Journal Description
Symmetry
Symmetry
is an international, peer-reviewed, open access journal covering research on symmetry/asymmetry phenomena wherever they occur in all aspects of natural sciences. Symmetry is published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus / SciFinder, Inspec, Astrophysics Data System, and other databases.
- Journal Rank: JCR - Q2 (Multidisciplinary Sciences) / CiteScore - Q1 (General Mathematics); Q1 (Physics and Astronomy); Q1 (Computer Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.2 days after submission; acceptance to publication is undertaken in 3.5 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Symmetry.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.7 (2022)
Latest Articles
MultiFuzzTOPS: A Fuzzy Multi-Criteria Decision-Making Model Using Type-2 Soft Sets and TOPSIS
Symmetry 2024, 16(6), 655; https://doi.org/10.3390/sym16060655 (registering DOI) - 25 May 2024
Abstract
Effective and optimal decision-making can enhance system performance, potentially leading to a positive reputation and financial gains. Multi-criteria decision-making (MCDM) is an important research topic widely applied to practical decision-making problems. Using the basic idea of symmetry to balance the arrangement where elements
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Effective and optimal decision-making can enhance system performance, potentially leading to a positive reputation and financial gains. Multi-criteria decision-making (MCDM) is an important research topic widely applied to practical decision-making problems. Using the basic idea of symmetry to balance the arrangement where elements or features have an equality or similarity in distribution, MCDM provides robust decisions in such multi-dimensional complex issues. This study proposes MultiFuzzTOPS, a decision-making model to deal with complexity of multi-criteria decision-making. The proposed MultiFuzzTOPS leverages the fuzzy logic and soft sets such as type-2 soft sets (T2SS) and technique for order preference by similarity to ideal solution (TOPSIS) for decision-making. We validate the proposed model by implementing it to solve the pesticide selection problem in food science by considering various criteria for the selection of pesticides. Our proposed MultiFuzzTOPS recommends the best pesticide compared with its counterparts because it covers the maximum information for the selection of the best alternative. Results are ranked on the basis of the Hamming distance and similarity coefficient. We also validate the effectiveness by performing the sensitivity analysis, and the validation shows the reliability and effectiveness of our proposed model.
Full article
(This article belongs to the Section Computer)
Open AccessArticle
A Modified Spectral Conjugate Gradient Method for Absolute Value Equations Associated with Second-Order Cones
by
Leifu Gao, Zheng Liu, Jingfei Zou and Zengwei Wang
Symmetry 2024, 16(6), 654; https://doi.org/10.3390/sym16060654 (registering DOI) - 25 May 2024
Abstract
In this paper, we propose a modified spectral conjugate gradient (MSCG) method for solving absolute value equations associated with second-order cones (SOCAVEs). Some properties of the SOCAVEs are analyzed, and the global convergence of the MSCG method is discussed in depth. Numerical experiments
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In this paper, we propose a modified spectral conjugate gradient (MSCG) method for solving absolute value equations associated with second-order cones (SOCAVEs). Some properties of the SOCAVEs are analyzed, and the global convergence of the MSCG method is discussed in depth. Numerical experiments are given to illustrate the effectiveness and competitiveness of our algorithm.
Full article
(This article belongs to the Section Mathematics)
Open AccessArticle
A Symmetric Multiprocessor System-on-a-Chip-Based Solution for Real-Time Image Dehazing
by
Dat Ngo and Bongsoon Kang
Symmetry 2024, 16(6), 653; https://doi.org/10.3390/sym16060653 (registering DOI) - 25 May 2024
Abstract
The acquisition of digital images is susceptible to haze, and images captured under such adverse conditions may impact high-level applications designed for clean input data. Image dehazing emerges as a practical solution to this problem, as it can be employed to pre-process images
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The acquisition of digital images is susceptible to haze, and images captured under such adverse conditions may impact high-level applications designed for clean input data. Image dehazing emerges as a practical solution to this problem, as it can be employed to pre-process images immediately after acquisition. This paper presents a concise review of impactful algorithms, including those based on deep learning models, to identify the existing gap in real-time processing capabilities. Subsequently, a real-time dehazing system on a multiprocessor system-on-a-chip (MPSoC) platform is introduced to bridge this gap. The proposed system balances the trade-off between dehazing performance and computational complexity; hence, the name “Symmetric” is coined. Additionally, the entire system is implemented in programmable logic and wrapped by an interface circuit supporting double-buffering, rendering it highly suitable for seamless integration into existing camera systems. Implementation results on a Zynq UltraScale+ MPSoC ZCU106 Evaluation Kit demonstrate a maximum operating frequency of 356.51 MHz, equivalent to a maximum processing speed of 40.27 frames per second for DCI 4K resolution.
Full article
(This article belongs to the Special Issue Symmetry in Process Optimization)
Open AccessArticle
Critical Information Mining Network: Identifying Crop Diseases in Noisy Environments
by
Yi Shao, Wenzhong Yang, Zhifeng Lu, Haokun Geng and Danny Chen
Symmetry 2024, 16(6), 652; https://doi.org/10.3390/sym16060652 - 24 May 2024
Abstract
When agricultural experts explore the use of artificial intelligence technology to identify and detect crop diseases, they mainly focus on the research of a stable environment, but ignore the problem of noise in the process of image acquisition in real situations. To solve
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When agricultural experts explore the use of artificial intelligence technology to identify and detect crop diseases, they mainly focus on the research of a stable environment, but ignore the problem of noise in the process of image acquisition in real situations. To solve this problem, we propose an innovative solution called the Critical Information Mining Network (CIMNet). Compared with traditional models, CIMNet has higher recognition accuracy and wider application scenarios. The network has a good effect on crop disease recognition under noisy environments, and can effectively deal with the interference of noise to the recognition effect in actual farmland scenes. Consider that the shape of the leaves can be symmetrical or asymmetrical.First, we introduce the Non-Local Attention Module (Non-Local), which uses a unique self-attention mechanism to fully capture the context information of the image. The module overcomes the limitation of traditional convolutional neural networks that only rely on local features and ignore global features. Global features are particularly important when the image is disturbed by noise. Non-Local improves a more comprehensive visual understanding of crop disease recognition. Secondly, we have innovatively designed a Multi-scale Critical Information Fusion Module (MSCM). The module uses the Key Information Extraction Module (KIB) to dig into the shallow key features in the network deeply. The shallow key features strengthen the feature perception of the model to the noise image through texture and contour information, and then the shallow key features and deep features are fused to enrich the original deep feature information of the network. Finally, we conducted experiments on two public datasets, and the results showed that the accuracy of our model in crop disease identification under a noisy environment was significantly improved. At the same time, our model also showed excellent performance under stable conditions. The results of this study provide favorable support for the improvement of crop production efficiency.
Full article
(This article belongs to the Special Issue Symmetry in Image Processing: Novel Topics and Advancements)
Open AccessArticle
Numerical Study on Aerodynamic Noise Reduction in Passenger Car with Fender Shape Optimization
by
Dongqi Jiao, Haichao Zhou, Tinghui Huang and Wei Zhang
Symmetry 2024, 16(6), 651; https://doi.org/10.3390/sym16060651 - 24 May 2024
Abstract
Despite the rapid development of vehicle intelligent technology, the aerodynamic noise problem of internal combustion engine vehicles and pure electric vehicles at high speed has always been a growing problem. In this study, the effects of the car body fender shape on the
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Despite the rapid development of vehicle intelligent technology, the aerodynamic noise problem of internal combustion engine vehicles and pure electric vehicles at high speed has always been a growing problem. In this study, the effects of the car body fender shape on the aerodynamic noises of the rearview mirror and wheel region were investigated, and a noise reduction method was also proposed by optimizing the fender shape. To realize the parametric modeling of the fender, five positional variables were selected to define the fender configuration; the free-form deformation (FFD) method was used to establish the response fender model according the DOE schemes, and computational fluid dynamics (CFD) simulations are used to obtain the noise results. Then, with the help of the radial basis function (RBF) model and the adaptive simulated annealing (ASA) algorithm, the aerodynamic shape of the fender was optimized to reduce aerodynamic noise. Comparative analysis was then employed to assess flow field characteristics of the optimized model against the original model and elucidate the fender configuration’s contribution to aerodynamic noise reduction and its realization mechanism.
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(This article belongs to the Section Engineering and Materials)
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Open AccessArticle
Numerical Simulation Study Considering Discontinuous Longitudinal Joints in Soft Soil under Symmetric Loading
by
Xianwei He, Xiangyang Xu and Hao Yang
Symmetry 2024, 16(6), 650; https://doi.org/10.3390/sym16060650 - 24 May 2024
Abstract
In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly
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In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 , the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness.
Full article
(This article belongs to the Special Issue Symmetry, Finite Element Analysis, and Intelligent Sensing and Monitoring: Applications in Engineering)
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Open AccessArticle
Evaluation of Classification Performance of New Layered Convolutional Neural Network Architecture on Offline Handwritten Signature Images
by
Yasin Ozkan and Pakize Erdogmus
Symmetry 2024, 16(6), 649; https://doi.org/10.3390/sym16060649 - 23 May 2024
Abstract
While there are many verification studies on signature images using deep learning algorithms in the literature, there is a lack of studies on the classification of signature images. Signatures are used as a means of identification for banking, security controls, symmetry, certificates, and
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While there are many verification studies on signature images using deep learning algorithms in the literature, there is a lack of studies on the classification of signature images. Signatures are used as a means of identification for banking, security controls, symmetry, certificates, and contracts. In this study, the aim was to design network architectures that work very fast in areas that require only signature images. For this purpose, a new Si-CNN network architecture with existing layers was designed. Afterwards, a new loss function and layer (Si-CL), a novel architecture using Si-CL as classification layer in Si-CNN to increase the performance of this architecture, was designed. This architecture was called Si-CNN+NC (New Classification). Si-CNN and Si-CNN+NC were trained with two datasets. The first dataset which was used for training is the “C-Signatures” (Classification Signatures) dataset, which was created to test these networks. The second dataset is the “Cedar” dataset, which is a benchmark dataset. The number of classes and sample numbers in the two datasets are symmetrical with each other. To compare the performance of the trained networks, four of the most well-known pre-trained networks, GoogleNet, DenseNet201, Inceptionv3, and ResNet50, were also trained with the two datasets with transfer learning. The findings of the study showed that the proposed network models can learn features from two different handwritten signature images and achieve higher accuracy than other benchmark models. The test success of the trained networks showed that the Si-CNN+NC network outperforms the others, in terms of both accuracy and speed. Finally, Si-CNN and Si-CNN+NC networks were trained with the gold standard dataset MNIST and showed superior performance. Due to its superior performance, Si-CNN and Si-CNN+NC can be used by signature experts as an aid in a variety of applications, including criminal detection and forgery.
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(This article belongs to the Special Issue Symmetry/Asymmetry in Neural Networks)
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Open AccessArticle
The Schwarzian Approach in Sturm–Liouville Problems
by
Nektarios Vlahakis
Symmetry 2024, 16(6), 648; https://doi.org/10.3390/sym16060648 - 23 May 2024
Abstract
A novel method for finding the eigenvalues of a Sturm–Liouville problem is developed. Following the minimalist approach, the problem is transformed to a single first-order differential equation with appropriate boundary conditions. Although the resulting equation is nonlinear, its form allows us to find
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A novel method for finding the eigenvalues of a Sturm–Liouville problem is developed. Following the minimalist approach, the problem is transformed to a single first-order differential equation with appropriate boundary conditions. Although the resulting equation is nonlinear, its form allows us to find the general solution by adding a second part to a particular solution. This splitting of the general solution into two parts involves the Schwarzian derivative: hence, the name of the approach. The eigenvalues that correspond to acceptable solutions can be found by requiring the second part to correct the asymptotically diverging behavior of the particular solution. The method can be applied to many different areas of physics, such as the Schrödinger equation in quantum mechanics and stability problems in fluid dynamics. Examples are presented.
Full article
(This article belongs to the Special Issue Feature Papers in 'Physics' Section 2024)
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Open AccessArticle
Inequalities for the Euclidean Operator Radius of n-Tuple Operators and Operator Matrices in Hilbert C∗-Modules
by
Mohammad H. M. Rashid and Wael Mahmoud Mohammad Salameh
Symmetry 2024, 16(6), 647; https://doi.org/10.3390/sym16060647 - 23 May 2024
Abstract
This study takes a detailed look at various inequalities related to the Euclidean operator radius. It examines groups of n-tuple operators, studying how they add up and multiply together. It also uncovers a unique power inequality specific to the Euclidean operator radius.
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This study takes a detailed look at various inequalities related to the Euclidean operator radius. It examines groups of n-tuple operators, studying how they add up and multiply together. It also uncovers a unique power inequality specific to the Euclidean operator radius. The research broadens its scope to analyze how n-tuple operators, when used as parts of operator matrices, illustrate inequalities connected to the Euclidean operator radius. By using the Euclidean numerical radius and Euclidean operator norm for n-tuple operators, the study introduces a range of new inequalities. These inequalities not only set limits for the addition, multiplication, and Euclidean numerical radius of n-tuple operators but also help in establishing inequalities for the Euclidean operator radius. This process involves carefully examining the Euclidean numerical radius inequalities of operator matrices with n-tuple operators. Additionally, a new inequality is derived, focusing specifically on the Euclidean operator norm of operator matrices. Throughout, the research keeps circling back to the idea of finding and understanding symmetries in linear operators and matrices. The paper highlights the significance of symmetry in mathematics and its impact on various mathematical areas.
Full article
(This article belongs to the Section Mathematics)
Open AccessArticle
A Novel Self-Adaptive Deformable Convolution-Based U-Net for Low-Light Image Denoising
by
Hua Wang, Jianzhong Cao, Huinan Guo and Cheng Li
Symmetry 2024, 16(6), 646; https://doi.org/10.3390/sym16060646 - 23 May 2024
Abstract
Capturing images under extremely low-light conditions usually suffers from various types of noise due to the limited photon and low signal-to-noise ratio (SNR), which makes low-light denoising a challenging task in the field of imaging technology. Nevertheless, existing methods primarily focus on investigating
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Capturing images under extremely low-light conditions usually suffers from various types of noise due to the limited photon and low signal-to-noise ratio (SNR), which makes low-light denoising a challenging task in the field of imaging technology. Nevertheless, existing methods primarily focus on investigating the precise modeling of real noise distributions while neglecting improvements in the noise modeling capabilities of learning models. To address this situation, a novel self-adaptive deformable-convolution-based U-Net (SD-UNet) model is proposed in this paper. Firstly, deformable convolution is employed to tackle noise patterns with different geometries, thus extracting more reliable noise representations. After that, a self-adaptive learning block is proposed to enable the network to automatically select appropriate learning branches for noise with different scales. Finally, a novel structural loss function is leveraged to evaluate the difference between denoised and clean images. The experimental results on multiple public datasets validate the effectiveness of the proposed method.
Full article
(This article belongs to the Special Issue Advances in Image Processing with Symmetry/Asymmetry)
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Open AccessArticle
Improvement and Application of Hale’s Dynamic Time Warping Algorithm
by
Hairong Wang and Qiufang Zheng
Symmetry 2024, 16(6), 645; https://doi.org/10.3390/sym16060645 - 23 May 2024
Abstract
Due to the different generation and propagation mechanisms of P- and S-waves, there may be significant differences in the seismic data collected by the two, which poses a great obstacle to the time domain matching of P- and S-waves in multiwave exploration. Furthermore,
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Due to the different generation and propagation mechanisms of P- and S-waves, there may be significant differences in the seismic data collected by the two, which poses a great obstacle to the time domain matching of P- and S-waves in multiwave exploration. Furthermore, the quality and accuracy of the matching effect will directly affect the subsequent multiwave joint inversion and interpretation effect. Therefore, the study of P and S-wave-matching methods plays a crucial role in seismic exploration. In 2013, Hale improved the classical Dynamic Time Warping (DTW) algorithm applied to solve the problem of speech recognition, and obtained the DTW algorithm suitable for solving the matching of P-waves and S-waves. The seismic wave-matching results generated by this algorithm are horizontal discontinuous (different trajectories) and need further processing. This study analyses the algorithm based on simulations of seismic waves using Ricker wavelets. In response to existing problems, this paper proposes strategies to improve the DTW algorithm. The algorithm in this study significantly improved the continuity of the registration results of the actual seismic wave data in the horizontal direction (different traces).
Full article
(This article belongs to the Special Issue Advanced Symmetry Methods for Dynamics, Control, Optimization and Applications in 2023)
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Open AccessRetraction
RETRACTED: Lin et al. A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation. Symmetry 2023, 15, 219
by
Yun Lin, Yi Tang, Yanfei Zhu, Fangbin Song and Wenzhe Tang
Symmetry 2024, 16(6), 644; https://doi.org/10.3390/sym16060644 - 23 May 2024
Abstract
The Symmetry Editorial Office retracts the article titled “A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation” [...]
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Open AccessArticle
Estimation of the Domain of Attraction on Controlled Nonlinear Neutral Complex Networks via Razumikhin Approach
by
Hong Yu and Yinfang Song
Symmetry 2024, 16(6), 643; https://doi.org/10.3390/sym16060643 - 22 May 2024
Abstract
This paper is devoted to dealing with the issue of the estimation of the domain of attraction (DOA) for highly nonlinear neutral complex networks (HNNCNs) with time delays. Firstly, by the Razumikhin approach, we establish several novel lemmas on the estimation of DOA
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This paper is devoted to dealing with the issue of the estimation of the domain of attraction (DOA) for highly nonlinear neutral complex networks (HNNCNs) with time delays. Firstly, by the Razumikhin approach, we establish several novel lemmas on the estimation of DOA for highly nonlinear neutral differential systems. The cases of bounded non-differentiable delays and unbounded proportional delays are discussed, respectively. Subsequently, by utilizing the proposed lemmas, combining the Lyapunov stability theory and inequality technique, the estimation of DOA on HNNCNs with bounded delays or proportional delays is derived when the chosen control gain is sufficiently large. If initial values start from DOA, then the states of systems will exponentially or polynomially converge to the equilibrium point, which means that the local exponential or polynomial synchronization of HNNCNs is realized. Additionally, the weighted outer-coupling matrix of complex networks is not required to be symmetric, which means that the derived results can be applied to both the undirected networks and directed networks. Finally, several numerical examples are provided to illustrate the feasibility of theoretical findings.
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(This article belongs to the Section Mathematics)
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Open AccessArticle
Mean-Field Stochastic Linear Quadratic Optimal Control for Jump-Diffusion Systems with Hybrid Disturbances
by
Chao Tang, Xueqin Li and Qi Wang
Symmetry 2024, 16(6), 642; https://doi.org/10.3390/sym16060642 - 22 May 2024
Abstract
A mean-field linear quadratic stochastic (MF-SLQ for short) optimal control problem with hybrid disturbances and cross terms in a finite horizon is concerned. The state equation is a systems driven by the Wiener process and the Poisson random martingale measure disturbed by some
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A mean-field linear quadratic stochastic (MF-SLQ for short) optimal control problem with hybrid disturbances and cross terms in a finite horizon is concerned. The state equation is a systems driven by the Wiener process and the Poisson random martingale measure disturbed by some stochastic perturbations. The cost functional is also disturbed, which means more general cases could be characterized, especially when extra environment perturbations exist. In this paper, the well-posedness result on the jump diffusion systems is obtained by the fixed point theorem and also the solvability of the MF-SLQ problem. Actually, by virtue of adjoint variables, classic variational calculus, and some dual representation, an optimal condition is derived. Throughout our research, in order to connect the optimal control and the state directly, two Riccati differential equations, a BSDE with random jumps and an ordinary equation (ODE for short) on disturbance terms are obtained by a decoupling technique, which provide an optimal feedback regulator. Meanwhile, the relationship between the two Riccati equations and the so-called mean-field stochastic Hamilton system is established. Consequently, the optimal value is characterized by the initial state, disturbances, and original value of the Riccati equations. Finally, an example is provided to illustrate our theoretic results.
Full article
(This article belongs to the Section Engineering and Materials)
Open AccessArticle
An Adaptive Search Algorithm for Multiplicity Dynamic Flexible Job Shop Scheduling with New Order Arrivals
by
Linshan Ding, Zailin Guan, Dan Luo, Mudassar Rauf and Weikang Fang
Symmetry 2024, 16(6), 641; https://doi.org/10.3390/sym16060641 - 22 May 2024
Abstract
In today’s customer-centric economy, the demand for personalized products has compelled corporations to develop manufacturing processes that are more flexible, efficient, and cost-effective. Flexible job shops offer organizations the agility and cost-efficiency that traditional manufacturing processes lack. However, the dynamics of modern manufacturing,
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In today’s customer-centric economy, the demand for personalized products has compelled corporations to develop manufacturing processes that are more flexible, efficient, and cost-effective. Flexible job shops offer organizations the agility and cost-efficiency that traditional manufacturing processes lack. However, the dynamics of modern manufacturing, including machine breakdown and new order arrivals, introduce unpredictability and complexity. This study investigates the multiplicity dynamic flexible job shop scheduling problem (MDFJSP) with new order arrivals. To address this problem, we incorporate the fluid model to propose a fluid randomized adaptive search (FRAS) algorithm, comprising a construction phase and a local search phase. Firstly, in the construction phase, a fluid construction heuristic with an online fluid dynamic tracking policy generates high-quality initial solutions. Secondly, in the local search phase, we employ an improved tabu search procedure to enhance search efficiency in the solution space, incorporating symmetry considerations. The results of the numerical experiments demonstrate the superior effectiveness of the FRAS algorithm in solving the MDFJSP when compared to other algorithms. Specifically, the proposed algorithm demonstrates a superior quality of solution relative to existing algorithms, with an average improvement of 29.90%; and exhibits an acceleration in solution speed, with an average increase of 1.95%.
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(This article belongs to the Special Issue Symmetry in Computing Algorithms and Applications)
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Open AccessArticle
Nonlinear Transport through Parity–Time Symmetric Lattice Potentials
by
Wei Mao and Yongping Zhang
Symmetry 2024, 16(6), 640; https://doi.org/10.3390/sym16060640 - 22 May 2024
Abstract
We study nonlinear transports of a light field through finite parity–time symmetric lattice potentials. The initial light field is trapped in a source reservoir and is released to expand toward the lattice potentials along the transverse direction due to the nonlinearity. We identify
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We study nonlinear transports of a light field through finite parity–time symmetric lattice potentials. The initial light field is trapped in a source reservoir and is released to expand toward the lattice potentials along the transverse direction due to the nonlinearity. We identify the transports that can be classified into in-band and in-gap transports. In the in-band transport, the light field can tunnel through the lattices into the sink reservoir, and in the in-gap transport, the light field is self-trapped inside the lattices to form a solitary wave.
Full article
(This article belongs to the Special Issue Symmetry-Related Quantum Phases in Exciton-Polariton Condensates)
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Open AccessArticle
An Online Review-Driven Picture Fuzzy Multi-Criteria Group Decision-Making Approach for Evaluating the Online Medical Service Quality of Doctors
by
Kaiwen Shi and Juanjuan Peng
Symmetry 2024, 16(6), 639; https://doi.org/10.3390/sym16060639 - 21 May 2024
Abstract
In order to further investigate the level of online medical services in China and improve the medical experience of patients, this study aims to establish an online review-driven picture fuzzy multi-criteria group decision-making (MCGDM) approach for the online medical service evaluation of doctors.
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In order to further investigate the level of online medical services in China and improve the medical experience of patients, this study aims to establish an online review-driven picture fuzzy multi-criteria group decision-making (MCGDM) approach for the online medical service evaluation of doctors. First, based on the Aczel–Alsina t-norm and t-conorm, the normal picture fuzzy Aczel–Alsina operations involving a variable parameter are defined to make the corresponding operations more flexible than other operations. Second, two picture fuzzy Aczel–Alsina aggregation operators are developed, and the corresponding properties are discussed as well. Third, combined with the online review information of China’s medical platform Haodaifu, the online review-driven evaluation attributes and their corresponding weights are obtained, which can make the evaluation model more objective. Fourth, an extended normal picture fuzzy complex proportional assessment (COPRAS) decision-making method for the service quality evaluation of online medical services is proposed. Finally, an empirical example is presented to verify the feasibility and validity of the proposed method. A sensitivity analysis and a comparison analysis are also conducted to demonstrate the effectiveness and flexibility of the proposed approach.
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(This article belongs to the Special Issue Fuzzy Set Theory and Uncertainty Theory—Volume III)
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Open AccessArticle
Strange Things in Bottom-to-Strange Decays: The Standard Model Turned Upside Down?
by
Martin Andersson, Alexander Mclean Marshall, Konstantinos A. Petridis and Eluned Smith
Symmetry 2024, 16(6), 638; https://doi.org/10.3390/sym16060638 - 21 May 2024
Abstract
The flavour anomalies are a set of experimental deviations from the Standard Model (SM) predictions in several observables involving decays of bottom quarks. In particular, tensions between theory and experiment in measurements involving a bottom quark decaying into a strange quark and a
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The flavour anomalies are a set of experimental deviations from the Standard Model (SM) predictions in several observables involving decays of bottom quarks. In particular, tensions between theory and experiment in measurements involving a bottom quark decaying into a strange quark and a pair of muons have motivated much theoretical work to explore possible new physics explanations. This review summarises the tumultuous evolution of these tensions, focusing on the most recent experimental results and their implications for physics beyond the SM. We also discuss the prospects for future measurements and tests of the flavour anomalies at the LHC and other facilities.
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(This article belongs to the Special Issue Symmetries and Anomalies in Flavour Physics)
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Open AccessArticle
A Necessary Optimality Condition on the Control of a Charged Particle
by
Nigar Yildirim Aksoy, Ercan Celik and Merve Zengin
Symmetry 2024, 16(6), 637; https://doi.org/10.3390/sym16060637 - 21 May 2024
Abstract
We consider an optimal control problem with the boundary functional for a Schrödinger equation describing the motion of a charged particle. By using the existence of an optimal solution, we search the necessary optimality conditions for the examined control problem. First, we constitute
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We consider an optimal control problem with the boundary functional for a Schrödinger equation describing the motion of a charged particle. By using the existence of an optimal solution, we search the necessary optimality conditions for the examined control problem. First, we constitute an adjoint problem by a Lagrange multiplier that is related to constraints of theory on symmetries and conservation laws. The adjoint problem obtained is a boundary value problem with a nonhomogeneous boundary condition. We prove the existence and uniqueness of the solution of the adjoint problem. Then, we demonstrate the differentiability of the objective functional in the sense of Frechet and get a formula for its gradient. Finally, we give a necessary optimality condition in the form of a variational inequality.
Full article
(This article belongs to the Special Issue Advanced Symmetry Methods for Dynamics, Control, Optimization and Applications in 2023)
Open AccessArticle
Real-Time Control of Sintering Moisture Based on Temporal Fusion Transformers
by
Xinping Chen, Jinyang Cheng, Ziyun Zhou, Xinyu Lu, Binghui Ye and Yushan Jiang
Symmetry 2024, 16(6), 636; https://doi.org/10.3390/sym16060636 - 21 May 2024
Abstract
The quality of sintered ore, which serves as the primary raw material for blast furnace ironmaking, is directly influenced by the moisture in the sintering mixture. In order to improve the precision of water addition in the sintering process, this paper proposes an
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The quality of sintered ore, which serves as the primary raw material for blast furnace ironmaking, is directly influenced by the moisture in the sintering mixture. In order to improve the precision of water addition in the sintering process, this paper proposes an intelligent model for predicting water-filling volume based on Temporal Fusion Transformer (TFT), whose symmetry enables it to effectively capture long-term dependencies in time series data. Utilizing historical sintering data to develop a prediction model for the amount of mixing and water addition, the results indicate that the TFT model can achieve the R squared of 0.9881, and the root mean square error (RMSE) of 3.5951. When compared to the transformer, long short-term memory (LSTM), and particle swarm optimization–long short-term memory (PSO-LSTM), it is evident that the TFT model outperforms the other models, improving the RMSE by 8.5403, 6.9852, and 0.453, respectively. As an application, the TFT model provides an effective interval reference for moisture control in normal sintering processes, which ensures that the error is within 1 t.
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(This article belongs to the Topic Intelligent Control in Smart Energy Systems)
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Topics
Topic in
Axioms, Computation, MCA, Mathematics, Symmetry
Mathematical Modeling
Topic Editors: Babak Shiri, Zahra AlijaniDeadline: 31 May 2024
Topic in
Algorithms, Axioms, Fractal Fract, Mathematics, Symmetry
Fractal and Design of Multipoint Iterative Methods for Nonlinear Problems
Topic Editors: Xiaofeng Wang, Fazlollah SoleymaniDeadline: 30 June 2024
Topic in
Algorithms, Future Internet, Information, Mathematics, Symmetry
Research on Data Mining of Electronic Health Records Using Deep Learning Methods
Topic Editors: Dawei Yang, Yu Zhu, Hongyi XinDeadline: 31 August 2024
Topic in
Algorithms, Computation, Mathematics, Molecules, Symmetry, Nanomaterials, Materials
Advances in Computational Materials Sciences
Topic Editors: Cuiying Jian, Aleksander CzekanskiDeadline: 30 September 2024
Conferences
Special Issues
Special Issue in
Symmetry
The Nuclear Physics of Neutron Stars
Guest Editor: Charalampos MoustakidisDeadline: 31 May 2024
Special Issue in
Symmetry
Time Series Forecasting in Physical Geography
Guest Editors: Babak Mohammadi, Mohammed AchiteDeadline: 15 June 2024
Special Issue in
Symmetry
Quantum Mechanics: Concepts, Symmetries, and Recent Developments
Guest Editor: Tuong Trong TruongDeadline: 30 June 2024
Special Issue in
Symmetry
Symmetry in Hamiltonian Dynamical Systems
Guest Editor: Fernando HaasDeadline: 15 July 2024