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Symmetry
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Symmetry and IoT Intelligence in the Post Pandemic Economy
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Symmetry and IoT Intelligence in the Post Pandemic Economy

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 49150

Special Issue Editor

Prof. Dr. Peng-Yeng Yin

E-Mail Website
Guest Editor
Information Technology and Management Program, Ming Chuan University, Taoyuan City 333, Taiwan
Interests: artificial intelligence; evolutionary computation; wind and solar energy; metaheuristics; pattern recognition; image processing; machine learning; software engineering; computational intelligence; operations research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

“Symmetry” stems in almost every discipline of natural and social sciences. Its elements appear in many applications, for example, object recognition, engineering design, music composition, and market prediction. By using the properties of “symmetry”, intelligent systems such as Internet of Things (IoT), Cyber Physical System (CPS) can be made more efficient and effective. The changing of industry innovative technology and business challenging competitiveness is overwhelming in the last decade. It is partly due to the emerging of new technologies such as IoT, CPS, deep learning, self media, shared economy¸ and partly due to the international trade protection which constrains the development of global supply chain and regional tax-free agreement. The advent of COVID-19 pandemic posed a tremendous setback on economy, but it also gives birth to new opportunities of emerging industry and health-related business, ranging from E-business, delivery platform, work-from-home appliances, facial mask design, disinfectant, and health promotion products. This sort of post pandemic economy will definitely play a major role in the future. The aim of this Special Issue is to call attention to the important trend of using Symmetry and IoT Intelligence in the Post Pandemic Economy. We are collaborating with several conferences on this theme and are also open for submissions (research and review articles) covering the topics, including (though not limited to) the following:

  • symmetry and heuristic and metaheuristic
  • symmetry and IoT applications
  • symmetry technology in post pandemic economy
  • IoT in post pandemic economy
  • emerging industry in post pandemic economy
  • agriculture technology in post pandemic economy
  • business, finance, and tourism in post pandemic economy
  • IoT in big health industry
  • emerging industry in big health industry
  • agriculture technology in big health industry
  • business, finance, and tourism in big health industry

Prof. Dr. Peng-Yeng Yin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • symmetry
  • Internet of Things (IoT)
  • big health
  • heuristic and metaheuristic
  • post pandemic economy

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Published Papers (7 papers)

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Research

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28 pages, 936 KiB  
Article
Sovereign Debt and Currency Crises Prediction Models Using Machine Learning Techniques
by David Alaminos, José Ignacio Peláez, M. Belén Salas and Manuel A. Fernández-Gámez
Symmetry 2021, 13(4), 652; https://doi.org/10.3390/sym13040652 - 12 Apr 2021
Cited by 12 | Viewed by 3542
Abstract
Sovereign debt and currencies play an increasingly influential role in the development of any country, given the need to obtain financing and establish international relations. A recurring theme in the literature on financial crises has been the prediction of sovereign debt and currency [...] Read more.
Sovereign debt and currencies play an increasingly influential role in the development of any country, given the need to obtain financing and establish international relations. A recurring theme in the literature on financial crises has been the prediction of sovereign debt and currency crises due to their extreme importance in international economic activity. Nevertheless, the limitations of the existing models are related to accuracy and the literature calls for more investigation on the subject and lacks geographic diversity in the samples used. This article presents new models for the prediction of sovereign debt and currency crises, using various computational techniques, which increase their precision. Also, these models present experiences with a wide global sample of the main geographical world zones, such as Africa and the Middle East, Latin America, Asia, Europe, and globally. Our models demonstrate the superiority of computational techniques concerning statistics in terms of the level of precision, which are the best methods for the sovereign debt crisis: fuzzy decision trees, AdaBoost, extreme gradient boosting, and deep learning neural decision trees, and for forecasting the currency crisis: deep learning neural decision trees, extreme gradient boosting, random forests, and deep belief network. Our research has a large and potentially significant impact on the macroeconomic policy adequacy of the countries against the risks arising from financial crises and provides instruments that make it possible to improve the balance in the finance of the countries. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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22 pages, 6132 KiB  
Article
Vehicular Communications Utility in Road Safety Applications: A Step toward Self-Aware Intelligent Traffic Systems
by Eduard Zadobrischi and Mihai Dimian
Symmetry 2021, 13(3), 438; https://doi.org/10.3390/sym13030438 - 8 Mar 2021
Cited by 23 | Viewed by 3973
Abstract
The potential of wireless technologies is significant in the area of the safety and efficiency of road transport and communications systems. The challenges and requirements imposed by end users and competent institutions demonstrate the need for viable solutions. A common protocol by which [...] Read more.
The potential of wireless technologies is significant in the area of the safety and efficiency of road transport and communications systems. The challenges and requirements imposed by end users and competent institutions demonstrate the need for viable solutions. A common protocol by which there could be vehicle-to-vehicle and vehicle-to-road communications is ideal for avoiding collisions and road accidents, all in a vehicular ad hoc network (VANET). Ways of transmitting warning messages simultaneously by vehicle-to-vehicle and vehicle-to-infrastructure communications by various multi-hop routings are set out. Approaches to how to improve communication reliability by achieving low latency are addressed through the multi-channel (MC) technique based on two non-overlaps for vehicle-to-vehicle (V2V) and vehicle-to-road (V2R) or road-to-vehicle (R2V) communications. The contributions of this paper offer an opportunity to use common communication adaptable protocols, depending on the context of the situation, coding techniques, scenarios, analysis of transfer rates, and reception of messages according to the type of protocol used. Communications between the road infrastructure and users through a relative communication protocol are highlighted and simulated in this manuscript. The results obtained by the proposed and simulated scenarios demonstrate that it is complementary and that the common node of V2V/V2R (R2V) communication protocols substantially improves the process of transmitting messages in low-latency conditions and is ideal for the development of road safety systems. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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25 pages, 7751 KiB  
Article
A Scalable Virtualized Server Cluster Providing Sensor Data Storage and Web Services
by Mei-Ling Chiang and Tsung-Te Hou
Symmetry 2020, 12(12), 1942; https://doi.org/10.3390/sym12121942 - 25 Nov 2020
Cited by 3 | Viewed by 3827
Abstract
With the rapid development of the Internet of Things (IoT) technology, diversified applications deploy extensive sensors to monitor objects, such as PM2.5 air quality monitoring. The sensors transmit data to the server periodically and continuously. However, a single server cannot provide efficient [...] Read more.
With the rapid development of the Internet of Things (IoT) technology, diversified applications deploy extensive sensors to monitor objects, such as PM2.5 air quality monitoring. The sensors transmit data to the server periodically and continuously. However, a single server cannot provide efficient services for the ever-growing IoT devices and the data they generate. This study bases on the concept of symmetry of architecture and quantities in system design and explores the load balancing issue to improve performance. This study uses the Linux Virtual Server (LVS) and virtualization technology to deploy a virtual machine (VM) cluster. It consists of a front-end server, also a load balancer, to dispatch requests, and several back-end servers to provide services. These receive data from sensors and provide Web services for browsing real-time sensor data. The Hadoop Distributed File System (HDFS) and HBase are used to store the massive amount of received sensor data. Because load-balancing is critical for resource utilization, this study also proposes a new load distribution algorithm for VM-based server clusters that simultaneously provide multiple services, such as sensor services and Web service. It considers the aggregate load of all back-end servers on the same physical server that provides multiple services. It also considers the difference between physical machines and VMs. Algorithms such as those for LVS, which do not consider these factors, can cause load imbalance between physical servers. The experimental results demonstrate that the proposed system is fault tolerant, highly scalable, and offers high availability and high performance. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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20 pages, 4452 KiB  
Article
Context-Dependent Object Proposal and Recognition
by Ray-I Chang, Chao-Lung Ting, Syuan-Yi Wu and Peng-Yeng Yin
Symmetry 2020, 12(10), 1619; https://doi.org/10.3390/sym12101619 - 30 Sep 2020
Cited by 3 | Viewed by 1985
Abstract
Accurate and fast object recognition is crucial in applications such as automatic driving and unmanned aerial vehicles. Traditional object recognition methods relying on image-wise computations cannot afford such real-time applications. Object proposal methods appear to fit into this scenario by segmenting object-like regions [...] Read more.
Accurate and fast object recognition is crucial in applications such as automatic driving and unmanned aerial vehicles. Traditional object recognition methods relying on image-wise computations cannot afford such real-time applications. Object proposal methods appear to fit into this scenario by segmenting object-like regions to be further analyzed by sophisticated recognition models. Traditional object proposal methods have the drawback of generating many proposals in order to maintain a satisfactory recall of true objects. This paper presents two proposal refinement strategies based on low-level cues and context-dependent features, respectively. The low-level cues are used to enhance the edge image, while the context-dependent features are verified to rule out false objects that are irrelevant to our application. In particular, the context of the drink commodity is considered because the drink commodity has the largest sales in Taiwan’s convenience store chains, and the analysis of its context has great value in marketing and management. We further developed a support vector machine (SVM) based on the Bag of Words (BoW) model with scale-invariant feature transform (SIFT) descriptors to recognize the proposals. The experimental results show that our object proposal method generates many fewer proposals than those generated by Selective Search and EdgeBoxes, with similar recall. For the performance of SVM, at least 82% of drink objects are correctly recognized for test datasets of various challenging difficulties. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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18 pages, 354 KiB  
Article
Truncated-Exponential-Based Appell-Type Changhee Polynomials
by Tabinda Nahid, Parvez Alam and Junesang Choi
Symmetry 2020, 12(10), 1588; https://doi.org/10.3390/sym12101588 - 24 Sep 2020
Cited by 12 | Viewed by 2054
Abstract
The truncated exponential polynomials em(x) (1), their extensions, and certain newly-introduced polynomials which combine the truncated exponential polynomials with other known polynomials have been investigated and applied in various ways. In this paper, by incorporating the Appell-type Changhee polynomials [...] Read more.
The truncated exponential polynomials em(x) (1), their extensions, and certain newly-introduced polynomials which combine the truncated exponential polynomials with other known polynomials have been investigated and applied in various ways. In this paper, by incorporating the Appell-type Changhee polynomials Chn*(x) (10) and the truncated exponential polynomials in a natural way, we aim to introduce so-called truncated-exponential-based Appell-type Changhee polynomials eCn*(x) in Definition 1. Then, we investigate certain properties and identities for these new polynomials such as explicit representation, addition formulas, recurrence relations, differential and integral formulas, and some related inequalities. We also present some integral inequalities involving these polynomials eCn*(x). Further we discuss zero distributions of these polynomials by observing their graphs drawn by Mathematica. Lastly some open questions are suggested. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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19 pages, 6583 KiB  
Article
Traffic Flow Density Model and Dynamic Traffic Congestion Model Simulation Based on Practice Case with Vehicle Network and System Traffic Intelligent Communication
by Eduard Zadobrischi, Lucian-Mihai Cosovanu and Mihai Dimian
Symmetry 2020, 12(7), 1172; https://doi.org/10.3390/sym12071172 - 15 Jul 2020
Cited by 33 | Viewed by 11506
Abstract
The massive increase in the number of vehicles has set a precedent in terms of congestion, being one of the important factors affecting the flow of traffic, but there are also effects on the world economy. The studies carried out so far try [...] Read more.
The massive increase in the number of vehicles has set a precedent in terms of congestion, being one of the important factors affecting the flow of traffic, but there are also effects on the world economy. The studies carried out so far try to highlight solutions that will streamline the traffic, as society revolves around transportation and its symmetry. Current research highlights that the increased density of vehicles could be remedied by dedicated short-range communications (DSRC) systems through communications of the type vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) or vehicle-to-everything (V2X). We can say that wireless communication technologies have the potential to significantly change the efficiency and road safety, thus improving the efficiency of transport systems. An important factor is to comply with the requirements imposed on the use of vehicle safety and transport applications. Therefore, this paper focuses on several simulations on the basis of symmetry models, implemented in practical cases in order to streamline vehicle density and reduce traffic congestion. The scenarios aim at both the communication of the vehicles with each other and their prioritization by the infrastructure, so we can have a report on the efficiency of the proposed models. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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Review

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29 pages, 1381 KiB  
Review
Internet of Things and Its Applications: A Comprehensive Survey
by Rosilah Hassan, Faizan Qamar, Mohammad Kamrul Hasan, Azana Hafizah Mohd Aman and Amjed Sid Ahmed
Symmetry 2020, 12(10), 1674; https://doi.org/10.3390/sym12101674 - 14 Oct 2020
Cited by 200 | Viewed by 20794
Abstract
With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create [...] Read more.
With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create a single communication architecture. As it has significantly expanded in recent years, it is fundamental to study this trending technology in detail and take a close look at its applications in the different domains. It represents an enabler of new communication possibilities between people and things. The main asset of this concept is its significant influence through the creation of a new world dimension. The key features required for employing a large-scale IoT are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications. This research work is presented in four main sections, including a general overview of IoT technology, a summary of previous correlated surveys, a review regarding the main IoT applications, and a section on the challenges of IoT. The purpose of this study is to fully cover the applications of IoT, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. This work explains the concept of IoT and defines and summarizes its main technologies and uses, offering a next-generation protocol as a solution to the challenges. IoT challenges were investigated to enhance research and development in the fields. The contribution and weaknesses of each research work cited are covered, highlighting eventual possible research questions and open matters for IoT applications to ensure a full analysis coverage of the discussed papers. Full article
(This article belongs to the Special Issue Symmetry and IoT Intelligence in the Post Pandemic Economy)
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