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Symmetry
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Computer Science and Symmetry/Asymmetry: Feature Papers
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Computer Science and Symmetry/Asymmetry: Feature Papers

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

Deadline for manuscript submissions: closed (15 May 2024) | Viewed by 8307

Special Issue Editor

Prof. Dr. Alexander Shelupanov

E-Mail Website
Guest Editor
Department of Complex Information Security of Computer Systems, University of Control Systems and Radioelectronics, Lenin Ave, 40, Tomskaya Oblast, 634050 Tomsk, Russia
Interests: theory and practice of complex information security systems; information security, mathematical modeling of difficult systems; algorithms of processing of big data
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As Section Editor-in-Chief of the Computer Science and Symmetry/Asymmetry Section of the journal Symmetry, I am glad to announce this Special Issue on “Computer Science and Symmetry/Asymmetry: Feature Papers”. We would like to cooperate with some excellent scholars/scientific groups and publish several very important high-level works. Our aim now is to introduce new insights into science development or cutting-edge technology related to the symmetry field in Computer Science which will make a great contribution to the community. The topics include information security, cybersecurity, IoT, robotics, big data, machine learning, artificial intelligence, and other areas of interest associated with computer science and engineering.

You are welcome to send short proposals for submissions of Feature Papers to our Editorial Office ([email protected]) before submission.

These will firstly be evaluated by our Editors. Please note that selected full papers will still be subject to a thorough and rigorous peer review.

Prof. Dr. Alexander Shelupanov
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.

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Published Papers (5 papers)

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Research

23 pages, 6711 KiB  
Article
Simulation of Dynamic Path Planning of Symmetrical Trajectory of Mobile Robots Based on Improved A* and Artificial Potential Field Fusion for Natural Resource Exploration
by Yuriy Kozhubaev and Ruide Yang
Symmetry 2024, 16(7), 801; https://doi.org/10.3390/sym16070801 - 26 Jun 2024
Cited by 2 | Viewed by 1527
Abstract
With the rapid development of new-generation artificial intelligence and Internet of Things technology, mobile robot technology has been widely used in various fields. Among them, the autonomous path-planning technology of mobile robots is one of the cores for realizing their autonomous driving and [...] Read more.
With the rapid development of new-generation artificial intelligence and Internet of Things technology, mobile robot technology has been widely used in various fields. Among them, the autonomous path-planning technology of mobile robots is one of the cores for realizing their autonomous driving and obstacle avoidance. This study conducts an in-depth discussion on the real-time and dynamic obstacle avoidance capabilities of mobile robot path planning. First, we proposed a preprocessing method for obstacles in the grid map, focusing on the closed processing of the internal space of concave obstacles to ensure the feasibility of the path while effectively reducing the number of grid nodes searched by the A* algorithm, thereby improving path search efficiency. Secondly, in order to achieve static global path planning, this study adopts the A algorithm. However, in practice, algorithm A has problems such as a large number of node traversals, low search efficiency, redundant path nodes, and uneven turning angles. To solve these problems, we optimized the A* algorithm, focusing on optimizing the heuristic function and weight coefficient to reduce the number of node traversals and improve search efficiency. In addition, we use the Bezier curve method to smooth the path and remove redundant nodes, thereby reducing the turning angle. Then, in order to achieve dynamic local path planning, this study adopts the artificial potential field method. However, the artificial potential field method has the problems of unreachable target points and local minima. In order to solve these problems, we optimized the repulsion field so that the target point is at the lowest point of the global energy of the gravitational field and the repulsive field and eliminated the local optimal point. Finally, for the path-planning problem of mobile robots in dynamic environments, this study proposes a hybrid path-planning method based on a combination of the improved A* algorithm and the artificial potential field method. In this study, we not only focus on the efficiency of mobile robot path planning and real-time dynamic obstacle avoidance capabilities but also pay special attention to the symmetry of the final path. By introducing symmetry, we can more intuitively judge whether the path is close to the optimal state. Symmetry is an important criterion for us to evaluate the performance of the final path. Full article
(This article belongs to the Special Issue Computer Science and Symmetry/Asymmetry: Feature Papers)
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13 pages, 369 KiB  
Article
Maximum Coverage by k Lines
by Chaeyoon Chung, Antoine Vigneron and Hee-Kap Ahn
Symmetry 2024, 16(2), 206; https://doi.org/10.3390/sym16020206 - 9 Feb 2024
Viewed by 1176
Abstract
Given a set of n disks in the plane, we study the problem of finding k lines that together intersect the maximum number of input disks. We consider three variants of this problem with the following constraints on the solution: (1) no constraint [...] Read more.
Given a set of n disks in the plane, we study the problem of finding k lines that together intersect the maximum number of input disks. We consider three variants of this problem with the following constraints on the solution: (1) no constraint on the lines, (2) the k lines should be parallel and (3) the k lines should pass through a common point. For k=2, we give O(n3logn)-time algorithms for all three cases. For any fixed k≥3, we give an O(n3k/2)-time algorithm for (1). For variants (2) and (3), the running times of our algorithms vary from O(n4) to O(n6). Full article
(This article belongs to the Special Issue Computer Science and Symmetry/Asymmetry: Feature Papers)
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38 pages, 9244 KiB  
Article
Tour Route Recommendation Model by the Improved Symmetry-Based Naive Bayes Mining and Spatial Decision Forest Search
by Xiao Zhou, Jian Peng, Bowei Wen and Mingzhan Su
Symmetry 2023, 15(12), 2168; https://doi.org/10.3390/sym15122168 - 6 Dec 2023
Cited by 1 | Viewed by 1229
Abstract
In machine learning, classifiers have the feature of constant symmetry when performing the attribute transformation. In the research field of tourism recommendation, tourists’ interests should be mined and extracted by the symmetrical transformation in founding the training dataset and creating the classifier, so [...] Read more.
In machine learning, classifiers have the feature of constant symmetry when performing the attribute transformation. In the research field of tourism recommendation, tourists’ interests should be mined and extracted by the symmetrical transformation in founding the training dataset and creating the classifier, so as to ensure that the recommendation results meet the individualized interests and needs. In this paper, by applying the feature of constant symmetry in the classifier and analyzing the research background and existing problems of POI tour routes, we propose and construct a tour route recommendation model using improved symmetry-based Naive Bayes mining and spatial decision forest search. First, the POI natural attribute classification model is constructed based on text mining to classify the natural attributes of the destination POIs. Second, the destination POI recommendation model based on the improved symmetry-based Naive Bayes mining and decision forest algorithm is constructed, outputting POIs that match tourists’ interests. On this basis, the POI tour route recommendation model based on a spatial decision tree algorithm is established, which outputs the optimal tour route with the lowest sub-interval cost and route interval cost. Finally, the validation and comparative experiments are designed to output the optimal POIs and tour routes by using the proposed algorithms, and then the proposed algorithm is compared with the commonly used route planning methods, GDM and 360M. Experimental results show that the proposed algorithm can reduce travel costs by 4.56% and 10.36%, respectively, on the optimal tour route compared to the GDM and 360M and by 2.94% and 8.01%, respectively, on the suboptimal tour route compared to the GDM and 360M, which verifies the advantages of the proposed algorithm over the traditional route planning methods. Full article
(This article belongs to the Special Issue Computer Science and Symmetry/Asymmetry: Feature Papers)
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18 pages, 2759 KiB  
Article
Map Construction and Path Planning Method for Mobile Robots Based on Collision Probability Model
by Jingwen Li, Wenkang Tang, Dan Zhang, Dayong Fan, Jianwu Jiang and Yanling Lu
Symmetry 2023, 15(10), 1891; https://doi.org/10.3390/sym15101891 - 9 Oct 2023
Cited by 2 | Viewed by 1479
Abstract
A map construction method based on a collision probability model and an improved A* algorithm is proposed to address the issues of insufficient security in mobile robot map construction and path planning in complex environments. The method is based on modeling the asymmetry [...] Read more.
A map construction method based on a collision probability model and an improved A* algorithm is proposed to address the issues of insufficient security in mobile robot map construction and path planning in complex environments. The method is based on modeling the asymmetry of paths, which complicates problem solving. Firstly, this article constructs a collision probability function model, and based on this model it is fused with the obstacle grid map, which is based on the grid method, to draw a collision probability grid map (CPGM) containing collision probability information. Secondly, incorporating the collision probability values from the CPGM into the actual cost function of the traditional A* algorithm improves the security of path planning in complex environments. The experimental results show that the improved A* algorithm decreases the percentage of dangerous nodes in complex environments by 69.23%, shortens the path planning length by 19.52%, reduces the search time by 16.8%, and reduces the number of turns by 46.67%. Therefore, the method in this paper solves the problem of traditional grid maps lacking security information and can plan a path with higher security and which is smoother, improving the security and robustness of mobile robot autonomous navigation in complex environments. Full article
(This article belongs to the Special Issue Computer Science and Symmetry/Asymmetry: Feature Papers)
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22 pages, 10429 KiB  
Article
An Invitation Model Protocol (IMP) for the Bitcoin Asymmetric Lightning Network
by Ali Abdullah and A. M. Mutawa
Symmetry 2023, 15(6), 1273; https://doi.org/10.3390/sym15061273 - 16 Jun 2023
Cited by 1 | Viewed by 2026
Abstract
The Lightning Network (LN), a second-layer protocol built atop Bitcoin, promises swift, low-cost transactions, thereby addressing blockchain scalability and enhancing user privacy. As the global financial technology landscape evolves, the LN’s importance in the future of fintech and the Fourth Industrial Revolution (4IR) [...] Read more.
The Lightning Network (LN), a second-layer protocol built atop Bitcoin, promises swift, low-cost transactions, thereby addressing blockchain scalability and enhancing user privacy. As the global financial technology landscape evolves, the LN’s importance in the future of fintech and the Fourth Industrial Revolution (4IR) becomes increasingly pivotal. The anticipated rise of blockchain-based payments and smart contracts in businesses demands a more agile and secure payment system. However, the LN’s early stage raises valid concerns about security and reliability, especially when implemented on a huge asymmetric network such as the Internet, potentially hindering its broader adoption. Malicious nodes could intentionally cause payment failures or initiate attacks, such as DDoS attacks, by overwhelming other nodes in the network with channel-opening requests. As a result, users will be discouraged from using the LN; hence, the technology will become obsolete as individuals will not waste the time and power investment required for using this technology. Addressing these issues, this paper proposes an innovative invitation model protocol (IMP) to reinforce the LN’s security and reliability. The IMP creates an exclusive ‘Club’ within the LN, admitting only nodes verified as honest, thereby bolstering network security and reliability. The protocol empowers Club Founders to expel members exhibiting malicious activities, thereby preserving the invested time, energy, and funds of the network’s users. The IMP was rigorously tested using Amazon Web Services Virtual Machines within the Bitcoin and Lightning Network’s Testnet environment, which is a highly asymmetric network. The results demonstrated the protocol’s efficacy in fulfilling its objectives, marking a significant step towards a safer and more efficient blockchain transaction network. As the blockchain continues to revolutionize the financial sector, implementing robust security measures such as the IMP becomes essential. This research paper introduces a novel approach to enhancing the reliability and security of a Lightning Network (LN), and thus distinguishes itself from the existing literature, by introducing an additional step before establishing or joining such a network. The research underscores the critical role of such protocols in realizing the potential of the LN in powering the next wave of fintech and industrial innovation. Full article
(This article belongs to the Special Issue Computer Science and Symmetry/Asymmetry: Feature Papers)
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