cited by 5 | Viewed by 6246

Abstract

Reusable launch vehicles (RLVs) are a solution for effective and economic transportation in future aerospace exploration. However, RLVs are limited to being used under simple landing conditions (small landing velocity and angle) due to their poor adaptability and the high rocket acceleration of [...] Read more.

Reusable launch vehicles (RLVs) are a solution for effective and economic transportation in future aerospace exploration. However, RLVs are limited to being used under simple landing conditions (small landing velocity and angle) due to their poor adaptability and the high rocket acceleration of current landing systems. In this paper, an adaptive RLV landing system with semi-active control is proposed. The proposed landing system can adjust the damping forces of primary strut dampers through semi-actively controlled currents in accordance with practical landing conditions. A landing dynamic model of the proposed landing system is built. According to the dynamic model, an light and effective RLV landing system is parametrically designed based on the response surface methodology. Dynamic simulations validate the proposed landing system under landing conditions including the highest rocket acceleration and the greatest damper compressions. The simulation results show that the proposed landing system with semi-active control has better landing performance than current landing systems that use passive liquid or liquid–honeycomb dampers. Additionally, the flexibility and friction of the structure are discussed in the simulations. Compared to rigid models, flexible models decrease rocket acceleration by 51% and 54% at the touch down moments under these two landing conditions, respectively. The friction increases rocket acceleration by less than 1%. However, both flexibility and friction have little influence on the distance between the rocket and ground, or the compression strokes of the dampers. Full article

(This article belongs to the Special Issue Multibody Systems with Flexible Elements)

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11 pages, 898 KiB

Open AccessArticle

Dynamic Response of the Newton Voigt–Kelvin Modelled Linear Viscoelastic Systems at Harmonic Actions

by Cornelia Dobrescu

Symmetry 2020, 12(9), 1571; https://doi.org/10.3390/sym12091571 - 22 Sep 2020

Cited by 6 | Viewed by 1769

Abstract

The variety of viscoelastic systems and structures, for the most part, is studied analytically, with significant results. As a result of analytical, numerical and experimental research, which was conducted on a larger variety of linear viscoelastic systems and structures. We analyzed the dynamic [...] Read more.

The variety of viscoelastic systems and structures, for the most part, is studied analytically, with significant results. As a result of analytical, numerical and experimental research, which was conducted on a larger variety of linear viscoelastic systems and structures. We analyzed the dynamic behavior for the viscoelastic composite materials, anti-vibration viscous-elastic systems consisting of discrete physical devices, road structures consisting of natural soil structures with mineral aggregates and asphalt mixes, and mixed mechanic systems of insulation of the industrial vibrations consisting of elastic and viscous devices. In this context, the compound rheological model can be schematized as being

V - (E | V)

type of the Newton Voigt–Kelvin model with inertial excited mass, applicable to linear viscoelastic materials. Full article

(This article belongs to the Special Issue Symmetry in Dynamic Systems)

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19 pages, 9454 KiB

Open AccessArticle

Enhanced Hand-Oriented Activity Recognition Based on Smartwatch Sensor Data Using LSTMs

by Sakorn Mekruksavanich, Anuchit Jitpattanakul, Phichai Youplao and Preecha Yupapin

Symmetry 2020, 12(9), 1570; https://doi.org/10.3390/sym12091570 - 22 Sep 2020

Cited by 61 | Viewed by 4578

Abstract

The creation of the Internet of Things (IoT), along with the latest developments in wearable technology, has provided new opportunities in human activity recognition (HAR). The modern smartwatch offers the potential for data from sensors to be relayed to novel IoT platforms, which [...] Read more.

The creation of the Internet of Things (IoT), along with the latest developments in wearable technology, has provided new opportunities in human activity recognition (HAR). The modern smartwatch offers the potential for data from sensors to be relayed to novel IoT platforms, which allow the constant tracking and monitoring of human movement and behavior. Recently, traditional activity recognition techniques have done research in advance by choosing machine learning methods such as artificial neural network, decision tree, support vector machine, and naive Bayes. Nonetheless, these conventional machine learning techniques depend inevitably on heuristically handcrafted feature extraction, in which human domain knowledge is normally limited. This work proposes a hybrid deep learning model called CNN-LSTM that employed Long Short-Term Memory (LSTM) networks for activity recognition with the Convolution Neural Network (CNN). The study makes use of HAR involving smartwatches to categorize hand movements. Using the study based on the Wireless Sensor Data Mining (WISDM) public benchmark dataset, the recognition abilities of the deep learning model can be accessed. The accuracy, precision, recall, and F-measure statistics are employed using the evaluation metrics to assess the recognition abilities of LSTM models proposed. The findings indicate that this hybrid deep learning model offers better performance than its rivals, where the achievement of 96.2% accuracy, while the f-measure is 96.3%, is obtained. The results show that the proposed CNN-LSTM can support an improvement of the performance of activity recognition. Full article

(This article belongs to the Section Computer)

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Graphical abstract

12 pages, 691 KiB

Open AccessArticle

Prospective Teachers’ Development of Meta-Cognitive Functions in Solving Mathematical-Based Programming Problems with Scratch

by Juhaina Awawdeh Shahbari, Wajeeh Daher, Nimer Baya’a and Otman Jaber

Symmetry 2020, 12(9), 1569; https://doi.org/10.3390/sym12091569 - 22 Sep 2020

Cited by 9 | Viewed by 2570

Abstract

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study [...] Read more.

Transformations, including symmetry and rotations, are important in solving mathematical problems. Meta-cognitive functions are considered critical in solving mathematical problems. In the current study, we examined prospective teachers’ use of meta-cognitive functions while solving mathematical-based programming problems in the Scratch environment. The study was conducted among 18 prospective teachers, who engaged in a sequence of mathematical problems that utilize Scratch. The data sources included video recordings and solution reports while they performed mathematical problems. The findings indicated that the participants developed their meta-cognitive functions as problem solvers related to both mathematics and programming aspects. The findings also indicated that the participants developed regulation meta-cognitive functions more than awareness and evaluation ones in mathematical and programming aspects. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Economics, Biomedicine and Engineering)

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17 pages, 3194 KiB

Open AccessArticle

Simulation Methodology-Based Context-Aware Architecture Design for Behavior Monitoring of Systems

by Tae Ho Cho

Symmetry 2020, 12(9), 1568; https://doi.org/10.3390/sym12091568 - 22 Sep 2020

Cited by 5 | Viewed by 2116

Abstract

Generally, simulation models are constructed to replicate and predict the behavior of real systems that currently exist or are expected to exist in the future. Once a simulation model is implemented, the model can be connected to a real system for which the [...] Read more.

Generally, simulation models are constructed to replicate and predict the behavior of real systems that currently exist or are expected to exist in the future. Once a simulation model is implemented, the model can be connected to a real system for which the model has been built through sensors or networks so that important activities in the real system can be monitored indirectly through the model. This article proposes a modeling formalism BM-DEVS (Behavior Monitor-DEVS) that defines simulation models capable of monitoring the desired behavior patterns within the models so that the target system’s behavior can be monitored indirectly. In BM-DEVS, an extension of classic Discrete Event System Specification (DEVS), the behavior to be monitored is expressed as a set of temporal logic (TL) production rules within a multi-component model that consists of multiple component models to be monitored. An inference engine module for reasoning with the TL rules is designed based on the abstract simulator that carries out instructions in the BM-DEVS models to perform the simulation process. The major application of BM-DEVS is in the design and implementation of the context-aware architecture needed for various intelligent systems as a core constituent. Essentially all systems where some form of behavior monitoring is required are candidate applications of BM-DEVS. This research is motivated by the view that there exists symmetry between the real-world and the cyber world, in that the problems in both environments should be expressed with the same basic constituents of time and space; this naturally leads to adopting spatiotemporal variables composed of simulation models and developing a problem solver that exploits these variables. Full article

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13 pages, 8185 KiB

Open AccessArticle

Collision Free Smooth Path for Mobile Robots in Cluttered Environment Using an Economical Clamped Cubic B-Spline

by Iram Noreen

Symmetry 2020, 12(9), 1567; https://doi.org/10.3390/sym12091567 - 22 Sep 2020

Cited by 19 | Viewed by 3114

Abstract

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such [...] Read more.

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates

C^{2}

continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage. Full article

(This article belongs to the Section Computer)

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20 pages, 1546 KiB

Open AccessFeature PaperArticle

Toward Improving the Prediction Accuracy of Product Recommendation System Using Extreme Gradient Boosting and Encoding Approaches

by Zeinab Shahbazi, Debapriya Hazra, Sejoon Park and Yung Cheol Byun

Symmetry 2020, 12(9), 1566; https://doi.org/10.3390/sym12091566 - 22 Sep 2020

Cited by 32 | Viewed by 5780

Abstract

With the spread of COVID-19, the “untact” culture in South Korea is expanding and customers are increasingly seeking for online services. A recommendation system serves as a decision-making indicator that helps users by suggesting items to be purchased in the future by exploring [...] Read more.

With the spread of COVID-19, the “untact” culture in South Korea is expanding and customers are increasingly seeking for online services. A recommendation system serves as a decision-making indicator that helps users by suggesting items to be purchased in the future by exploring the symmetry between multiple user activity characteristics. A plethora of approaches are employed by the scientific community to design recommendation systems, including collaborative filtering, stereotyping, and content-based filtering, etc. The current paradigm of recommendation systems favors collaborative filtering due to its significant potential to closely capture the interest of a user as compared to other approaches. The collaborative filtering harnesses features like user-profile details, visited pages, and click information to determine the interest of a user, thereby recommending the items that are related to the user’s interest. The existing collaborative filtering approaches exploit implicit and explicit features and report either good classification or prediction outcome. These systems fail to exhibit good results for both measures at the same time. We believe that avoiding the recommendation of those items that have already been purchased could contribute to overcoming the said issue. In this study, we present a collaborative filtering-based algorithm to tackle big data of user with symmetric purchasing order and repetitive purchased products. The proposed algorithm relies on combining extreme gradient boosting machine learning architecture with word2vec mechanism to explore the purchased products based on the click patterns of users. Our algorithm improves the accuracy of predicting the relevant products to be recommended to the customers that are likely to be bought. The results are evaluated on the dataset that contains click-based features of users from an online shopping mall in Jeju Island, South Korea. We have evaluated Mean Absolute Error, Mean Square Error, and Root Mean Square Error for our proposed methodology and also other machine learning algorithms. Our proposed model generated the least error rate and enhanced the prediction accuracy of the recommendation system compared to other traditional approaches. Full article

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13 pages, 3526 KiB

Open AccessArticle

Wavelet Feature Outdoor Fingerprint Localization Based on ResNet and Deep Convolution GAN

by Yingke Lei, Da Li, Haichuan Zhang and Xin Li

Symmetry 2020, 12(9), 1565; https://doi.org/10.3390/sym12091565 - 22 Sep 2020

Cited by 6 | Viewed by 2126

Abstract

Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over the past decade. Among the associated techniques, wireless fingerprint positioning has garnered much interest due to its compatibility with existing hardware. At present, with the widespread deployment [...] Read more.

Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over the past decade. Among the associated techniques, wireless fingerprint positioning has garnered much interest due to its compatibility with existing hardware. At present, with the widespread deployment of long-term evolution (LTE) networks and the uniqueness of wireless information fingerprints, fingerprint positioning based on LTE networks is the mainstream method for outdoor positioning. However, in order to improve its accuracy, this method needs to collect enough data at a large number of reference points, which is a labor-intensive task. In this paper, experimental data are collected at different reference points and then converted into wavelet feature maps. Then, a Deep Convolutional Generative Adversarial Network (DCGAN) is leveraged to generate a symmetric fingerprint database. Localization is then carried out by the proposed Deep Residual Network (Resnet), which is capable of learning reliable features from a fingerprint image database. To further increase the robustness of the positioning system, a variety of data enhancement methods are used. Finally, we experimentally demonstrate that the generated symmetric fingerprint database and proposed Resnet reduce the manpower required for fingerprint database collection and improve the accuracy of the outdoor positioning system. Full article

(This article belongs to the Section Computer)

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14 pages, 280 KiB

Open AccessArticle

Cross-Docking Center Location Selection Based on Interval Multi-Granularity Multicriteria Group Decision-Making

by Xuchen Deng and Shaojian Qu

Symmetry 2020, 12(9), 1564; https://doi.org/10.3390/sym12091564 - 22 Sep 2020

Cited by 4 | Viewed by 1859

Abstract

Cross-docking is a new logistics model. The location planning of the crossover center is one of the important issues in logistics management. The location of the cross-docking center is not only a technical issue, but also a management issue. This is a decision [...] Read more.

Cross-docking is a new logistics model. The location planning of the crossover center is one of the important issues in logistics management. The location of the cross-docking center is not only a technical issue, but also a management issue. This is a decision made by senior leaders after considering various factors. Therefore, considering the decision-making method, a multicriteria group decision-making method based on an interval multi-granularity language model is proposed. It is suitable for non-static frameworks where the decision-making environment changes at any time during the process. Due to the uncertainty of the location information of the cross-docking center, experts can use their favorite language tag set to provide preferences, so a multi-granular interval fuzzy language model is used to enable experts to reliably provide preference values. At the same time, taking into account the formula threshold for decision-making, after a limited round of discussions, decision-making experts, site selection criteria, and site alternatives can be changed arbitrarily so that when the final opinion is reached, the consensus of experts reaches this threshold. Finally, through the numerical calculation of the site selection center, it is found that the experts will reach a higher level of consensus when joining the experts who change their status. The validity of the method is verified, and the feasibility and applicability of the proposed method are shown. Full article

(This article belongs to the Section Mathematics)

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14 pages, 341 KiB

Open AccessArticle

Automatic Repair of Semantic Defects Using Restraint Mechanisms

by Yukun Dong, Li Zhang, Shanchen Pang, Wenjing Yin, Mengying Wu, Meng Wu and Haojie Li

Symmetry 2020, 12(9), 1563; https://doi.org/10.3390/sym12091563 - 22 Sep 2020

Cited by 2 | Viewed by 2205

Abstract

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair [...] Read more.

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired. Full article

(This article belongs to the Special Issue Special issue on Symmetry and Asymmetry in IoT and CPS Security and Privacy)

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19 pages, 2960 KiB

Open AccessArticle

Graph Learning-Based Ontology Sparse Vector Computing

by Jianzhang Wu, Arun Kumar Sangaiah and Wei Gao

Symmetry 2020, 12(9), 1562; https://doi.org/10.3390/sym12091562 - 21 Sep 2020

Cited by 2 | Viewed by 2363

Abstract

The ontology sparse vector learning algorithm is essentially a dimensionality reduction trick, i.e., the key components in the p-dimensional vector are taken out, and the remaining components are set to zero, so as to obtain the key information in a certain ontology [...] Read more.

The ontology sparse vector learning algorithm is essentially a dimensionality reduction trick, i.e., the key components in the p-dimensional vector are taken out, and the remaining components are set to zero, so as to obtain the key information in a certain ontology application background. In the early stage of ontology data processing, the goal of the algorithm is to find the location of key components through the learning of some ontology sample points, if the relevant concepts and structure information of each ontology vertex with p-dimensional vectors are expressed. The ontology sparse vector itself contains a certain structure, such as the symmetry between components and the binding relationship between certain components, and the algorithm can also be used to dig out the correlation and decisive components between the components. In this paper, the graph structure is used to express these components and their interrelationships, and the optimal solution is obtained by using spectral graph theory and graph optimization techniques. The essence of the proposed ontology learning algorithm is to find the decisive vertices in the graph

G_{β}

. Finally, two experiments show that the given ontology learning algorithm is effective in similarity calculation and ontology mapping in some specific engineering fields. Full article

(This article belongs to the Special Issue Fuzzy Mathematics Applied to Science, Engineering and Sustainability Issues)

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18 pages, 10121 KiB

Open AccessArticle

Low-Light Image Enhancement Based on Quasi-Symmetric Correction Functions by Fusion

by Changli Li, Shiqiang Tang, Jingwen Yan and Teng Zhou

Symmetry 2020, 12(9), 1561; https://doi.org/10.3390/sym12091561 - 21 Sep 2020

Cited by 17 | Viewed by 2795

Abstract

Sometimes it is very difficult to obtain high-quality images because of the limitations of image-capturing devices and the environment. Gamma correction (GC) is widely used for image enhancement. However, traditional GC perhaps cannot preserve image details and may even reduce local contrast within [...] Read more.

Sometimes it is very difficult to obtain high-quality images because of the limitations of image-capturing devices and the environment. Gamma correction (GC) is widely used for image enhancement. However, traditional GC perhaps cannot preserve image details and may even reduce local contrast within high-illuminance regions. Therefore, we first define two couples of quasi-symmetric correction functions (QCFs) to solve these problems. Moreover, we propose a novel low-light image enhancement method based on proposed QCFs by fusion, which combines a globally-enhanced image by QCFs and a locally-enhanced image by contrast-limited adaptive histogram equalization (CLAHE). A large number of experimental results showed that our method could significantly enhance the detail and improve the contrast of low-light images. Our method also has a better performance than other state-of-the-art methods in both subjective and objective assessments. Full article

(This article belongs to the Section Computer)

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12 pages, 616 KiB

Open AccessArticle

Exact Solutions and Continuous Numerical Approximations of Coupled Systems of Diffusion Equations with Delay

by Elia Reyes, M. Ángeles Castro, Antonio Sirvent and Francisco Rodríguez

Symmetry 2020, 12(9), 1560; https://doi.org/10.3390/sym12091560 - 21 Sep 2020

Cited by 3 | Viewed by 1726

Abstract

In this work, we obtain exact solutions and continuous numerical approximations for mixed problems of coupled systems of diffusion equations with delay. Using the method of separation of variables, and based on an explicit expression for the solution of the separated vector initial-value [...] Read more.

In this work, we obtain exact solutions and continuous numerical approximations for mixed problems of coupled systems of diffusion equations with delay. Using the method of separation of variables, and based on an explicit expression for the solution of the separated vector initial-value delay problem, we obtain exact infinite series solutions that can be truncated to provide analytical–numerical solutions with prescribed accuracy in bounded domains. Although usually implicit in particular applications, the method of separation of variables is deeply correlated with symmetry ideas. Full article

(This article belongs to the Special Issue Ordinary and Partial Differential Equations: Theory and Applications)

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17 pages, 1188 KiB

Open AccessArticle

Reconstructed f(R) Gravity and Its Cosmological Consequences in theChameleon Scalar Field with a Scale Factor Describing the Pre-Bounce Ekpyrotic Contraction

by Soumyodipta Karmakar, Kairat Myrzakulov, Surajit Chattopadhyay and Ratbay Myrzakulov

Symmetry 2020, 12(9), 1559; https://doi.org/10.3390/sym12091559 - 21 Sep 2020

Cited by 6 | Viewed by 2585

Abstract

The present study reports a reconstruction scheme for

f (R)

gravity with the scale factor

a (t) \propto {(t_{*} - t)}^{\frac{2}{c^{2}}}

describing the pre-bounce ekpyrotic contraction, where

t_{*}

is the big crunch [...] Read more.

The present study reports a reconstruction scheme for

f (R)

gravity with the scale factor

a (t) \propto {(t_{*} - t)}^{\frac{2}{c^{2}}}

describing the pre-bounce ekpyrotic contraction, where

t_{*}

is the big crunch time. The reconstructed

f (R)

is used to derive expressions for density and pressure contributions, and the equation of state parameter resulting from this reconstruction is found to behave like “quintom”. It has also been observed that the reconstructed

f (R)

has satisfied a sufficient condition for a realistic model. In the subsequent phase, the reconstructed

f (R)

is applied to the model of the chameleon scalar field, and the scalar field

ϕ

and the potential

V (ϕ)

are tested for quasi-exponential expansion. It has been observed that although the reconstructed

f (R)

satisfies one of the sufficient conditions for realistic model, the quasi-exponential expansion is not available due to this reconstruction. Finally, the consequences of pre-bounce ekpyrotic inflation in

f (R)

gravity are compared to the background solution for

f (R)

matter bounce. Full article

(This article belongs to the Section Physics)

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19 pages, 523 KiB

Open AccessArticle

Stuck Knots

by Khaled Bataineh

Symmetry 2020, 12(9), 1558; https://doi.org/10.3390/sym12091558 - 21 Sep 2020

Cited by 2 | Viewed by 2105

Abstract

Singular knots and links have projections involving some usual crossings and some four-valent rigid vertices. Such vertices are symmetric in the sense that no strand overpasses the other. In this research we introduce stuck knots and links to represent physical knots and links [...] Read more.

Singular knots and links have projections involving some usual crossings and some four-valent rigid vertices. Such vertices are symmetric in the sense that no strand overpasses the other. In this research we introduce stuck knots and links to represent physical knots and links with projections involving some stuck crossings, where the physical strands get stuck together showing which strand overpasses the other at a stuck crossing. We introduce the basic elements of the theory and we give some isotopy invariants of such knots including invariants which capture the chirality (mirror imaging) of such objects. We also introduce another natural class of stuck knots, which we call relatively stuck knots, where each stuck crossing has a stuckness factor that indicates to the value of stuckness at that crossing. Amazingly, a generalized version of Jones polynomial makes an invariant of such quantized knots and links. We give applications of stuck knots and links and their invariants in modeling and understanding bonded RNA foldings, and we explore the topology of such objects with invariants involving multiplicities at the bonds. Other perspectives are also discussed. Full article

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20 pages, 821 KiB

Open AccessArticle

On Product of Smooth Neutrosophic Topological Spaces

by Kalaivani Chandran, Swathi Sundari Sundaramoorthy, Florentin Smarandache and Saeid Jafari

Symmetry 2020, 12(9), 1557; https://doi.org/10.3390/sym12091557 - 21 Sep 2020

Cited by 1 | Viewed by 1540

Abstract

In this paper, we develop the notion of the basis for a smooth neutrosophic topology in a more natural way. As a sequel, we define the notion of symmetric neutrosophic quasi-coincident neighborhood systems and prove some interesting results that fit with the classical [...] Read more.

In this paper, we develop the notion of the basis for a smooth neutrosophic topology in a more natural way. As a sequel, we define the notion of symmetric neutrosophic quasi-coincident neighborhood systems and prove some interesting results that fit with the classical ones, to establish the consistency of theory developed. Finally, we define and discuss the concept of product topology, in this context, using the definition of basis. Full article

(This article belongs to the Section Mathematics)

12 pages, 3769 KiB

Open AccessArticle

An Efficient Network Resource Management in SDN for Cloud Services

by Myunghoon Jeon, Namgi Kim, Yehoon Jang and Byoung-Dai Lee

Symmetry 2020, 12(9), 1556; https://doi.org/10.3390/sym12091556 - 21 Sep 2020

Cited by 5 | Viewed by 2063

Abstract

With the recent advancements in cloud computing technology, the number of cloud-based services has been gradually increasing. Symmetrically, users are asking for quality of experience (QoE) to be maintained or improved. To do this, it has become necessary to manage network resources more [...] Read more.

With the recent advancements in cloud computing technology, the number of cloud-based services has been gradually increasing. Symmetrically, users are asking for quality of experience (QoE) to be maintained or improved. To do this, it has become necessary to manage network resources more efficiently inside the cloud. Many theoretical studies for improving the users’ QoE have been proposed. However, there are few practical solutions due to the lack of symmetry between implementation and theoretical researches. Hence, in this study, we propose a ranking table-based network resource allocation method that dynamically allocates network resources per service flow based on flow information periodically collected from a software defined network (SDN). It dynamically identifies the size of the data transmission for each service flow on the SDN and differentially allocates network resources to each service flow based on this size. As a result, it maintains the maximum QoE for the user by increasing the network utilization. The experimental results show that the proposed method achieves 29.4% higher network efficiency than the general Open Shortest Path First (OSPF) method on average. Full article

(This article belongs to the Section Computer)

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25 pages, 2993 KiB

Open AccessArticle

Parallel Hybrid Testing Techniques for the Dual-Programming Models-Based Programs

by Ahmed Mohammed Alghamdi, Fathy Elbouraey Eassa, Maher Ali Khamakhem, Abdullah Saad AL-Malaise AL-Ghamdi, Ahmed S. Alfakeeh, Abdullah S. Alshahrani and Ala A. Alarood

Symmetry 2020, 12(9), 1555; https://doi.org/10.3390/sym12091555 - 20 Sep 2020

Cited by 4 | Viewed by 2467

Abstract

The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware’s ability as well as the parallelism in the application by integrating more than one programming model. One [...] Read more.

The importance of high-performance computing is increasing, and Exascale systems will be feasible in a few years. These systems can be achieved by enhancing the hardware’s ability as well as the parallelism in the application by integrating more than one programming model. One of the dual-programming model combinations is Message Passing Interface (MPI) + OpenACC, which has several features including increased system parallelism, support for different platforms with more performance, better productivity, and less programming effort. Several testing tools target parallel applications built by using programming models, but more effort is needed, especially for high-level Graphics Processing Unit (GPU)-related programming models. Owing to the integration of different programming models, errors will be more frequent and unpredictable. Testing techniques are required to detect these errors, especially runtime errors resulting from the integration of MPI and OpenACC; studying their behavior is also important, especially some OpenACC runtime errors that cannot be detected by any compiler. In this paper, we enhance the capabilities of ACC_TEST to test the programs built by using the dual-programming models MPI + OpenACC and detect their related errors. Our tool integrated both static and dynamic testing techniques to create ACC_TEST and allowed us to benefit from the advantages of both techniques reducing overheads, enhancing system execution time, and covering a wide range of errors. Finally, ACC_TEST is a parallel testing tool that creates testing threads based on the number of application threads for detecting runtime errors. Full article

(This article belongs to the Section Computer)

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7 pages, 748 KiB

Open AccessArticle

Existence and Uniqueness of the Solution for an Integral Equation with Supremum, via w-Distances

by Veronica Ilea and Diana Otrocol

Symmetry 2020, 12(9), 1554; https://doi.org/10.3390/sym12091554 - 20 Sep 2020

Cited by 12 | Viewed by 2076

Abstract

Following the idea of T. Wongyat and W. Sintunavarat, we obtain some existence and uniqueness results for the solution of an integral equation with supremum. The paper ends with the study of Gronwall-type theorems, comparison theorems and a result regarding a Ulam–Hyers stability [...] Read more.

Following the idea of T. Wongyat and W. Sintunavarat, we obtain some existence and uniqueness results for the solution of an integral equation with supremum. The paper ends with the study of Gronwall-type theorems, comparison theorems and a result regarding a Ulam–Hyers stability result for the corresponding fixed point problem. Full article

(This article belongs to the Special Issue Fixed Point Theory and Computational Analysis with Applications)

18 pages, 1340 KiB

Open AccessArticle

US Dollar/Turkish Lira Exchange Rate Forecasting Model Based on Deep Learning Methodologies and Time Series Analysis

by Harun Yasar and Zeynep Hilal Kilimci

Symmetry 2020, 12(9), 1553; https://doi.org/10.3390/sym12091553 - 20 Sep 2020

Cited by 10 | Viewed by 4076

Abstract

Exchange rate forecasting has been an important topic for investors, researchers, and analysts. In this study, financial sentiment analysis (FSA) and time series analysis (TSA) are proposed to form a predicting model for US Dollar/Turkish Lira exchange rate. For this purpose, the proposed [...] Read more.

Exchange rate forecasting has been an important topic for investors, researchers, and analysts. In this study, financial sentiment analysis (FSA) and time series analysis (TSA) are proposed to form a predicting model for US Dollar/Turkish Lira exchange rate. For this purpose, the proposed hybrid model is constructed in three stages: obtaining and modeling text data for FSA, obtaining and modeling numerical data for TSA, and blending two models like a symmetry. To our knowledge, this is the first study in the literature that uses social media platforms as a source for FSA and blends them with TSA methods. To perform FSA, word embedding methods Word2vec, GloVe, fastText, and deep learning models such as CNN, RNN, LSTM are used. To the best of our knowledge, this study is the first attempt in terms of performing the FSA by using the combinations of deep learning models with word embedding methods for both Turkish and English texts. For TSA, simple exponential smoothing, Holt–Winters, Holt’s linear, and ARIMA models are employed. Finally, with the usage of the proposed model, any user who wants to make a US Dollar/Turkish Lira exchange rate forecast will be able to make a more consistent and strong exchange rate forecast. Full article

(This article belongs to the Section Computer)

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18 pages, 6449 KiB

Open AccessArticle

Research on Image Adaptive Enhancement Algorithm under Low Light in License Plate Recognition System

by Chunhe Shi, Chengdong Wu and Yuan Gao

Symmetry 2020, 12(9), 1552; https://doi.org/10.3390/sym12091552 - 20 Sep 2020

Cited by 3 | Viewed by 2933

Abstract

The traffic block port monitors and manages the road traffic by shooting and recording the motor vehicles. However, due to the complex factors such as shooting angle, light condition, environmental background, etc., the recognition rate of license plate is not high enough. High [...] Read more.

The traffic block port monitors and manages the road traffic by shooting and recording the motor vehicles. However, due to the complex factors such as shooting angle, light condition, environmental background, etc., the recognition rate of license plate is not high enough. High light and low light under complex lighting conditions are symmetry problems. This paper analyzes and solves the low light problem in detail, an image adaptive enhancement algorithm under low light conditions is proposed in the paper. The algorithm mainly includes four modules, among which, the fast image classification module uses the deep and separable convolutional neural network to classify low-light images into low-light images by day and low-light images by night, greatly reducing the computation burden on the basis of ensuring the classification accuracy. The image enhancement module inputs the classified images into two different image enhancement algorithms and adopts the idea of dividing and ruling; the image quality evaluation module adopts a weighted comprehensive evaluation index. The final experiment shows that the comprehensive evaluation indexes are all greater than 0.83, which can improve the subsequent recognition of vehicle face and license plate. Full article

(This article belongs to the Section Computer)

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35 pages, 3704 KiB

Open AccessEditor’s ChoiceArticle

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

by Bartłomiej Kizielewicz and Wojciech Sałabun

Symmetry 2020, 12(9), 1551; https://doi.org/10.3390/sym12091551 - 20 Sep 2020

Cited by 48 | Viewed by 3397

Abstract

Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet [...] Read more.

Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet identification of preferences makes it impossible to determine the preferences for new alternatives. In this work, we propose a new approach to identifying a multi-criteria decision model to address this challenge. Our proposal is based on stochastic optimization techniques and the characteristic objects method (COMET). An extensive work comparing the use of hill-climbing, simulated annealing, and particle swarm optimization algorithms are presented in this paper. The paper also contains preliminary studies on initial conditions. Finally, our approach has been demonstrated using a simple numerical example. Full article

(This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problems)

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6 pages, 241 KiB

Open AccessArticle

Explicit Formulas for All Scator Holomorphic Functions in the (1+2)-Dimensional Case

by Jan L. Cieśliński and Dzianis Zhalukevich

Symmetry 2020, 12(9), 1550; https://doi.org/10.3390/sym12091550 - 20 Sep 2020

Cited by 5 | Viewed by 1814

Abstract

Scators form a vector space endowed with a non-distributive product, in the hyperbolic case, have physical applications related to some deformations of special relativity (breaking the Lorentz symmetry) while the elliptic case leads to new examples of hypercomplex numbers and related notions of [...] Read more.

Scators form a vector space endowed with a non-distributive product, in the hyperbolic case, have physical applications related to some deformations of special relativity (breaking the Lorentz symmetry) while the elliptic case leads to new examples of hypercomplex numbers and related notions of holomorphicity. Until now, only a few particular cases of scator holomorphic functions have been found. In this paper we obtain all solutions of the generalized Cauchy–Riemann system which describes analogues of holomorphic functions in the

(1 + 2)

-dimensional scator space. Full article

(This article belongs to the Special Issue Symmetry in Geometric Functions and Mathematical Analysis)

56 pages, 2440 KiB

Open AccessEditor’s ChoiceArticle

Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods

by Wojciech Sałabun, Jarosław Wątróbski and Andrii Shekhovtsov

Symmetry 2020, 12(9), 1549; https://doi.org/10.3390/sym12091549 - 20 Sep 2020

Cited by 245 | Viewed by 8792

Abstract

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) [...] Read more.

Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors’ approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods. Full article

(This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problems)

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