Special Issue "Selected Papers from IIKII 2021 Conferences"

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 4641

Special Issue Editors

Prof. Dr. Teen-­Hang Meen
E-Mail Website
Guest Editor
Department of Electronic Engineering, National Formosa University, Yunlin 632, Taiwan
Interests: IoT devices; photovoltaic devices; STEM education
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Charles Tijus
E-Mail Website
Guest Editor
Director of the Cognitions Humaine et Artificielle Laboratory, Professeur de Psychologie Cognitive – Université, Paris 8, France
Interests: internet of objects; data mining; brain–computer interaction
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jih-Fu Tu
E-Mail Website
Guest Editor
Department of Electrical Engineering, Lunghwa University of Science and Technology, Taoyuan 333, Taiwan
Interests: human computer interaction; internet technologies; distributed processing systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Symmetry in language refers to a sense of harmonious and beautiful proportion and balance. In mathematics, “symmetry” has a more precise definition, i.e., that an object is invariant to any of various transformations, including reflectionrotation or scaling. Mathematical symmetry may be observed with respect to the passage of time, as a spatial relationship, through geometric transformations, through other kinds of functional transformations, and as an aspect of abstract objects, theoretic models and even knowledge itself. Recently, symmetry theorems and simulations have been widely applied in engineering to improve the developments of new technologies.

In addition, the International Institute of Knowledge Innovation and Invention (IIKII, http://www.iikii.org) promotes the exchange of innovations and inventions and establishes a communication platform for international innovations and research. Tthis year, IIKII is cooperating with the IEEE Tainan Section Sensors Council to hold IEEE conferences such as IEEE ECBIOS 2021 (http://www.ecbios.asia), IEEE ICAIRC 2021 (http://www.icairc.asia), IEEE ICKII 2021 (http://www.ickii.org), and IEEE ECICE 2021 (http://www.ecice.asia). This Special Issue entitled “Selected Papers from IIKII 2021 Conferences” shall publish excellent papers from IIKII 2021 conferences, including symmetry in physics, chemistry, biology, mathematics, and computer science, etc. We invite investigators to contribute original research articles, as well as review articles, to this Special Issue. Potential topics include but are not limited to:

  • Physics: conservation laws, Noether’s theorem, spatial parity, charge parity, time parity, G-parity, standard model, internal symmetry, Lorentz symmetry, transformations, invariance, conservation, local and global symmetries, laws and symmetry, symmetry breaking, color symmetry, periodic and quasiperiodic crystals, time-reversal symmetry breaking, symmetry and complexity, Curie–Rosen symmetry principles, constants, biophysics, entropy, and indistinguishability;
  • Chemistry: crystal and crystallography, chiral molecules, chiral resolution and asymmetric synthesis, asymmetric induction, chiral auxiliaries and chiral catalysts, stereochemistry, diastereomers, stereogenic, stereoisomers (enantiomers, atropisomers, diastereomers), stability, mixing, and phase separation;
  • Biology:symmetry in biology, radial symmetry (tetramerism, pentamerism, etc.), diversity, preservation, sustainability, morphology, origin of life, and molecular evolution (homochirality);
  • Mathematics: invariance, transformation, group theory, Lie groups, chirality, achiral or amphichiral, helix and Möbius strip, knot theory, graph theory, isometry, plane of symmetry, skewness, vertex algebra, asymmetry, dissymmetry, nonsymmetry and antisymmetry, supergroups and nonlinear algebraic structures, supersymmetry and supergravity, strings and branes, integrability and geometry, information theory, Felix Klein’s Erlangen Program, and continuous symmetry;
  • Computer Science, Theory and Methods:computer-aided design, computational geometry, computer graphics, visualization, image compression, data compression, pattern recognition, diversity, similarity, and conservation and sustainability.
  • Symmetry and other scientific disciplines and engineering.

Prof. Dr. Teen-­Hang Meen
Prof. Dr. Charles Tijus
Prof. Dr. Jih-Fu Tu
Guest Editors

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 1800 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

  • Physics symmetry
  • Chemistry symmetry
  • Biology symmetry
  • Mathematics symmetry, computer science, theory, and methods
  • Symmetry and other scientific disciplines and engineering

Published Papers (7 papers)

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Research

Article
Adaptive Superpixel-Based Disparity Estimation Algorithm Using Plane Information and Disparity Refining Mechanism in Stereo Matching
Symmetry 2022, 14(5), 1005; https://doi.org/10.3390/sym14051005 - 15 May 2022
Viewed by 390
Abstract
The motivation of this paper is to address the limitations of the conventional keypoint-based disparity estimation methods. Conventionally, disparity estimation is usually based on the local information of keypoints. However, keypoints may distribute sparsely in the smooth region, and keypoints with the same [...] Read more.
The motivation of this paper is to address the limitations of the conventional keypoint-based disparity estimation methods. Conventionally, disparity estimation is usually based on the local information of keypoints. However, keypoints may distribute sparsely in the smooth region, and keypoints with the same descriptors may appear in a symmetric pattern. Therefore, conventional keypoint-based disparity estimation methods may have limited performance in smooth and symmetric regions. The proposed algorithm is superpixel-based. Instead of performing keypoint matching, both keypoint and semiglobal information are applied to determine the disparity in the proposed algorithm. Since the local information of keypoints and the semi-global information of the superpixel are both applied, the accuracy of disparity estimation can be improved, especially for smooth and symmetric regions. Moreover, to address the non-uniform distribution problem of keypoints, a disparity refining mechanism based on the similarity and the distance of neighboring superpixels is applied to correct the disparity of the superpixel with no or few keypoints. The experiments show that the disparity map generated by the proposed algorithm has a lower matching error rate than that generated by other methods. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
Decision Making of Software Release Time at Different Confidence Intervals with Ohba’s Inflection S-Shape Model
Symmetry 2022, 14(3), 593; https://doi.org/10.3390/sym14030593 - 16 Mar 2022
Cited by 2 | Viewed by 508
Abstract
Software developers need information for deciding the optimal time for software release with improved software reliability. However, it is not easy for them to decide when and how to release newly developed software to the market. For a decision, the reliability and test [...] Read more.
Software developers need information for deciding the optimal time for software release with improved software reliability. However, it is not easy for them to decide when and how to release newly developed software to the market. For a decision, the reliability and test costs of the software need to be balanced carefully for avoiding unnecessary confusion and users’ complaints. To address this need, related research has been carried out to propose an appropriate tool for such decisions. In many studies, software reliability growth models (SRGMs) were applied using the concept of confidence intervals to estimate the reliability of software. Confidence intervals were calculated on the basis of the assumption of a normal distribution showing the symmetrical occurrence of data with the mean as a center. However, the reliability data of software do not always have such symmetry for assuming the normal distribution. Therefore, it is necessary to propose a method for overcoming the mean value randomness that causes asymmetry in the related data. In previous studies, estimating variance and mean of errors of software was not considered, which led to the unreliable estimation of the confidence intervals of the mean value for decision making. Previous studies also lacked practicability in applications due to statistics from the asymmetrical data distribution. As a result, software developers could not effectively evaluate the possible risk related to the software release time. To improve the estimation, we employ the inflection S-shape model to propose the SRGM on the basis of confidence intervals assumed to come from the normal distribution. The proposed model allows determining the optimal time for software release with the consideration of its potential risk. For efficient determination, the architecture and user interface of the computation system are also proposed. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
Developing an Optical Measuring System for Hole Saw Caps
Symmetry 2021, 13(12), 2311; https://doi.org/10.3390/sym13122311 - 03 Dec 2021
Viewed by 392
Abstract
This paper developed a set of size detection systems with a computer vision method based on the accuracy requirements of the hole saw caps to meet the needs of the accuracy detection machine. The results allow manufacturers to build a digitalized hole saw [...] Read more.
This paper developed a set of size detection systems with a computer vision method based on the accuracy requirements of the hole saw caps to meet the needs of the accuracy detection machine. The results allow manufacturers to build a digitalized hole saw cap detection system at a low cost. We have designed a measurement system for the hole saw caps with the computer vision method to measure the dimensions of the hole saw caps. However, a valid measurement value of the hole saw caps must be positioned symmetrically. However, in fact, when the measurement system is positioned accurately asymmetrically, it will cause a problem in the measurement data. Therefore, the dark box environment made of a light source and the back plate of the hole saw caps material and two cameras are employed to observe the hole saw caps from both above and the side views. Then, personal desktop computers calculate the size of the hole saw caps based on the camera screen vision with a Python program. The results of the proposed methodology are obtained by measuring 10 workpieces of different sizes, and all the errors within a range of 2 pixels (pixel, px) met the detection standards. Therefore, the developed hole saw cap detection system is in line with expectations. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
Majority Decision Aggregation with Binarized Data in Wireless Sensor Networks
Symmetry 2021, 13(9), 1671; https://doi.org/10.3390/sym13091671 - 10 Sep 2021
Cited by 1 | Viewed by 468
Abstract
Wireless sensor networks (WSNs) are the cornerstone of the current Internet of Things era. They have limited resources and features, a smaller packet size than other types of networks, and dynamic multi-hop transmission. WSNs can monitor a particular area of interest and are [...] Read more.
Wireless sensor networks (WSNs) are the cornerstone of the current Internet of Things era. They have limited resources and features, a smaller packet size than other types of networks, and dynamic multi-hop transmission. WSNs can monitor a particular area of interest and are used in many different applications. For example, during the COVID-19 pandemic, WSNs have been used to measure social distancing/contact tracing among people. However, the major challenge faced by WSN protocols is limited battery energy. Therefore, the whole WSN area is divided into odd clusters using k-means++ clustering to make a majority rule decision to reduce the amount of additional data sent to the base station (or sink) and achieve node energy-saving efficiency. This study proposes an energy-efficient binarized data aggregation (EEBDA) scheme, by which, through a threshold value, the collected sensing data are asserted with binary values. Subsequently, the corresponding cluster head (CH), according to the Hamming weight and the final majority decision, is calculated and sent to the base station (BS). The EEBDA is based on each cluster and divides the entire WSN area into four quadrants. All CHs construct a data-relay transmission link in the same quadrant; the binary value is transferred from the CHs to the sink. The EEBDA adopts a CH rotation scheme to aggregate the data based on the majority results in the cluster. The simulation results demonstrate that the EEBDA can reduce redundant data transmissions, average the energy consumption of nodes in the cluster, and obtain a better network lifetime when compared to the LEACH, LEACH-C, and DEEC algorithms. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
Identification and Machine Learning Prediction of Nonlinear Behavior in a Robotic Arm System
Symmetry 2021, 13(8), 1445; https://doi.org/10.3390/sym13081445 - 06 Aug 2021
Cited by 3 | Viewed by 675
Abstract
In this study, the subject of investigation was the dynamic double pendulum crank mechanism used in a robotic arm. The arm is driven by a DC motor though the crank system and connected to a fixed side with a mount that includes a [...] Read more.
In this study, the subject of investigation was the dynamic double pendulum crank mechanism used in a robotic arm. The arm is driven by a DC motor though the crank system and connected to a fixed side with a mount that includes a single spring and damping. Robotic arms are now widely used in industry, and the requirements for accuracy are stringent. There are many factors that can cause the induction of nonlinear or asymmetric behavior and even excite chaotic motion. In this study, bifurcation diagrams were used to analyze the dynamic response, including stable symmetric orbits and periodic and chaotic motions of the system under different damping and stiffness parameters. Behavior under different parameters was analyzed and verified by phase portraits, the maximum Lyapunov exponent, and Poincaré mapping. Firstly, to distinguish instability in the system, phase portraits and Poincaré maps were used for the identification of individual images, and the maximum Lyapunov exponents were used for prediction. GoogLeNet and ResNet-50 were used for image identification, and the results were compared using a convolutional neural network (CNN). This widens the convolutional layer and expands pooling to reduce network training time and thickening of the image; this deepens the network and strengthens performance. Secondly, the maximum Lyapunov exponent was used as the key index for the indication of chaos. Gaussian process regression (GPR) and the back propagation neural network (BPNN) were used with different amounts of data to quickly predict the maximum Lyapunov exponent under different parameters. The main finding of this study was that chaotic behavior occurs in the robotic arm system and can be more efficiently identified by ResNet-50 than by GoogLeNet; this was especially true for Poincaré map diagnosis. The results of GPR and BPNN model training on the three types of data show that GPR had a smaller error value, and the GPR-21 × 21 model was similar to the BPNN-51 × 51 model in terms of error and determination coefficient, showing that GPR prediction was better than that of BPNN. The results of this study allow the formation of a highly accurate prediction and identification model system for nonlinear and chaotic motion in robotic arms. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
Different Object Functions for SWIPT Optimization by SADDE and APSO
Symmetry 2021, 13(8), 1340; https://doi.org/10.3390/sym13081340 - 24 Jul 2021
Viewed by 657
Abstract
Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and [...] Read more.
Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and Harvesting Power (HP) are investigated in the broadband communication. Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Self-Adaptive Dynamic Differential Evolution (SADDE) and Asynchronous Particle Swarm Optimization (APSO) are used to optimize the feed length of the antenna array. Two different object functions are proposed in the paper. The first one is the weighting factor multiplying the constraint BER and HP plus HP. The second one is the constraint BER multiplying HP. Simulations show that the first object function is capable of optimizing the total harvesting power under the BER constraint and APSO can quickly converges quicker than SADDE. However, the weighting for the final object function requires a pretest in advance, whereas the second object function does not need to set the weighting case by case and the searching is more efficient than the first one. From the numerical results, the proposed criterion can achieve the SWIPT requirement. Thus, we can use the novel proposed criterion (the second criterion) to optimize the SWIPT problem without testing the weighting case by case. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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Article
A Secure Three-Factor Anonymous User Authentication Scheme for Internet of Things Environments
Symmetry 2021, 13(7), 1121; https://doi.org/10.3390/sym13071121 - 23 Jun 2021
Cited by 1 | Viewed by 648
Abstract
Internet of Things (IoT) is composed of various kinds of devices such as cars, electrical appliances, machines and sensors. With IoT technologies, devices can exchange information through the network, people are allowed to get information collected by devices without interacting with them, and [...] Read more.
Internet of Things (IoT) is composed of various kinds of devices such as cars, electrical appliances, machines and sensors. With IoT technologies, devices can exchange information through the network, people are allowed to get information collected by devices without interacting with them, and automatic operations for devices are realized. Because of the variety of IoT devices, some of them possess limited computational capability. On the other hand, data transmission in IoT networks is usually through a public channel. To ensure efficiency and security for IoT environments, Lee et al. proposed a three-factor authentication scheme with hash function and XOR operation. They claimed their scheme possessed superior properties and could resist common attacks. After analyzing their scheme, we find that their scheme is vulnerable to five flaws. In this paper, how these found flaws threaten Lee et al.’s scheme is shown in detail. Then, we propose an improvement to overcome the found flaws and preserve the advantages by employing ECC. Full article
(This article belongs to the Special Issue Selected Papers from IIKII 2021 Conferences)
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