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Mathematics
Number of Followers: 3 Open Access journal ISSN (Online) 2227-7390 Published by MDPI [247 journals] |
- Mathematics, Vol. 11, Pages 502: A Particle Reinforced Gradient Honeycomb
Sandwich Panel for Broadband Sound Insulation
Authors: Geman Shi, Xiaoxun Wu, Renjie Jiang, Shande Li
First page: 502
Abstract: The sound insulation capacity of traditional sound insulation boards is limited by the law of mass, and any improvement in sound insulation capacity contradicts the demand for light weight. In order to overcome this shortcoming, a lightweight particle reinforced gradient honeycomb sandwich panel is proposed to achieve lightweight sound insulation. The sound insulation of the particle reinforced honeycomb sandwich panel is calculated based on the transfer matrix method. The accuracy of the theory is verified through finite element simulation, and the influence of material and structural parameters on the sound insulation performance of the sandwich panel is analyzed. The results show that the sound insulation of the honeycomb sandwich panel can be significantly improved by adding reinforcement particles to the aluminum matrix, and the sound insulation also increases as the particle mass fraction of the reinforcement increases. In addition, the valley value of the sound insulation curve moves towards the low frequency direction, which indicates that the sound insulation performance of the sandwich plate at low frequencies is effectively improved.
Citation: Mathematics
PubDate: 2023-01-17
DOI: 10.3390/math11030502
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 503: Linear Diophantine Fuzzy Subspaces of a
Vector Space
Authors: Madeleine Al-Tahan, Sarka Hoskova-Mayerova, Saba Al-Kaseasbeh, Suha Ali Tahhan
First page: 503
Abstract: The notion of a linear diophantine fuzzy set as a generalization of a fuzzy set is a mathematical approach that deals with vagueness in decision-making problems. The use of reference parameters associated with validity and non-validity functions in linear diophantine fuzzy sets makes it more applicable to model vagueness in many real-life problems. On the other hand, subspaces of vector spaces are of great importance in many fields of science. The aim of this paper is to combine the two notions. In this regard, we consider the linear diophantine fuzzification of a vector space by introducing and studying the linear diophantine fuzzy subspaces of a vector space. First, we studied the behaviors of linear diophantine fuzzy subspaces of a vector space under a linear diophantine fuzzy set. Second, and by means of the level sets, we found a relationship between the linear diophantine fuzzy subspaces of a vector space and the subspaces of a vector space. Finally, we discuss the linear diophantine fuzzy subspaces of a quotient vector space.
Citation: Mathematics
PubDate: 2023-01-17
DOI: 10.3390/math11030503
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 504: Modeling the Impact of Overcoming the
Green Walls Implementation Barriers on Sustainable Building Projects: A
Novel Mathematical Partial Least Squares—SEM Method
Authors: Ahmed Farouk Kineber, Ayodeji Emmanuel Oke, Mohammed Magdy Hamed, Ehab Farouk Rached, Ali Elmansoury
First page: 504
Abstract: The sustainable building concept must be implemented throughout the project lifecycle to achieve the highest proceeds without lowering the standard. Although implementing green walls in emerging nations is partial, such studies have concentrated on drivers for implementing green walls. Conversely, there is less proof to comprehensively study the impact of implementing green walls’ overall sustainable success (OSS) concerning the lifecycle of projects. This research focuses on the green wall adoption barriers in construction projects in third-world nations. It assesses the effect of addressing green wall (GW) adoption obstacles on OSS throughout the project lifespan. Therefore, a broader review of the literature is needed for conceptual model development. Structural equation modelling and partial least square (SEM-PLS) have been developed employing a survey evaluation tool (i.e., questionnaire). Information was derived from one hundred and five building professionals in Nigeria. The model output revealed that eradicating GWs barriers had a slight to intermediate influence on OSS during the construction scheme’s lifespan. These results offer the foundation for policymaking in third-world nations regarding successful project completion through evading barriers to green wall adoption. Similarly, green walls implementation will enhance the building project’s success.
Citation: Mathematics
PubDate: 2023-01-17
DOI: 10.3390/math11030504
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 505: A New Insight into Entropy Based on the
Fuzzy Operators, Applied to Useful Information Extraction from Noisy
Time-Frequency Distributions
Authors: József Dombi, Ana Vranković Lacković, Jonatan Lerga
First page: 505
Abstract: In this paper, we study the connections between generalized mean operators and entropies, where the mean value operators are related to the strictly monotone logical operators of fuzzy theory. Here, we propose a new entropy measure based on the family of generalized Dombi operators. Namely, this measure is obtained by using the Dombi operator as a generator function in the general solution of the bisymmetric functional equation. We show how the proposed entropy can be used in a fuzzy system where the performance is consistent in choosing the best alternative in the Multiple Attribute Decision-Making Problem. This newly defined entropy was also applied to the problem of extracting useful information from time-frequency representations of noisy, nonstationary, and multicomponent signals. The denoising results were compared to Shannon and Rényi entropies. The proposed entropy measure is shown to significantly outperform the competing ones in terms of denoising classification accuracy and the F1-score due to its sensitivity to small changes in the probability distribution.
Citation: Mathematics
PubDate: 2023-01-17
DOI: 10.3390/math11030505
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 506: Three Mathematical Models for COVID-19
Prediction
Authors: Martínez-Fernández, Fernández-Muñiz, Cernea, Fernández-Martínez, Kloczkowski
First page: 506
Abstract: The COVID-19 outbreak was a major event that greatly impacted the economy and the health systems around the world. Understanding the behavior of the virus and being able to perform long-term and short-term future predictions of the daily new cases is a working field for machine learning methods and mathematical models. This paper compares Verhulst’s, Gompertz´s, and SIR models from the point of view of their efficiency to describe the behavior of COVID-19 in Spain. These mathematical models are used to predict the future of the pandemic by first solving the corresponding inverse problems to identify the model parameters in each wave separately, using as observed data the daily cases in the past. The posterior distributions of the model parameters are then inferred via the Metropolis–Hastings algorithm, comparing the robustness of each prediction model and making different representations to visualize the results obtained concerning the posterior distribution of the model parameters and their predictions. The knowledge acquired is used to perform predictions about the evolution of both the daily number of infected cases and the total number of cases during each wave. As a main conclusion, predictive models are incomplete without a corresponding uncertainty analysis of the corresponding inverse problem. The invariance of the output (posterior prediction) with respect to the forward predictive model that is used shows that the methodology shown in this paper can be used to adopt decisions in real practice (public health).
Citation: Mathematics
PubDate: 2023-01-17
DOI: 10.3390/math11030506
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 507: A Bimodal Extension of the
Epsilon-Skew-Normal Model
Authors: Juan Duarte, Guillermo Martínez-Flórez, Diego Ignacio Gallardo, Osvaldo Venegas, Héctor W. Gómez
First page: 507
Abstract: This article introduces a bimodal model based on the epsilon-skew-normal distribution. This extension generates bimodal distributions similar to those produced by the mixture of normal distributions. We study the basic properties of this new family. We apply maximum likelihood estimators, calculate the information matrix and present a simulation study to assess parameter recovery. Finally, we illustrate the results to three real data sets, suggesting this new distribution as a plausible alternative for modelling bimodal data.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030507
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 508: It’s All in the Embedding! Fake
News Detection Using Document Embeddings
Authors: Ciprian-Octavian Truică, Elena-Simona Apostol
First page: 508
Abstract: With the current shift in the mass media landscape from journalistic rigor to social media, personalized social media is becoming the new norm. Although the digitalization progress of the media brings many advantages, it also increases the risk of spreading disinformation, misinformation, and malformation through the use of fake news. The emergence of this harmful phenomenon has managed to polarize society and manipulate public opinion on particular topics, e.g., elections, vaccinations, etc. Such information propagated on social media can distort public perceptions and generate social unrest while lacking the rigor of traditional journalism. Natural Language Processing and Machine Learning techniques are essential for developing efficient tools that can detect fake news. Models that use the context of textual data are essential for resolving the fake news detection problem, as they manage to encode linguistic features within the vector representation of words. In this paper, we propose a new approach that uses document embeddings to build multiple models that accurately label news articles as reliable or fake. We also present a benchmark on different architectures that detect fake news using binary or multi-labeled classification. We evaluated the models on five large news corpora using accuracy, precision, and recall. We obtained better results than more complex state-of-the-art Deep Neural Network models. We observe that the most important factor for obtaining high accuracy is the document encoding, not the classification model's complexity.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030508
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 509: Gated Recurrent Fuzzy Neural Network
Sliding Mode Control of a Micro Gyroscope
Authors: Jiapeng Xie, Juntao Fei, Cuicui An
First page: 509
Abstract: This paper proposes a non-singular fast terminal sliding mode control (NFTSMC) method for micro gyroscopes with unknown uncertainty based on gated recurrent fuzzy neural networks (GRFNNs). First, taking advantage of non-singular fast terminal sliding control, a sliding hyperplane is designed with a nonlinear function to ensure that the tracking error of the system converges to zero within a specified finite time. Then, the unknown model parameters of the micro gyroscope are estimated using a GRFNN. Since the GRFNN can adaptively adjust the base width, center vector, gated recurrent unit parameters, and outer gains, it can achieve accurate approximation to unknown models, enhancing the robustness and accuracy. In addition, due to the introduction of gated recurrent units, The GRFNN can effectively utilize the previous data and avoid the problem of gradient disappearance. The comparison of the simulation results with traditional neural sliding mode control shows that the proposed method can achieve better tracking performance and more accurate estimation of unknown models.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030509
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 510: Lagrangian Heuristic for Multi-Depot
Technician Planning of Product Distribution and Installation with a Lunch
Break
Authors: Fangzhou Yan, Huaxin Qiu, Dongya Han
First page: 510
Abstract: In this paper, we consider a technician planning scheme stemming from product distribution and installation in a manufacturing enterprise that considers factors such as soft time windows, skill areas, lunch breaks, and outsourcing options, among others. The goal is to identify the optimal partition of technicians into groups and assignment of customers to technician groups and find the optimal routes for technician groups to minimize the sum of the travel cost, soft time window violation cost, and outsourcing cost. To address this problem, the study develops a tailored Lagrangian heuristic that incorporates several strategies to speed up convergence and produce sharper bounds. Computational comparisons between the developed heuristic and MIP solver are presented. The results reveal that the bounds found by the developed algorithm outperform those found by CPLEX for large instances, and it is capable of identifying high-quality feasible solutions to large-scale problems.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030510
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 511: A Novel Hybrid Approach for Evaluation of
Resilient 4PL Provider for E-Commerce
Authors: Vukašin Pajić, Milorad Kilibarda, Milan Andrejić
First page: 511
Abstract: Today, e-commerce allows consumers access to a wide range of products on the global market, quick and convenient selection, purchase, ordering, and payment of products. Consumers expect to receive the products they bought online, very quickly, at favorable prices and delivery conditions. However, it is often not possible, because global supply chains are realized over large geographical distances, with a whole range of disruptions and challenges that need to be successfully overcome. With the aim of efficiently delivering products and meeting consumer expectations, retailers often leave this job to specialized and resilient logistics companies better known as fourth-party logistics (4PL) providers. On this occasion, it is necessary to conduct a very thorough evaluation of the logistics provider based on appropriate scientific approaches and models. In this paper, a new hybrid approach for the evaluation of resilient 4PLs was proposed, with the aim of providing appropriate support for the decision-making system on product delivery in e-commerce. The hybrid approach is based on the fuzzy full consistency method (FUCOM), evidence theory (ET), rule-based transformation (RBT), and weighted aggregated sum product assessment (WASPAS) methods. The proposed model was tested and applied to an example of an online retailer, which sells and delivers products originating from China and the countries of the Far East to the market of the Western Balkans and Southeastern Europe. Five 4PL providers were evaluated and ranked according to 10 criteria. According to the results, the most important criterion was IT capabilities, while the least important was cooperation. Additionally, sensitivity analysis was carried out to determine whether the final ranking will change. The obtained results showed that the proposed methodology represents a valuable decision support tool that can be used for solving not only the problem described in this paper but also similar problems.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030511
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 512: Dynamic Game Analysis on Cooperative
Advertising Strategy in a Manufacturer-Led Supply Chain with Risk Aversion
Authors: Jia Liu, Cuixia Li
First page: 512
Abstract: This paper considers a dynamic Stackelberg game model for a manufacturer-led supply chain with risk aversion. Cooperative advertising strategy is applied to the marketing decisions of supply chain participants. Based on Stackelberg game and system dynamic theory, the game and complex dynamical behaviors are studied through the use of several methods, such as the stability region of the system, bifurcation diagram, attractor diagram, and the largest Lyapunov exponent diagram. The expected utilities of participants are given and compared by numerical simulation. The results illustrate that a series of variations in adjustment speed of advertising expenditure, participation rate of local advertising expenditure by manufacturer, risk tolerance levels, and the effect coefficient of advertising expenditure may cause a loss of stability to the system and evolve into chaos. Meanwhile, the Nash equilibrium point and the expected utility of the manufacturer and retailer will change greatly. The parameter control method is further applied to control the chaos phenomenon of the system effectively. By means of analyzing the impact of relevant factors on the game model, the manufacturer and retailer can make optimal strategy decisions in the supply chain competition. The findings of this study mainly include the following three aspects. Firstly, for market stability and maximizing revenue, the manufacturer adjusts the participation rate appropriately, avoiding too high or too low values. Secondly, the manufacturer will try to reduce their own risk tolerance level for the economic revenue, and the retailer appropriately adjust the risk tolerance level to adapt to their own development according to their own enterprise strategy. Finally, both the manufacturer and retailer reduce their own effect coefficients of advertising expenditure. Meanwhile, they will attempt to increase their opponent’s effect coefficient to gain the most revenue. The research results of this study can provide important reference for the advertising expenditure decision and revenue maximization of participants in the context of risk aversion.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030512
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 513: Performance Evaluation of a Cloud
Datacenter Using CPU Utilization Data
Authors: Chen Li, Junjun Zheng, Hiroyuki Okamura, Tadashi Dohi
First page: 513
Abstract: Cloud computing and its associated virtualization have already been the most vital architectures in the current computer system design. Due to the popularity and progress of cloud computing in different organizations, performance evaluation of cloud computing is particularly significant, which helps computer designers make plans for the system’s capacity. This paper aims to evaluate the performance of a cloud datacenter Bitbrains, using a queueing model only from CPU utilization data. More precisely, a simple but non-trivial queueing model is used to represent the task processing of each virtual machine (VM) in the cloud, where the input stream is supposed to follow a non-homogeneous Poisson process (NHPP). Then, the parameters of arrival streams for each VM in the cloud are estimated. Furthermore, the superposition of estimated arrivals is applied to represent the CPU behavior of an integrated virtual platform. Finally, the performance of the integrated virtual platform is evaluated based on the superposition of the estimations.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030513
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 514: A Novel Context-Aware Reliable Routing
Protocol and SVM Implementation in Vehicular Area Networks
Authors: Manoj Sindhwani, Shippu Sachdeva, Akhil Gupta, Sudeep Tanwar, Fayez Alqahtani, Amr Tolba, Maria Simona Raboaca
First page: 514
Abstract: The Vehicular Ad-hoc Network (VANET) is an innovative technology that allows vehicles to connect with neighboring roadside structures to deliver intelligent transportation applications. To deliver safe communication among vehicles, a reliable routing approach is required. Due to the excessive mobility and frequent variation in network topology, establishing a reliable routing for VANETs takes a lot of work. In VANETs, transmission links are extremely susceptible to interruption; as a result, the routing efficiency of these constantly evolving networks requires special attention. To promote reliable routing in VANETs, we propose a novel context-aware reliable routing protocol that integrates k-means clustering and support vector machine (SVM) in this paper. The k-means clustering divides the routes into two clusters named GOOD and BAD. The cluster with high mean square error (MSE) is labelled as BAD, and the cluster with low MSE is labelled as GOOD. After training the routing data with SVM, the performance of each route from source to target is improved in terms of Packet Delivery Ratio (PDR), throughput, and End to End Delay (E2E). The proposed protocol will achieve improved routing efficiency with these changes.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030514
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 515: Sperm Abnormality Detection Using
Sequential Deep Neural Network
Authors: Suleman Shahzad, Muhammad Ilyas, M. Ikram Ullah Lali, Hafiz Tayyab Rauf, Seifedine Kadry, Emad Abouel Nasr
First page: 515
Abstract: Sperm morphological analysis (SMA) is an essential step in diagnosing male infertility. Using images of human sperm cells, this research proposes a unique sequential deep-learning method to detect abnormalities in semen samples. The proposed technique identifies and examines several components of human sperm. In order to conduct this study, we used the online Modified Human Sperm Morphology Analysis (MHSMA) dataset containing 1540 sperm images collected from 235 infertile individuals. For research purposes, this dataset is freely available online. To identify morphological abnormalities in different parts of human sperm, such as the head, vacuole, and acrosome, we proposed sequential deep neural network (SDNN) architecture. This technique is also particularly effective with low-resolution, unstained images. Sequential deep neural networks (SDNNs) demonstrate high accuracy in diagnosing morphological abnormalities based on the given dataset in our tests on the benchmark. Our proposed algorithm successfully detected abnormalities in the acrosome, head, and vacuole with an accuracy of 89%, 90%, and 92%, respectively. It is noteworthy that our system detects abnormalities of the acrosome and head with greater accuracy than current state-of-the-art approaches on the suggested benchmark. On a low-specification computer/laptop, our algorithm also requires less execution time. Additionally, it can classify photos in real time. Based on the results of our study, an embryologist can quickly decide whether to use the given sperm.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030515
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 516: Reductions and Exact Solutions of
Nonlinear Wave-Type PDEs with Proportional and More Complex Delays
Authors: Andrei D. Polyanin, Vsevolod G. Sorokin
First page: 516
Abstract: The study gives a brief overview of publications on exact solutions for functional PDEs with delays of various types and on methods for constructing such solutions. For the first time, second-order wave-type PDEs with a nonlinear source term containing the unknown function with proportional time delay, proportional space delay, or both time and space delays are considered. In addition to nonlinear wave-type PDEs with constant speed, equations with variable speed are also studied. New one-dimensional reductions and exact solutions of such PDEs with proportional delay are obtained using solutions of simpler PDEs without delay and methods of separation of variables for nonlinear PDEs. Self-similar solutions, additive and multiplicative separable solutions, generalized separable solutions, and some other solutions are presented. More complex nonlinear functional PDEs with a variable time or space delay of general form are also investigated. Overall, more than thirty wave-type equations with delays that admit exact solutions are described. The study results can be used to test numerical methods and investigate the properties of the considered and related PDEs with proportional or more complex variable delays.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030516
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 517: Tailings Pond Classification Based on
Authors: Haoxuan Yu, Izni Zahidi
First page: 517
Abstract: Mine pollution from mining activities is often widely recognised as a serious threat to public health, with mine solid waste causing problems such as tailings pond accumulation, which is considered the biggest hidden danger. The construction of tailings ponds not only causes land occupation and vegetation damage but also brings about potential environmental pollution, such as water and dust pollution, posing a health risk to nearby residents. If remote sensing images and machine learning techniques could be used to determine whether a tailings pond might have potential pollution and safety hazards, mainly monitoring tailings ponds that may have potential hazards, it would save a lot of effort in tailings ponds monitoring. Therefore, based on this background, this paper proposes to classify tailings ponds into two categories according to whether they are potentially risky or generally safe and to classify tailings ponds with remote sensing satellite images of tailings ponds using the DDN + ResNet-50 machine learning model based on ML.Net developed by Microsoft. In the discussion section, the paper introduces the environmental hazards of mine pollution and proposes the concept of “Healthy Mine” to provide development directions for mining companies and solutions to mine pollution and public health crises. Finally, we claim this paper serves as a guide to begin a conversation and to encourage experts, researchers and scholars to engage in the research field of mine solid waste pollution monitoring, assessment and treatment.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030517
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 518: The Slash Half-Normal Distribution
Applied to a Cure Rate Model with Application to Bone Marrow
Transplantation
Authors: Diego I. Gallardo, Yolanda M. Gómez, Héctor J. Gómez, María José Gallardo-Nelson, Marcelo Bourguignon
First page: 518
Abstract: This paper proposes, for the first time, the use of an asymmetric positive and heavy-tailed distribution in a cure rate model context. In particular, it introduces a cure-rate survival model by assuming that the time-to-event of interest follows a slash half-normal distribution and that the number of competing causes of the event of interest follows a power series distribution, which defines six new cure rate models. Several properties of the model are derived and an alternative expression for the cumulative distribution function of the model is presented, which is very useful for the computational implementation of the model. A procedure based on the expectation–maximization algorithm is proposed for the parameter estimation. Two simulation studies are performed to assess some properties of the estimators, showing the good performance of the proposed estimators in finite samples. Finally, an application to a bone marrow transplant data set is presented.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030518
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 519: Poisson Doubly Warped Product Manifolds
Authors: Ibrahim Al-Dayel, Foued Aloui, Sharief Deshmukh
First page: 519
Abstract: This article generalizes some geometric structures on warped product manifolds equipped with a Poisson structure to doubly warped products of pseudo-Riemannian manifolds equipped with a doubly warped Poisson structure. First, we introduce the notion of Poisson doubly warped product manifold (fB×bF,Π=μvΠBh+νhΠFv,g) and express the Levi-Civita contravariant connection, curvature and metacurvature of (fB×bF,Π,g) in terms of Levi-Civita connections, curvatures and metacurvatures of components (B,ΠB,gB) and (F,ΠF,gF). We also study compatibility conditions related to the Poisson structure Π and the contravariant metric g on fB×bF, so that the compatibility conditions on (B,ΠB,gB) and (F,ΠF,gF) remain consistent in the Poisson doubly warped product manifold (fB×bF,Π,g).
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030519
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 520: Accurate Approximation of the Matrix
Hyperbolic Cosine Using Bernoulli Polynomials
Authors: José M. Alonso, Javier Ibáñez, Emilio Defez, Fernando Alvarruiz
First page: 520
Abstract: This paper presents three different alternatives to evaluate the matrix hyperbolic cosine using Bernoulli matrix polynomials, comparing them from the point of view of accuracy and computational complexity. The first two alternatives are derived from two different Bernoulli series expansions of the matrix hyperbolic cosine, while the third one is based on the approximation of the matrix exponential by means of Bernoulli matrix polynomials. We carry out an analysis of the absolute and relative forward errors incurred in the approximations, deriving corresponding suitable values for the matrix polynomial degree and the scaling factor to be used. Finally, we use a comprehensive matrix testbed to perform a thorough comparison of the alternative approximations, also taking into account other current state-of-the-art approaches. The most accurate and efficient options are identified as results.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030520
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 521: Implementation and Performance Analysis
of Kalman Filters with Consistency Validation
Authors: Dah-Jing Jwo, Amita Biswal
First page: 521
Abstract: This paper provides a useful supplement note for implementing the Kalman filters. The material presented in this work points out several significant highlights with emphasis on performance evaluation and consistency validation between the discrete Kalman filter (DKF) and the continuous Kalman filter (CKF). Several important issues are delivered through comprehensive exposition accompanied by supporting examples, both qualitatively and quantitatively for implementing the Kalman filter algorithms. The lesson learned assists the readers to capture the basic principles of the topic and enables the readers to better interpret the theory, understand the algorithms, and correctly implement the computer codes for further study on the theory and applications of the topic. A wide spectrum of content is covered from theoretical to implementation aspects, where the DKF and CKF along with the theoretical error covariance check based on Riccati and Lyapunov equations are involved. Consistency check of performance between discrete and continuous Kalman filters enables readers to assure correctness on implementing and coding for the algorithm. The tutorial-based exposition presented in this article involves the materials from a practical usage perspective that can provide profound insights into the topic with an appropriate understanding of the stochastic process and system theory.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030521
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 522: A Hybrid PSO-DE Intelligent Algorithm for
Solving Constrained Optimization Problems Based on Feasibility Rules
Authors: Eryang Guo, Yuelin Gao, Chenyang Hu, Jiaojiao Zhang
First page: 522
Abstract: In this paper, we study swarm intelligence computation for constrained optimization problems and propose a new hybrid PSO-DE algorithm based on feasibility rules. Establishing individual feasibility rules as a way to determine whether the position of an individual satisfies the constraint or violates the degree of the constraint, which will determine the choice of the individual optimal position and the global optimal position in the particle population. First, particle swarm optimization (PSO) is used to act on the top 50% of individuals with higher degree of constraint violation to update their velocity and position. Second, Differential Evolution (DE) is applied to act on the individual optimal position of each individual to form a new population. The current individual optimal position and the global optimal position are updated using the feasibility rules, thus forming a hybrid PSO-DE intelligent algorithm. Analyzing the convergence and complexity of PSO-DE. Finally, the performance of the PSO-DE algorithm is tested with 12 benchmark functions of constrained optimization and 57 engineering optimization problems, the numerical results show that the proposed algorithm has good accuracy, effectiveness and robustness.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030522
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 523: The Meshfree Radial Point Interpolation
Method (RPIM) for Wave Propagation Dynamics in Non-Homogeneous Media
Authors: Cong Liu, Shaosong Min, Yandong Pang, Yingbin Chai
First page: 523
Abstract: This work presents a novel simulation approach to couple the meshfree radial point interpolation method (RPIM) with the implicit direct time integration method for the transient analysis of wave propagation dynamics in non-homogeneous media. In this approach, the RPIM is adopted for the discretization of the overall space domain, while the discretization of the time domain is completed by employing the efficient Bathe time stepping scheme. The dispersion analysis demonstrates that, in wave analysis, the amount of numerical dispersion error resulting from the discretization in the space domain can be suppressed at a very low level when the employed nodal support domain of the interpolation function is adequately large. Meanwhile, it is also mathematically shown that the amount of numerical error resulting from the time domain discretization is actually a monotonically decreasing function of the non-dimensional time domain discretization interval. Consequently, the present simulation approach is capable of effectively handling the transient analysis of wave propagation dynamics in non-homogeneous media, and the disparate waves with different speeds can be solved concurrently with very high computation accuracy. This numerical feature makes the present simulation approach more suitable for complicated wave analysis than the traditional finite element approach because the waves with disparate speeds always cannot be concurrently solved accurately. Several numerical tests are given to check the performance of the present simulation approach for the analysis of wave propagation dynamics in non-homogeneous media.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030523
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 524: Adaptive Load Incremental Step in Large
Increment Method for Elastoplastic Problems
Authors: Baorang Cui, Jingxiu Zhang, Yong Ma
First page: 524
Abstract: As a force-based finite element method (FEM), large increment method (LIM) shows unique advantages in material nonlinearity problems. In LIM for material nonlinearity analysis, adaptive load incremental step is a fundamental step for its successful application. In this work, a strategy to automatically refine the load incremental step is proposed in the framework of LIM. The adaptive load incremental step is an iterative process based on the whole loading process, and the location and number of post-refined incremental steps are determined by the posteriori error of energy on the pre-refined incremental steps. Furthermore, the iterative results from the pre-refined incremental steps can be utilized as the initial value to calculate the result for the post-refined incremental steps, which would significantly improve the computational accuracy and efficiency. The strategy is demonstrated using a two-dimensional example with a bilinear hardening material model under cyclic loading, which verifies the accuracy and efficiency of the strategy in LIM. Compared with the displacement-based FEM, which relies upon a step-by-step incremental approach stemming from flow theory, the adaptive load incremental step based on the whole loading process of LIM can avoid the cumulative errors caused by step-by-step in global stage and can quantify the accuracy of results. This work provides a guidance for the practical application of LIM in nonlinear problems.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030524
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 525: Power System Transient Stability
Assessment Based on Machine Learning Algorithms and Grid Topology
Authors: Mihail Senyuk, Murodbek Safaraliev, Firuz Kamalov, Hana Sulieman
First page: 525
Abstract: This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic stability assessment is achieved. The selected research topic relates to the issue of changing the structure and parameters of modern power systems. The key features of modern power systems include the following: decreased total inertia caused by integration of renewable sources energy, stricter requirements for emergency control accuracy, highly digitized operation and control of power systems, and high volumes of data that describe power system operation. Arranging emergency control in these new conditions is one of the prominent problems in modern power systems. In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. Transient stability of a power system was analyzed as the base function. Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. In the case of the test sample, accuracy of instability classification for XGBoost was 91.5%, while that for Random Forest was 81.6%. The accuracy of algorithms increased by 10.9% and 1.5%, respectively, when the topology of the power system was taken into account.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030525
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 526: An improved Fractional MPPT Method by
Using a Small Circle Approximation of the P–V Characteristic Curve
Authors: Ernesto Bárcenas-Bárcenas, Diego R. Espinoza-Trejo, José A. Pecina-Sánchez, Héctor A. Álvarez-Macías, Isaac Compeán-Martínez, Ángel A. Vértiz-Hernández
First page: 526
Abstract: This paper presents an analytical solution to the maximum power point tracking (MPPT) problem for photovoltaic (PV) applications in the form of an improved fractional method. The proposal makes use of a mathematical function that describes the relationship between power and voltage in a PV module in a neighborhood including the maximum power point (MPP). The function is generated by using only three points of the P–V curve. Next, by using geometrical relationships, an analytical value for the MPP can be obtained. The advantage of the proposed technique is that it provides an explicit mathematical expression for calculation of the voltage at the maximum power point (vMPP) with high accuracy. Even more, complex calculations, manufacturer data, the measurements of short circuit current (iSC) and open-circuit voltage (vOC) are not required, making the proposal less invasive than other solutions. The proposed method is validated using the P–V curve of one PV module. Experimental work demonstrates the speed in the calculation of vMPP and the feasibility of the proposed solution. In addition, this MPPT proposal requires only the typical and available measurements, namely, PV voltage and current. Consequently, the proposed method could be implemented in most PV applications.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030526
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 527: Semantic Similarity-Based Mobile
Application Isomorphic Graphical User Interface Identification
Authors: Jing Cheng, Jiayi Zhao, Weidong Xu, Tao Zhang, Feng Xue, Shaoying Liu
First page: 527
Abstract: Applying robots to mobile application testing is an emerging approach to automated black-box testing. The key to supporting automated robot testing is the efficient modeling of GUI elements. Since the application under testing often contains a large number of similar GUIs, the GUI model obtained often contains many redundant nodes. This causes the state space explosion of GUI models which has a serious effect on the efficiency of GUI testing. Hence, how to accurately identify isomorphic GUIs and construct quasi-concise GUI models are key challenges faced today. We thus propose a semantic similarity-based approach to identifying isomorphic GUIs for mobile applications. Using this approach, the information of GUI elements is first identified by deep learning network models, then, the GUI structure model feature vector and the semantic model feature vector are extracted and finally merged to generate a GUI embedding vector with semantic information. Finally, the isomorphic GUIs are identified by cosine similarity. Then, three experiments are conducted to verify the generalizability and effectiveness of the method. The experiments demonstrate that the proposed method can accurately identify isomorphic GUIs and shows high compatibility in terms of cross-platform and cross-device applications.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030527
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 528: Quantile Dependence between Crude Oil
Returns and Implied Volatility: Evidence from Parametric and Nonparametric
Tests
Authors: Bechir Raggad, Elie Bouri
First page: 528
Abstract: We examine the daily dependence and directional predictability between the returns of crude oil and the Crude Oil Volatility Index (OVX). Unlike previous studies, we apply a battery of quantile-based techniques, namely the quantile unit root test, the causality-in-quantiles test, and the cross-quantilogram approach. Our main results show evidence of significant bi-directional predictability that is quantile-dependent and asymmetric. A significant positive Granger causality runs from oil (OVX) returns to OVX (oil) returns when both series are in similar lower (upper) quantiles, as well as in opposite quantiles. The Granger causality from OVX returns to oil returns is only significant during periods of high volatility, although it is not always positive. The findings imply that the forward-looking estimate of oil volatility, reflecting the sentiment of oil market participants, should be considered when studying price variations in the oil market, and that crude oil returns can be used to predict oil implied volatility during bearish market conditions. Therefore, the findings have implications regarding predictability under various conditions for oil market participants.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030528
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 529: Scale Mixture of Maxwell-Boltzmann
Distribution
Authors: Jaime S. Castillo, Katherine P. Gaete, Héctor A. Muñoz, Diego I. Gallardo, Marcelo Bourguignon, Osvaldo Venegas, Héctor W. Gómez
First page: 529
Abstract: This paper presents a new distribution, the product of the mixture between Maxwell-Boltzmann and a particular case of the generalized gamma distributions. The resulting distribution, called the Scale Mixture Maxwell-Boltzmann, presents greater kurtosis than the recently introduced slash Maxwell-Boltzmann distribution. We obtained closed-form expressions for its probability density and cumulative distribution functions. We studied some of its properties and moments, as well as its skewness and kurtosis coefficients. Parameters were estimated by the moments and maximum likelihood methods, via the Expectation-Maximization algorithm for the latter case. A simulation study was performed to illustrate the parameter recovery. The results of an application to a real data set indicate that the new model performs very well in the presence of outliers compared with other alternatives in the literature.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030529
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 530: Multicollinearity and Linear Predictor
Link Function Problems in Regression Modelling of Longitudinal Data
Authors: Mozhgan Taavoni, Mohammad Arashi, Samuel Manda
First page: 530
Abstract: In the longitudinal data analysis we integrate flexible linear predictor link function and high-correlated predictor variables. Our approach uses B-splines for non-parametric part in the linear predictor component. A generalized estimation equation is used to estimate the parameters of the proposed model. We assess the performance of our proposed model using simulations and an application to an analysis of acquired immunodeficiency syndrome data set.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030530
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 531: A Forgotten Effects Approach to the
Analysis of Complex Economic Systems: Identifying Indirect Effects on
Trade Networks
Authors: Felipe Chávez-Bustamante, Elliott Mardones-Arias, Julio Rojas-Mora, Jaime Tijmes-Ihl
First page: 531
Abstract: The purpose of this paper is to identify the emergence of indirect trade flows prompted by the export interaction of the world’s economies. Using data on exports from the United Nations Conference on Trade and Development (UNCTAD) for the period 2016–2021, we construct an international trade network which is analyzed through the “forgotten effects theory” that identifies tuples of countries with an origin, intermediary countries, and a destination. This approach intends to spotlight something beyond the analysis of the direct trade network by the identification of second and third-order paths. The analysis using both network analyses, as well as the forgotten effect approaches, which show that the international trade network presents a hub-and-spoke behavior in contrast to most extant research finding a core-periphery structure. The structure is then comprised of three almost separated trade networks and a hub country that bridges commerce between those networks. The contribution of this article is to move the analysis forward from other works that utilize trade networks, including those of econometric nature—such as the ones based on gravity models—by incorporating indirect relationships between countries, which could provide distinctive and novel insights into the study of economic networks.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030531
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 532: Privacy Preservation Authentication:
Group Secret Handshake with Multiple Groups
Authors: Dong Han, Zhen Li, Mengyu Wang, Chang Xu, Kashif Sharif
First page: 532
Abstract: The technique of group secret handshake (GSH) has been used to help the members affiliated with the same group in achieving private authentication. After executing GSH protocols, the participants affiliated with the group can compute a shared secret key, or generate a public encryption key while the true participants can self-compute their decryption keys. This paper presents a concrete GSH protocol with Multiple Groups. Only a legitimate member can prove that it belongs to a set of legitimate affiliations, but which affiliation it belongs to will not be leaked. The Group Authority can reveal the real identities of the fellows in the proposed scheme after analyzing the flow of communication. The proposed scheme can provide affiliation-hiding and detectability. In addition, it achieves Perfect Forward Secrecy.
Citation: Mathematics
PubDate: 2023-01-18
DOI: 10.3390/math11030532
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 533: Bifurcation Diagram of the Model of a
Lagrange Top with a Vibrating Suspension Point
Authors: Pavel E. Ryabov, Sergei V. Sokolov
First page: 533
Abstract: The article considers a model system that describes a dynamically symmetric rigid body in the Lagrange case with a suspension point that performs high-frequency oscillations. This system, reduced to axes rigidly connected to the body, after the averaging procedure, has the form of the Hamilton equations with two degrees of freedom and has the Liouville integrability property of a Hamiltonian system with two degrees of freedom, which describes the dynamics of a Lagrange top with an oscillating suspension point. The paper presents a bifurcation diagram of the moment mapping. Using the bifurcation diagram, we presented in geometric form the results of the study of the problem of stability of singular points, in particular, singular points of rank zero and rank one.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030533
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 534: Challenging the Curse of Dimensionality
in Multidimensional Numerical Integration by Using a Low-Rank Tensor-Train
Format
Authors: Boian Alexandrov, Gianmarco Manzini, Erik W. Skau, Phan Minh Duc Truong, Radoslav G. Vuchov
First page: 534
Abstract: Numerical integration is a basic step in the implementation of more complex numerical algorithms suitable, for example, to solve ordinary and partial differential equations. The straightforward extension of a one-dimensional integration rule to a multidimensional grid by the tensor product of the spatial directions is deemed to be practically infeasible beyond a relatively small number of dimensions, e.g., three or four. In fact, the computational burden in terms of storage and floating point operations scales exponentially with the number of dimensions. This phenomenon is known as the curse of dimensionality and motivated the development of alternative methods such as the Monte Carlo method. The tensor product approach can be very effective for high-dimensional numerical integration if we can resort to an accurate low-rank tensor-train representation of the integrand function. In this work, we discuss this approach and present numerical evidence showing that it is very competitive with the Monte Carlo method in terms of accuracy and computational costs up to several hundredths of dimensions if the integrand function is regular enough and a sufficiently accurate low-rank approximation is available.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030534
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 535: A Unifying Principle in the Theory of
Modular Relations
Authors: Guodong Liu, Kalyan Chakraborty, Shigeru Kanemitsu
First page: 535
Abstract: The Voronoĭ summation formula is known to be equivalent to the functional equation for the square of the Riemann zeta function in case the function in question is the Mellin tranform of a suitable function. There are some other famous summation formulas which are treated as independent of the modular relation. In this paper, we shall establish a far-reaching principle which furnishes the following. Given a zeta function Z(s) satisfying a suitable functional equation, one can generalize it to Zf(s) in the form of an integral involving the Mellin transform F(s) of a certain suitable function f(x) and process it further as Z˜f(s). Under the condition that F(s) is expressed as an integral, and the order of two integrals is interchangeable, one can obtain a closed form for Z˜f(s). Ample examples are given: the Lipschitz summation formula, Koshlyakov’s generalized Dedekind zeta function and the Plana summation formula. In the final section, we shall elucidate Hamburger’s results in light of RHBM correspondence (i.e., through Fourier–Whittaker expansion).
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030535
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 536: Mathematical Modeling of the State of the
Battery of Cargo Electric Vehicles
Authors: Nikita V. Martyushev, Boris V. Malozyomov, Svetlana N. Sorokova, Egor A. Efremenkov, Mengxu Qi
First page: 536
Abstract: In this paper, a mathematical simulation model of an electric vehicle traction battery has been developed, in which the battery was studied during the dynamic modes of its charge and discharge for heavy electric vehicles in various driving conditions—the conditions of the urban cycle and movement outside the city. The state of a lithium-ion battery is modeled based on operational factors, including changes in battery temperature. The simulation results will be useful for the implementation of real-time systems that take into account the processes of changing the characteristics of traction batteries. The developed mathematical model can be used in battery management systems to monitor the state of charge and battery degradation using the assessment of the state of charge (SOC) and the state of health (SOH). This is especially important when designing and operating a smart battery management system (BMS) in virtually any application of lithium-ion batteries, providing information on how long the device will run before it needs to be charged (SOC value) and when the battery should be replaced due to loss of battery capacity (SOH value). Based on the battery equivalent circuit and the system of equations, a simulation model was created to calculate the electrical and thermal characteristics. The equivalent circuit includes active and reactive elements, each of which imitates the physicochemical parameter of the battery under study or the structural element of the electrochemical battery. The input signals of the mathematical model are the current and ambient temperatures obtained during the tests of the electric vehicle, and the output signals are voltage, electrolyte temperature and degree of charge. The resulting equations make it possible to assign values of internal resistance to a certain temperature value and a certain value of the degree of charge. As a result of simulation modeling, the dependence of battery heating at various ambient temperatures was determined.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030536
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 537: Semi-Automatic 3D Reconstruction of
Atheroma Plaques from Intravascular Ultrasound Images Using an ad-hoc
Algorithm
Authors: Javier Martínez, Daniel Pérez-Palau, Myriam Cilla, Neus Garrido, Ana Larrañaga, Ignacio Pérez-Rey
First page: 537
Abstract: The occurrence of atheroma plaques in the arteries can eventually obstruct them, leading to diseases such as atherosclerosis, which can cause, among others, a myocardial infarction or a stroke. As a consequence, it is necessary to shorten the time spent in locating and reconstructing the atheroma plaque that can be developed in an artery. This localization is usually conducted manually from the contours located on the cross-sectional radiographs of the artery and then reconstructed by creating the volumes using different techniques. This paper presents a 3-D reconstruction of the atheroma plaque by applying an image processing algorithm ad-hoc developed in order to obtain the boundaries of the atheroma, from a set of intravascular ultrasound images. The advantage of the approach developed in this paper is that it can be implemented in common medical procedures, as an important complementary decision-support tool. By reconstructing the atheroma instead of the artery, this work provides a different approach to improve its location and treatment. Results presented herein can be implemented in machine-learning-based algorithms, able to predict the growth and extent of incipient atheroma plaques, which ultimately contribute to an early detection of this pathology.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030537
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 538: Energy Decay Estimates of a Timoshenko
System with Two Nonlinear Variable Exponent Damping Terms
Authors: Adel M. Al-Mahdi, Mohammad M. Al-Gharabli
First page: 538
Abstract: This paper is concerned with the asymptotic behavior of the solution of a Timoshenko system with two nonlinear variable exponent damping terms. We prove that the system is stable under some specific conditions on the variable exponent and the equal wave speeds of propagation. We obtain exponential and polynomial decay results by using the multiplier method, and we prove that one variable damping is enough to have polynomial and exponential decay. We observe that the decay is not necessarily improved if the system has two variable damping terms. Our results built on, developed and generalized some earlier results in the literature.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030538
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 539: The Numerical Solution of the External
Dirichlet Generalized Harmonic Problem for a Sphere by the Method of
Probabilistic Solution
Authors: Mamuli Zakradze, Zaza Tabagari, Nana Koblishvili, Tinatin Davitashvili, Jose Maria Sanchez, Francisco Criado-Aldeanueva
First page: 539
Abstract: In the present paper, an algorithm for the numerical solution of the external Dirichlet generalized harmonic problem for a sphere by the method of probabilistic solution (MPS) is given, where “generalized” indicates that a boundary function has a finite number of first kind discontinuity curves. The algorithm consists of the following main stages: (1) the transition from an infinite domain to a finite domain by an inversion; (2) the consideration of a new Dirichlet generalized harmonic problem on the basis of Kelvin’s theorem for the obtained finite domain; (3) the numerical solution of the new problem for the finite domain by the MPS, which in turn is based on a computer simulation of the Weiner process; (4) finding the probabilistic solution of the posed generalized problem at any fixed points of the infinite domain by the solution of the new problem. For illustration, numerical examples are considered and results are presented.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030539
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 540: Characterization of Flow under Impervious
Dams: Dimensionless Groups and Universal Solutions
Authors: Encarnación Martínez-Moreno, Gonzalo García-Ros, Iván Alhama, Francisco Alhama
First page: 540
Abstract: As far as we know, no dimensionless solutions for infiltrated flow under dams in anisotropic media exist since those that can be found in manuals refer to isotropic soils. The novelty of this work is the presentation of universal solutions in the form of abaci for water flow, average exit gradient, uplift force, and its application point for this type of soil. These solutions are obtained by the application of the discriminated nondimensionalization technique to the governing equations in order to find accurate dimensionless groups that control the results of the problem. In particular, the ratio of permeabilities corrected by a geometrical aspect relationship appears as a governing group, so anisotropy can be considered as input information. In this way, the sought solutions are a function of the emerging groups. Numerical solutions are used to successfully verify the results obtained, which in turn are compared to those of other authors for isotropic scenarios.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030540
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 541: Fuzzy Model for Determining the Risk
Premium to the Rental Rate When Renting Technological Equipment
Authors: Yuriy Ekhlakov, Sergei Saprunov, Pavel Senchenko, Anatoly Sidorov
First page: 541
Abstract: The article is devoted to the method of determining the risk surcharge in rental rates for special technological equipment. The relevance and features of the task, as well as existing approaches to solve it in other subject areas, are described. The risk of landlords is highlighted as “the inability to fully ensure the receipt of a stable income recorded in the lease agreement”. The three most significant risk-forming factors are highlighted: the early return of equipment, the emergence of debt on payments from the tenant, and the breakdown of equipment due to the fault of the tenant. A fuzzy model for estimating the likelihood of the manifestation of risk-forming factors is proposed depending on the following challenges of the rental pillar: the size of the enterprise, financial stability, the age of the enterprise, the number of current trials, and the reputation of the enterprise. Describes: universal linguistics for input and output values characterizing risky components, logical output rules, and the assessment of the likelihood of risk in general. Based on the SciKit-Fuzzy library for the Python language, the model studies all available values of input variables, and tenants are presented separately on the boundary values of the enterprise parameters. A methodology for determining the rental rate, taking into account the risk surcharge, is proposed.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030541
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 542: A Behavioral Foundation of Satiation and
Habituation
Authors: Junyi Chai
First page: 542
Abstract: Tastes change over time. People’s tastes are distorted through two channels: satiation formation and habit formation. In this paper, we develop a theoretical foundation of satiation and habituation by an axiomatic approach. Our theory is based on a hierarchy of preference conditions called compensation independence. The behavioral assumption underlying the preference conditions are the psychological compensation of human beings. I flesh out an axiomatic system for general models of satiation and habit formation, which contains many functional forms in the literature as special cases. Moreover, I advance the axiomatization to accommodate the linear representations of satiation and habit formation that are prevailing in the literature. This paper contributes to the birth of a new generation of the behavioral foundation for modeling satiation and habit formation, which might improve on the current state of the art in understanding people’s tastes over time and preferences. Theoretically, this study contributes to the vein of time-nonseparable preferences.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030542
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 543: Mechanical Stability of the Heterogenous
Bilayer Solid Electrolyte Interphase in the Electrodes of
Lithium–Ion Batteries
Authors: Yasir Ali, Noman Iqbal, Imran Shah, Seungjun Lee
First page: 543
Abstract: Mechanical stability of the solid electrolyte interphase (SEI) is crucial to mitigate the capacity fade of lithium–ion batteries because the rupture of the SEI layer results in further consumption of lithium ions in newly generated SEI layers. The SEI is known as a heterogeneous bilayer and consists of an inner inorganic layer connecting the particle and an outer organic layer facing the electrolyte. The growth of the bilayer SEI over cycles alters the stress generation and failure possibility of both the organic and inorganic layers. To investigate the probability of mechanical failure of the bilayer SEI, we developed the electrochemical-mechanical coupled model with the core–double-shell particle/SEI layer model. The growth of the bilayer SEI is considered over cycles. Our results show that during charging, the stress of the particle changes from tensile to compressive as the thickness of bilayer SEI increases. On the other hand, in the SEI layers, large compressive radial and tensile tangential stress are generated. During discharging, the compressive radial stress of the bilayer SEI transforms into tensile radial stress. The tensile tangential and radial stresses are responsible for the fracture and debonding of the bilayer SEI, respectively. As the thickness ratio of the inorganic to organic layers increases, the fracture probability of the inorganic layer increases, while that of the organic layer decreases. However, the debonding probability of both layers is decreased. In addition, the SEI covering large particles is more vulnerable to fracture, while that covering small particles is more susceptible to debonding. Therefore, tailoring the thickness ratio of the inorganic to organic layers and particle size is important to reduce the fracture and debonding of the heterogeneous bilayer SEI.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030543
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 544: Four-Parameter Weibull Distribution with
Lower and Upper Limits Applicable in Reliability Studies and Materials
Testing
Authors: Jan Kohout
First page: 544
Abstract: A simply curved Weibull plot means that the studied data set has a three-parameter Weibull distribution with a non-zero location parameter representing the lower or the upper limit of the data set. This paper introduces a four-parameter Weibull distribution with both of these limits that can be applied in both reliability and materials engineering. A very reliable indicator of this distribution is the double-curved Weibull plot. The great advantage of this distribution is the fact that the corresponding hazard rate curve can be bathtub-shaped with a great ability to fit the measured data.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030544
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 545: Existence and Uniqueness of Generalized
and Mixed Finite Element Solutions for Steady Boussinesq Equation
Authors: Zhendong Luo, Xiangdong Liu, Yihui Zeng, Yuejie Li
First page: 545
Abstract: Herein, we mainly employ the fixed point theorem and Lax-Milgram theorem in functional analysis to prove the existence and uniqueness of generalized and mixed finite element (MFE) solutions for two-dimensional steady Boussinesq equation. Thus, we can fill in the gap of research for the steady Boussinesq equation since the existing studies for the equation are assumed the existence and uniqueness of generalized solution without providing proof.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030545
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 546: Total Problem of Constructing Linear
Regression Using Matrix Correction Methods with Minimax Criterion
Authors: Victor Gorelik, Tatiana Zolotova
First page: 546
Abstract: A linear problem of regression analysis is considered under the assumption of the presence of noise in the output and input variables. This approximation problem may be interpreted as an improper interpolation problem, for which it is required to correct optimally the positions of the original points in the data space so that they all lie on the same hyperplane. The use of the quadratic approximation criterion for such a problem led to the appearance of the total least squares method. In this paper, we use the minimax criterion to estimate the measure of correction of the initial data. It leads to a nonlinear mathematical programming problem. It is shown that this problem can be reduced to solving a finite number of linear programming problems. However, this number depends exponentially on the number of parameters. Some methods for overcoming this complexity of the problem are proposed.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030546
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 547: Petroleum Price Prediction with CNN-LSTM
and CNN-GRU Using Skip-Connection
Authors: Gun Il Kim, Beakcheol Jang
First page: 547
Abstract: Crude oil plays an important role in the global economy, as it contributes one-third of the energy consumption worldwide. However, despite its importance in policymaking and economic development, forecasting its price is still challenging due to its complexity and irregular price trends. Although a significant amount of research has been conducted to improve forecasting using external factors as well as machine-learning and deep-learning models, only a few studies have used hybrid models to improve prediction accuracy. In this study, we propose a novel hybrid model that captures the finer details and interconnections between multivariate factors to improve the accuracy of petroleum oil price prediction. Our proposed hybrid model integrates a convolutional neural network and a recurrent neural network with skip connections and is trained using petroleum oil prices and external data directly accessible from the official website of South Korea’s national oil corporation and the official Yahoo Finance site. We compare the performance of our univariate and multivariate models in terms of the Pearson correlation, mean absolute error, mean squared error, root mean squared error, and R squared (R2) evaluation metrics. Our proposed models exhibited significantly better performance than the existing models based on long short-term memory and gated recurrent units, showing correlations of 0.985 and 0.988, respectively, for 10-day price predictions and obtaining better results for longer prediction periods when compared with other deep-learning models. We validated that our proposed model with skip connections outperforms the benchmark models and showed that the convolutional neural network using gated recurrent units with skip connections is superior to the compared models. The findings suggest that, to some extent, relying on a single source of data is ineffective in predicting long-term changes in oil prices, and thus, to develop a better prediction model based on time-series based data, it is necessary to take a multivariate approach and develop an efficient computational model with skip connections.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030547
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 548: A Semantics-Based Clustering Approach for
Online Laboratories Using K-Means and HAC Algorithms
Authors: Saad Hikmat Haji, Karwan Jacksi, Razwan Mohmed Salah
First page: 548
Abstract: Due to the availability of a vast amount of unstructured data in various forms (e.g., the web, social networks, etc.), the clustering of text documents has become increasingly important. Traditional clustering algorithms have not been able to solve this problem because the semantic relationships between words could not accurately represent the meaning of the documents. Thus, semantic document clustering has been extensively utilized to enhance the quality of text clustering. This method is called unsupervised learning and it involves grouping documents based on their meaning, not on common keywords. This paper introduces a new method that groups documents from online laboratory repositories based on the semantic similarity approach. In this work, the dataset is collected first by crawling the short real-time descriptions of the online laboratories’ repositories from the Web. A vector space is created using frequency-inverse document frequency (TF-IDF) and clustering is done using the K-Means and Hierarchical Agglomerative Clustering (HAC) algorithms with different linkages. Three scenarios are considered: without preprocessing (WoPP); preprocessing with steaming (PPwS); and preprocessing without steaming (PPWoS). Several metrics have been used for evaluating experiments: Silhouette average, purity, V-measure, F1-measure, accuracy score, homogeneity score, completeness and NMI score (consisting of five datasets: online labs, 20 NewsGroups, Txt_sentoken, NLTK_Brown and NLTK_Reuters). Finally, by creating an interactive webpage, the results of the proposed work are contrasted and visualized.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030548
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 549: A Flexible Method for Diagnostic Accuracy
with Biomarker Measurement Error
Authors: Ching-Yun Wang, Ziding Feng
First page: 549
Abstract: Diagnostic biomarkers are often measured with errors due to imperfect lab conditions or analytic variability of the assay. The ability of a diagnostic biomarker to discriminate between cases and controls is often measured by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, among others. Ignoring measurement error can cause biased estimation of a diagnostic accuracy measure, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Existing assays available are either research grade or clinical grade. Research assays are cost effective, often multiplex, but they may be associated with moderate measurement errors leading to poorer diagnostic performance. In comparison, clinical assays may provide better diagnostic ability, but with higher cost since they are usually developed by industry. Correction for attenuation methods are often valid when biomarkers are from a normal distribution, but may be biased with skewed biomarkers. In this paper, we develop a flexible method based on skew–normal biomarker distributions to correct for bias in estimating diagnostic performance measures including AUC, sensitivity, and specificity. Finite sample performance of the proposed method is examined via extensive simulation studies. The methods are applied to a pancreatic cancer biomarker study.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030549
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 550: Some Certain Fuzzy Aumann Integral
Inequalities for Generalized Convexity via Fuzzy Number Valued Mappings
Authors: Khan, Othman, Voskoglou, Abdullah, Alzubaidi
First page: 550
Abstract: The topic of convex and nonconvex mapping has many applications in engineering and applied mathematics. The Aumann and fuzzy Aumann integrals are the most significant interval and fuzzy operators that allow the classical theory of integrals to be generalized. This paper considers the well-known fuzzy Hermite–Hadamard (HH) type and associated inequalities. With the help of fuzzy Aumann integrals and the newly introduced fuzzy number valued up and down convexity (𝑈𝒟-convexity), we increase this mileage even further. Additionally, with the help of definitions of lower 𝑈𝒟-concave (lower 𝑈𝒟-concave) and upper 𝑈𝒟-convex (concave) fuzzy number valued mappings (ℱ𝒩𝒱ℳs), we have gathered a sizable collection of both well-known and new extraordinary cases that act as applications of the main conclusions. We also offer a few examples of fuzzy number valued 𝑈𝒟-convexity to further demonstrate the validity of the fuzzy inclusion relations presented in this study.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030550
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 551: A Survey on the Theory of n-Hypergroups
Authors: Bijan Davvaz, Violeta Leoreanu-Fotea, Thomas Vougiouklis
First page: 551
Abstract: This paper presents a series of important results from the theory of n-hypergroups. Connections with binary relations and with lattices are presented. Special attention is paid to the fundamental relation and to the commutative fundamental relation. In particular, join n-spaces are analyzed.
Citation: Mathematics
PubDate: 2023-01-19
DOI: 10.3390/math11030551
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 552: Smoothness of Graph Energy in Chemical
Graphs
Authors: Katja Zemljič, Petra Žigert Pleteršek
First page: 552
Abstract: The energy of a graph G as a chemical concept leading to HMO theory was introduced by Hückel in 1931 and developed into a mathematical interpretation many years later when Gutman in 1978 gave his famous definition of the graph energy as the sum of the absolute values of the eigenvalues of the adjacency matrix of G. One of the general requirements for any topological index is that similar molecules have close TI values, which is called smoothness. To explore this property, we consider two variants of structure sensitivity and abruptness as introduced by Furtula et al. in 2013 and 2019, for hydrocarbons with up to 20 carbon atoms. Finally, we investigate the relationships between graph energies of acyclic hydrocarbons compared to their cyclic versions.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030552
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 553: Change Point Analysis for Kumaraswamy
Distribution
Authors: Weizhong Tian, Liyuan Pang, Chengliang Tian, Wei Ning
First page: 553
Abstract: The Kumaraswamy distribution is a common type of bounded distribution, which is widely used in agriculture, hydrology, and other fields. In this paper, we use the methods of the likelihood ratio test, modified information criterion, and Schwarz information criterion to analyze the change point of the Kumaraswamy distribution. Simulation experiments give the performance of the three methods. The application section illustrates the feasibility of the proposed method by applying it to a real dataset.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030553
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 554: Simultaneous Features of CC Heat Flux on
Dusty Ternary Nanofluid (Graphene + Tungsten Oxide + Zirconium Oxide)
through a Magnetic Field with Slippery Condition
Authors: Basma Souayeh
First page: 554
Abstract: The purpose of this work is to offer a unique theoretical ternary nanofluid (graphene/tungsten oxide/zirconium oxide) framework for better heat transfer. This model describes how to create better heat conduction than a hybrid nanofluid. Three different nanostructures with different chemical and physical bonds are suspended in water to create the ternary nanofluid (graphene/tungsten oxide/zirconium oxide). Toxic substances are broken down, the air is purified, and other devices are cooled thanks to the synergy of these nanoparticles. The properties of ternary nanofluids are discussed in this article, including their thermal conductivity, specific heat capacitance, viscosity, and density. In addition, heat transport phenomena are explained by the Cattaneo–Christov (CC) heat flow theory. In the modeling of the physical phenomena under investigation, the impacts of thermal nonlinear radiation and velocity slip are considered. By using the right transformations, flow-generating PDEs are converted into nonlinear ordinary differential equations. The parameters’ impacts on the velocity and temperature fields are analyzed in detail. The modeled problem is graphically handled in MATLAB using a numerical technique (BVP4c). Graphical representations of the important factors affecting temperature and velocity fields are illustrated through graphs. The findings disclose that the performance of ternary nanofluid phase heat transfer is improved compared to dusty phase performance. Furthermore, the magnetic parameter and the velocity slip parameter both experience a slowing-down effect of their respective velocities.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030554
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 555: A New Incommensurate Fractional-Order
COVID 19: Modelling and Dynamical Analysis
Authors: Abdallah Al-Husban, Noureddine Djenina, Rania Saadeh, Adel Ouannas, Giuseppe Grassi
First page: 555
Abstract: Nowadays, a lot of research papers are concentrating on the diffusion dynamics of infectious diseases, especially the most recent one: COVID-19. The primary goal of this work is to explore the stability analysis of a new version of the SEIR model formulated with incommensurate fractional-order derivatives. In particular, several existence and uniqueness results of the solution of the proposed model are derived by means of the Picard–Lindelöf method. Several stability analysis results related to the disease-free equilibrium of the model are reported in light of computing the so-called basic reproduction number, as well as in view of utilising a certain Lyapunov function. In conclusion, various numerical simulations are performed to confirm the theoretical findings.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030555
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 556: Hopf Bifurcation in a Predator–Prey
Model with Memory Effect in Predator and Anti-Predator Behaviour in Prey
Authors: Wenqi Zhang, Dan Jin, Ruizhi Yang
First page: 556
Abstract: In this paper, a diffusive predator–prey model with a memory effect in predator and anti-predator behaviour in prey is studied. The stability of the coexisting equilibrium and the existence of Hopf bifurcation are analysed by analysing the distribution of characteristic roots. The property of Hopf bifurcation is investigated by the theory of the centre manifold and normal form method. Through the numerical simulations, it is observed that the anti-predator behaviour parameter η, the memory-based diffusion coefficient parameter d, and memory delay τ can affect the stability of the coexisting equilibrium under some parameters and cause the spatially inhomogeneous oscillation of prey and predator’s densities.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030556
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 557: Improving the Robustness of Variable
Selection and Predictive Performance of Regularized Generalized Linear
Models and Cox Proportional Hazard Models
Authors: Feng Hong, Lu Tian, Viswanath Devanarayan
First page: 557
Abstract: High-dimensional data applications often entail the use of various statistical and machine-learning algorithms to identify an optimal signature based on biomarkers and other patient characteristics that predicts the desired clinical outcome in biomedical research. Both the composition and predictive performance of such biomarker signatures are critical in various biomedical research applications. In the presence of a large number of features, however, a conventional regression analysis approach fails to yield a good prediction model. A widely used remedy is to introduce regularization in fitting the relevant regression model. In particular, a L1 penalty on the regression coefficients is extremely useful, and very efficient numerical algorithms have been developed for fitting such models with different types of responses. This L1-based regularization tends to generate a parsimonious prediction model with promising prediction performance, i.e., feature selection is achieved along with construction of the prediction model. The variable selection, and hence the composition of the signature, as well as the prediction performance of the model depend on the choice of the penalty parameter used in the L1 regularization. The penalty parameter is often chosen by K-fold cross-validation. However, such an algorithm tends to be unstable and may yield very different choices of the penalty parameter across multiple runs on the same dataset. In addition, the predictive performance estimates from the internal cross-validation procedure in this algorithm tend to be inflated. In this paper, we propose a Monte Carlo approach to improve the robustness of regularization parameter selection, along with an additional cross-validation wrapper for objectively evaluating the predictive performance of the final model. We demonstrate the improvements via simulations and illustrate the application via a real dataset.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030557
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 558: Implicit Finite-Difference Scheme for a
Duffing Oscillator with a Derivative of Variable Fractional Order of the
Riemann-Liouville Type
Authors: Valentine Aleksandrovich Kim, Roman Ivanovich Parovik, Zafar Ravshanovich Rakhmonov
First page: 558
Abstract: The article considers an implicit finite-difference scheme for the Duffing equation with a derivative of a fractional variable order of the Riemann–Liouville type. The issues of stability and convergence of an implicit finite-difference scheme are considered. Test examples are given to substantiate the theoretical results. Using the Runge rule, the results of the implicit scheme are compared with the results of the explicit scheme. Phase trajectories and oscillograms for a Duffing oscillator with a fractional derivative of variable order of the Riemann–Liouville type are constructed, chaotic modes are detected using the spectrum of maximum Lyapunov exponents and Poincare sections. Q-factor surfaces, amplitude-frequency and phase-frequency characteristics are constructed for the study of forced oscillations. The results of the study showed that the implicit finite-difference scheme shows more accurate results than the explicit one.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030558
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 559: Effects of Diesel Price on Changes in
Agricultural Commodity Prices in Bulgaria
Authors: Miroslava Ivanova, Lilko Dospatliev
First page: 559
Abstract: The aim of this article is to supply the first empirical research inspecting how changes in diesel prices influence the prices of four agricultural commodities in Bulgaria. For this purpose, using a VECM and monthly agricultural commodity prices between January 2011 and July 2022, we estimated short-run and long-run changes in producer and retail prices of cow’s milk, chicken eggs, greenhouse tomatoes and cucumbers due to the change in average monthly diesel prices. The Granger causality test indicates that diesel prices cannot be used to forecast the behavior of producer and retail prices in the four markets considered. Diesel prices can be used to forecast the behavior of producer prices in only the cow’s milk market, and the diesel price predicts retail prices in the chicken egg and greenhouse cucumber markets. The results of the response of the researched prices of agricultural commodities to diesel price shocks indicate a positive response of both upstream and downstream prices of cow’s milk and chicken egg markets and upstream prices of the greenhouse tomato market despite the initial negative shock.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030559
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 560: Column-Type Prediction for Web Tables
Powered by Knowledge Base and Text
Authors: Junyi Wu, Chen Ye, Haoshi Zhi, Shihao Jiang
First page: 560
Abstract: Web tables are essential for applications such as data analysis. However, web tables are often incomplete and short of some critical information, which makes it challenging to understand the web table content. Automatically predicting column types for tables without metadata is significant for dealing with various tables from the Internet. This paper proposes a CNN-Text method to deal with this task, which fuses CNN prediction and voting processes. We present data augmentation and synthetic column generation approaches to improve the CNN’s performance and use extracted text to get better predictions. The experimental result shows that CNN-Text outperforms the baseline methods, demonstrating that CNN-Text is well qualified for the table column type prediction.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030560
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 561: Dynamic Image Representation in a Spiking
Neural Network Supplied by Astrocytes
Authors: Sergey V. Stasenko, Victor B. Kazantsev
First page: 561
Abstract: The mathematical model of the spiking neural network (SNN) supplied by astrocytes is investigated. The astrocytes are a specific type of brain cells which are not electrically excitable but induce chemical modulations of neuronal firing. We analyze how the astrocytes influence images encoded in the form of the dynamic spiking pattern of the SNN. Serving at a much slower time scale, the astrocytic network interacting with the spiking neurons can remarkably enhance the image representation quality. The spiking dynamics are affected by noise distorting the information image. We demonstrate that the activation of astrocytes can significantly suppress noise influence, improving the dynamic image representation by the SNN.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030561
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 562: Classifying Cardiac Arrhythmia from ECG
Signal Using 1D CNN Deep Learning Model
Authors: Adel A. Ahmed, Waleed Ali, Talal A. A. Abdullah, Sharaf J. Malebary
First page: 562
Abstract: Blood circulation depends critically on electrical activation, where any disturbance in the orderly pattern of the heart’s propagating wave of excitation can lead to arrhythmias. Diagnosis of arrhythmias using electrocardiograms (ECG) is widely used because they are a fast, inexpensive, and non-invasive tool. However, the randomness of arrhythmic events and the susceptibility of ECGs to noise leads to misdiagnosis of arrhythmias. In addition, manually diagnosing cardiac arrhythmias using ECG data is time-intensive and error-prone. With better training, deep learning (DL) could be a better alternative for fast and automatic classification. The present study introduces a novel deep learning architecture, specifically a one-dimensional convolutional neural network (1D-CNN), for the classification of cardiac arrhythmias. The model was trained and validated with real and noise-attenuated ECG signals from the MIT-BIH dataset. The main aim is to address the limitations of traditional electrocardiograms (ECG) in the diagnosis of arrhythmias, which can be affected by noise and randomness of events, leading to misdiagnosis and errors. To evaluate the model performance, the confusion matrix is used to calculate the model accuracy, precision, recall, f1 score, average and AUC-ROC. The experiment results demonstrate that the proposed model achieved outstanding performance, with 1.00 and 0.99 accuracies in the training and testing datasets, respectively, and can be a fast and automatic alternative for the diagnosis of arrhythmias.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030562
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 563: Optimization-Based Energy Disaggregation:
A Constrained Multi-Objective Approach
Authors: Jeewon Park, Oladayo S. Ajani, Rammohan Mallipeddi
First page: 563
Abstract: Recently, optimization-based energy disaggregation (ED) algorithms have been gaining significance due to their capability to perform disaggregation with minimal information compared to the pattern-based ED algorithms, which demand large amounts of data for training. However, the performances of optimization-based ED algorithms depend on the problem formulation that includes an objective function(s) and/or constraints. In the literature, ED has been formulated as a constrained single-objective problem or an unconstrained multi-objective problem considering disaggregation error, sparsity of state switching, on/off switching, etc. In this work, the ED problem is formulated as a constrained multi-objective problem (CMOP), where the constraints related to the operational characteristics of the devices are included. In addition, the formulated CMOP is solved using a constrained multi-objective evolutionary algorithm (CMOEA). The performance of the proposed formulation is compared with those of three high-performing ED formulations in the literature based on the appliance-level and overall indicators. The results show that the proposed formulation improves both appliance-level and overall ED results.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030563
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 564: Bounds and Maxima for the Workload in a
Multiclass Orbit Queue
Authors: Evsey V. Morozov, Irina V. Peshkova, Alexander S. Rumyantsev
First page: 564
Abstract: In this research, a single-server M-class retrial queueing system (orbit queue) with constant retrial rates and Poisson inputs is considered. The main purpose is to construct the upper and lower bounds of the stationary workload in this system expressed via the stationary workloads in the classical M/G/1 systems where the service time has M-component mixture distributions. This analysis is applied to establish the extreme behaviour of stationary workload in the retrial system with Pareto service-time distributions for all classes.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030564
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 565: Joint Discrete Approximation of Analytic
Functions by Shifts of the Riemann Zeta-Function Twisted by Gram Points
Authors: Antanas Laurinčikas
First page: 565
Abstract: Let θ(t) denote the increment of the argument of the product π−s/2Γ(s/2) along the segment connecting the points s=1/2 and s=1/2+it, and tn denote the solution of the equation θ(t)=(n−1)π, n=0,1,⋯. The numbers tn are called the Gram points. In this paper, we consider the approximation of a collection of analytic functions by shifts in the Riemann zeta-function (ζ(s+itkα1),⋯,ζ(s+itkαr)), k=0,1,⋯, where α1,⋯,αr are different positive numbers not exceeding 1. We prove that the set of such shifts approximating a given collection of analytic functions has a positive lower density. For the proof, a discrete limit theorem on weak convergence of probability measures in the space of analytic functions is applied.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030565
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 566: Hotelling T2 Control Chart for Detecting
Changes in Mortality Models Based on Machine-Learning Decision Tree
Authors: Suryo Adi Rakhmawan, M. Hafidz Omar, Muhammad Riaz, Nasir Abbas
First page: 566
Abstract: Mortality modelling is a practical method for the government and various fields to obtain a picture of mortality up to a specific age for a particular year. However, some information on the phenomenon may remain in the residual vector and be unrevealed from the models. We handle this issue by employing a multivariate control chart to discover substantial cohort changes in mortality behavior that the models still need to address. The Hotelling T2 control chart is applied to the externally studentized deviance model, which is already optimized using a machine-learning decision tree. This study shows a mortality model with the lowest MSE, MAPE, and deviance, by accomplishing simulations in various countries. In addition, the model that is more sensitive in detecting signals on the control chart is singled out so that we can perform a decomposition to determine the attributes of death in the specific outlying age group in a particular year. The case study in the decomposition uses data from the country Saudi Arabia. The overall results demonstrate that our method of processing and producing mortality models with machine learning can be a solution for developing countries or countries with limited mortality data to produce accurate predictions through monitoring control charts.
Citation: Mathematics
PubDate: 2023-01-20
DOI: 10.3390/math11030566
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 567: A Color Image Encryption Algorithm Based
on Hash Table, Hilbert Curve and Hyper-Chaotic Synchronization
Authors: Xiaoyuan Wang, Xinrui Zhang, Meng Gao, Yuanze Tian, Chunhua Wang, Herbert Ho-Ching Iu
First page: 567
Abstract: Chaotic systems, especially hyper-chaotic systems are suitable for digital image encryption because of their complex properties such as pseudo randomness and extreme sensitivity. This paper proposes a new color image encryption algorithm based on a hyper-chaotic system constructed by a tri-valued memristor. The encryption process is based on the structure of permutation-diffusion, and the transmission of key information is realized through hyper-chaotic synchronization technology. In this design, the hash value of the plaintext image is used to generate the initial key the permutation sequence with the Hash table structure based on the hyper-chaotic sequence is used to implement pixel-level and bit-level permutation operations. Hilbert curves combining with the ciphertext feedback mechanism are applied to complete the diffusion operation. A series of experimental analyses have been applied to measure the novel algorithm, and the results show that the scheme has excellent encryption performance and can resist a variety of attacks. This method can be applied in secure image communication fields.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030567
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 568: Optimization of the 24-Bit Fixed-Point
Format for the Laplacian Source
Authors: Zoran H. Perić, Milan R. Dinčić
First page: 568
Abstract: The 32-bit floating-point (FP32) binary format, commonly used for data representation in computers, introduces high complexity, requiring powerful and expensive hardware for data processing and high energy consumption, hence being unsuitable for implementation on sensor nodes, edge devices, and other devices with limited hardware resources. Therefore, it is often necessary to use binary formats of lower complexity than FP32. This paper proposes the usage of the 24-bit fixed-point format that will reduce the complexity in two ways, by decreasing the number of bits and by the fact that the fixed-point format has significantly less complexity than the floating-point format. The paper optimizes the 24-bit fixed-point format and examines its performance for data with the Laplacian distribution, exploiting the analogy between fixed-point binary representation and uniform quantization. Firstly, the optimization of the 24-bit uniform quantizer is performed by deriving two new closed-form formulas for a very accurate calculation of its maximal amplitude. Then, the 24-bit fixed-point format is optimized by optimization of its key parameter and by proposing two adaptation procedures, with the aim to obtain the same performance as of the optimal uniform quantizer in a wide range of variance of input data. It is shown that the proposed 24-bit fixed-point format achieves for 18.425 dB higher performance than the floating-point format with the same number of bits while being less complex.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030568
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 569: Viability Selection at Linked Sites
Authors: Bjarki Eldon
First page: 569
Abstract: Evolutionary ecology may be described as explaining ecology through evolution and vice versa, but one may also view it as an integration of the two fields, where one takes the view that ecology and evolution are inseparable, and one can only begin to understand the biology of organisms by synthesizing the two fields. An example of such a synthesis is the biology of high fecundity and the associated concept of sweepstakes reproduction, or skewed individual recruitment success. As an illustration, we consider selection at linked sites under various dominance and epistasis mechanisms in a diploid population evolving according to random sweepstakes and experiencing recurrent bottlenecks. Using simulations, we give a few examples of the impact of the stated elements on selection. We show that depending on the dominance mechanisms, random sweepstakes can shorten the time to fixation (conditional on fixation) of the fit type at all sites. Bottlenecks tend to increase the fixation time, with random sweepstakes counteracting the effects of bottlenecks on the fixation time. Understanding the effect of random sweepstakes, recurrent bottlenecks, dominance mechanisms and epistasis on the fate of selectively advantageous mutations may help with explaining genetic diversity in natural highly fecund populations possibly evolving under sweepstakes reproduction.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030569
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 570: A Multilevel Heterogeneous ADMM Algorithm
for Elliptic Optimal Control Problems with L1-Control Cost
Authors: Xiaotong Chen, Xiaoliang Song, Zixuan Chen, Lijun Xu
First page: 570
Abstract: In this paper, elliptic optimal control problems with L1-control cost and box constraints on the control are considered. To numerically solve the optimal control problems, we use the First optimize, then discretize approach. We focus on the inexact alternating direction method of multipliers (iADMM) and employ the standard piecewise linear finite element approach to discretize the subproblems in each iteration. However, in general, solving the subproblems is expensive, especially when the discretization is at a fine level. Motivated by the efficiency of the multigrid method for solving large-scale problems, we combine the multigrid strategy with the iADMM algorithm. Instead of fixing the mesh size before the computation process, we propose the strategy of gradually refining the grid. Moreover, to overcome the difficulty whereby the L1-norm does not have a decoupled form, we apply nodal quadrature formulas to approximately discretize the L1-norm and L2-norm. Based on these strategies, an efficient multilevel heterogeneous ADMM (mhADMM) algorithm is proposed. The total error of the mhADMM consists of two parts: the discretization error resulting from the finite-element discretization and the iteration error resulting from solving the discretized subproblems. Both errors can be regarded as the error of inexactly solving infinite-dimensional subproblems. Thus, the mhADMM can be regarded as the iADMM in function space. Furthermore, theoretical results on the global convergence, as well as the iteration complexity results o(1/k) for the mhADMM, are given. Numerical results show the efficiency of the mhADMM algorithm.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030570
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 571: Time-Transient Optimization of
Electricity and Fresh Water Cogeneration Cycle Using Gas Fuel and Solar
Energy
Authors: Khosrow Hemmatpour, Ramin Ghasemiasl, Mehrdad Malekzadeh dirin, Mohammad Amin Javadi
First page: 571
Abstract: In this study, a cogeneration cycle in a time-transient state is investigated and optimized. A quasi-equilibrium state is assumed because of the small time increments. Air temperature and solar power are calculated hourly. The cycle is considered in terms of energy, exergy, and economic and environmental analyses. Increasing the net present value (the difference between the present value of the cash inflows and outflows over a period of time) and reducing exergy destruction are selected as two optimization objective functions. The net present value is calculated for the period of 20 years of operation according to the operation parameters. The optimization variables are selected in such a way that one important variable is selected from each system. To optimize the cycle, the particle swarm optimization method is used. The number of particles used in this method is calculated using the trial-and-error method. This cycle is optimized using 13 particles and 42 iterations. After optimization, the energy efficiency increased by 0.5%, the exergy efficiency increased by 0.25%, and the exergy destruction decreased by 1% compared to the cycle with existing parameters.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030571
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 572: Phase-Space Modeling and Control of
Robots in the Screw Theory Framework Using Geometric Algebra
Authors: Jesús Alfonso Medrano-Hermosillo, Ricardo Lozoya-Ponce, Abraham Efraím Rodriguez-Mata, Rogelio Baray-Arana
First page: 572
Abstract: The following paper talks about the dynamic modeling and control of robot manipulators using Hamilton’s equations in the screw theory framework. The difference between the proposed work with diverse methods in the literature is the ease of obtaining the laws of control directly with screws and co-screws, which is considered modern robotics by diverse authors. In addition, geometric algebra (GA) is introduced as a simple and iterative tool to obtain screws and co-screws. On the other hand, such as the controllers, the Hamiltonian equations of motion (in the phase space) are developed using co-screws and screws, which is a novel approach to compute the dynamic equations for robots. Regarding the controllers, two laws of control are designed to ensure the error’s convergence to zero. The controllers are computed using the traditional feedback linearization and the sliding mode control theory. The first one is easy to program and the second theory provides robustness for matched disturbances. On the other hand, to prove the stability of the closed loop system, different Lyapunov functions are computed with co-screws and screws to guarantee its convergence to zero. Finally, diverse simulations are illustrated to show a comparison of the designed controllers with the most famous approaches.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030572
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 573: An Unsupervised Rapid Network Alignment
Framework via Network Coarsening
Authors: Lei Zhang, Feng Qian, Jie Chen, Shu Zhao
First page: 573
Abstract: Network alignment aims to identify the correspondence of nodes between two or more networks. It is the cornerstone of many network mining tasks, such as cross-platform recommendation and cross-network data aggregation. Recently, with the development of network representation learning techniques, researchers have proposed many embedding-based network alignment methods. The effect is better than traditional methods. However, several issues and challenges remain for network alignment tasks, such as lack of labeled data, mapping across network embedding spaces, and computational efficiency. Based on the graph neural network (GNN), we propose the URNA (unsupervised rapid network alignment) framework to achieve an effective balance between accuracy and efficiency. There are two phases: model training and network alignment. We exploit coarse networks to accelerate the training of GNN after first compressing the original networks into small networks. We also use parameter sharing to guarantee the consistency of embedding spaces and an unsupervised loss function to update the parameters. In the network alignment phase, we first use a once-pass forward propagation to learn node embeddings of original networks, and then we use multi-order embeddings from the outputs of all convolutional layers to calculate the similarity of nodes between the two networks via vector inner product for alignment. Experimental results on real-world datasets show that the proposed method can significantly reduce running time and memory requirements while guaranteeing alignment performance.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030573
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 574: Optimum Solutions of Systems of
Differential Equations via Best Proximity Points in b-Metric Spaces
Authors: Basit Ali, Arshad Ali Khan, Manuel De la De la Sen
First page: 574
Abstract: This paper deals with the existence of an optimum solution of a system of ordinary differential equations via the best proximity points. In order to obtain the optimum solution, we have developed the best proximity point results for generalized multivalued contractions of b-metric spaces. Examples are given to illustrate the main results and to show that the new results are the proper generalization of some existing results in the literature.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030574
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 575: Research of the Solutions Proximity of
Linearized and Nonlinear Problems of the Biogeochemical Process Dynamics
in Coastal Systems
Authors: Alexander Sukhinov, Yulia Belova, Natalia Panasenko, Valentina Sidoryakina
First page: 575
Abstract: The article considers a non-stationary three-dimensional spatial mathematical model of biological kinetics and geochemical processes with nonlinear coefficients and source functions. Often, the step of analytical study in models of this kind is skipped. The purpose of this work is to fill this gap, which will allow for the application of numerical modeling methods to a model of biogeochemical cycles and a computational experiment that adequately reflects reality. For this model, an initial-boundary value problem is posed and its linearization is carried out; for all the desired functions, their final spatial distributions for the previous time step are used. As a result, a chain of initial-boundary value problems is obtained, connected by initial–final data at each step of the time grid. To obtain inequalities that guarantee the convergence of solutions of a chain of linearized problems to the solution of the original nonlinear problems, the energy method, Gauss’s theorem, Green’s formula, and Poincaré’s inequality are used. The scientific novelty of this work lies in the proof of the convergence of solutions of a chain of linearized problems to the solution of the original nonlinear problems in the norm of the Hilbert space L2 as the time step τ tends to zero at the rate O(τ).
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030575
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 576: A New COVID-19 Pandemic Model Including
the Compartment of Vaccinated Individuals: Global Stability of the
Disease-Free Fixed Point
Authors: Isra Al-Shbeil, Noureddine Djenina, Ali Jaradat, Abdallah Al-Husban, Adel Ouannas, Giuseppe Grassi
First page: 576
Abstract: Owing to the COVID-19 pandemic, which broke out in December 2019 and is still disrupting human life across the world, attention has been recently focused on the study of epidemic mathematical models able to describe the spread of the disease. The number of people who have received vaccinations is a new state variable in the COVID-19 model that this paper introduces to further the discussion of the subject. The study demonstrates that the proposed compartment model, which is described by differential equations of integer order, has two fixed points, a disease-free fixed point and an endemic fixed point. The global stability of the disease-free fixed point is guaranteed by a new theorem that is proven. This implies the disappearance of the pandemic, provided that an inequality involving the vaccination rate is satisfied. Finally, simulation results are carried out, with the aim of highlighting the usefulness of the conceived COVID-19 compartment model.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030576
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 577: Common Fixed Point of Two L2 Operators
with Convergence Analysis and Application
Authors: Cristina Calineata, Cristian Ciobanescu, Teodor Turcanu
First page: 577
Abstract: This article introduces a new numerical algorithm for approximating the solution of the common fixed point problem for two operators defined on CAT(0) spaces, belonging to the class L2, which was very recently introduced. The main results refer to Δ and strong convergence of the sequence generated by the new algorithm. A distinct feature of the adopted approach is the use of equivalent sequences.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030577
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 578: Learning Heterogeneous Graph Embedding
with Metapath-Based Aggregation for Link Prediction
Authors: Chengdong Zhang, Keke Li, Shaoqing Wang, Bin Zhou, Lei Wang, Fuzhen Sun
First page: 578
Abstract: Along with the growth of graph neural networks (GNNs), many researchers have adopted metapath-based GNNs to handle complex heterogeneous graph embedding. The conventional definition of a metapath only distinguishes whether there is a connection between nodes in the network schema, where the type of edge is ignored. This leads to inaccurate node representation and subsequently results in suboptimal prediction performance. In heterogeneous graphs, a node can be connected by multiple types of edges. In fact, each type of edge represents one kind of scene. The intuition is that if the embedding of nodes is trained under different scenes, the complete representation of nodes can be obtained by organically combining them. In this paper, we propose a novel definition of a metapath whereby the edge type, i.e., the relation between nodes, is integrated into it. A heterogeneous graph can be considered as the compound of multiple relation subgraphs from the view of a novel metapath. In different subgraphs, the embeddings of a node are separately trained by encoding and aggregating the neighbors of the intrapaths, which are the instance levels of a novel metapath. Then, the final embedding of the node is obtained by the use of the attention mechanism which aggregates nodes from the interpaths, which is the semantic level of the novel metapaths. Link prediction is a downstream task by which to evaluate the effectiveness of the learned embeddings. We conduct extensive experiments on three real-world heterogeneous graph datasets for link prediction. The empirical results show that the proposed model outperforms the state-of-the-art baselines; in particular, when comparing it to the best baseline, the F1 metric is increased by 10.35% over an Alibaba dataset.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030578
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 579: Parameter Estimation and Hypothesis
Testing of The Bivariate Polynomial Ordinal Logistic Regression Model
Authors: Marisa Rifada, Vita Ratnasari, Purhadi Purhadi
First page: 579
Abstract: Logistic regression is one of statistical methods that used to analyze the correlation between categorical response variables and predictor variables which are categorical or continuous. Many studies on logistic regression have been carried out by assuming that the predictor variable and its logit link function have a linear relationship. However, in several cases it was found that the relationship was not always linear, but could be quadratic, cubic, or in the form of other curves, so that the assumption of linearity was incorrect. Therefore, this study will develop a bivariate polynomial ordinal logistic regression (BPOLR) model which is an extension of ordinal logistic regression, with two correlated response variables in which the relationship between the continuous predictor variable and its logit is modeled as a polynomial form. There are commonly two correlated response variables in scientific research. In this study, each response variable used consisted of three categories. This study aims to obtain parameter estimators of the BPOLR model using the maximum likelihood estimation (MLE) method, obtain test statistics of parameters using the maximum likelihood ratio test (MLRT) method, and obtain algorithms of estimating and hypothesis testing for parameters of the BPOLR model. The results of the first partial derivatives are not closed-form, thus, a numerical optimization such as the Berndt–Hall–Hall–Hausman (BHHH) method is needed to obtain the maximum likelihood estimator. The distribution statistically test is followed the Chi-square limit distribution, asymptotically.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030579
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 580: Deterioration Control Decision Support
Authors: Mrudul Y. Jani, Heta A. Patel, Amrita Bhadoriya, Urmila Chaudhari, Mohamed Abbas, Malak S. Alqahtani
First page: 580
Abstract: The deterioration rate is a significant aspect of perishable goods. Since perishable items will always deteriorate, there are effective methods for reducing the rate of deterioration. Furthermore, in the existing inventory control literature, the deterioration rate is often viewed as an exogenous component. Keeping this problem in mind, this article develops the perishable inventory control system from the retailer’s perspective in which: (i) the deterioration rate is a controllable factor and suggests a new fresh quality technology (FQT) indicator, (ii) demand is determined by the perishable product’s quality, that is controlled by its rate of deterioration, (iii) the credit duration is predefined, and (iv) shortages are expected. The key goal is to demonstrate that there is an ideal quantity of the order that minimizes the retailer’s overall cost in terms of cycle time and deterioration rate. Finally, theoretical results are validated by solving two numerical illustrations and conducting a sensitivity analysis of the main factors resulting from the following managerial implications: (i) if the range of deterioration is between zero and one then the retailer should invest in the preservation factor to preserve the perishable product and if greater than one the retailer should not invest in the preservation factor, (ii) credit period significantly reduces the total cost. Hence, this trade credit strategy is more beneficial to the model.
Citation: Mathematics
PubDate: 2023-01-21
DOI: 10.3390/math11030580
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 581: A Distributed Blocking Flowshop
Scheduling with Setup Times Using Multi-Factory Collaboration Iterated
Greedy Algorithm
Authors: Chenyao Zhang, Yuyan Han, Yuting Wang, Junqing Li, Kaizhou Gao
First page: 581
Abstract: As multi-factory production models are more widespread in modern manufacturing systems, a distributed blocking flowshop scheduling problem (DBFSP) is studied in which no buffer between adjacent machines and setup time constraints are considered. To address the above problem, a mixed integer linear programming (MILP) model is first constructed, and its correctness is verified. Then, an iterated greedy-algorithm-blending multi-factory collaboration mechanism (mIG) is presented to optimize the makespan criterion. In the mIG algorithm, a rapid evaluation method is designed to reduce the time complexity, and two different iterative processes are selected by a certain probability. In addition, collaborative interactions between cross-factory and inner-factory are considered to further improve the exploitation and exploration of mIG. Finally, the 270 tests showed that the average makespan and RPI values of mIG are 1.93% and 78.35% better than the five comparison algorithms on average, respectively. Therefore, mIG is more suitable to solve the studied DBFSP_SDST.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030581
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 582: Stabilization of Stochastic Dynamical
Systems of a Random Structure with Markov Switches and Poisson
Perturbations
Authors: Taras Lukashiv, Yuliia Litvinchuk, Igor V. Malyk, Anna Golebiewska, Petr V. Nazarov
First page: 582
Abstract: An optimal control for a dynamical system optimizes a certain objective function. Here, we consider the construction of an optimal control for a stochastic dynamical system with a random structure, Poisson perturbations and random jumps, which makes the system stable in probability. Sufficient conditions of the stability in probability are obtained, using the second Lyapunov method, in which the construction of the corresponding functions plays an important role. Here, we provide a solution to the problem of optimal stabilization in a general case. For a linear system with a quadratic quality function, we give a method of synthesis of optimal control based on the solution of Riccati equations. Finally, in an autonomous case, a system of differential equations was constructed to obtain unknown matrices that are used for the construction of an optimal control. The method using a small parameter is justified for the algorithmic search of an optimal control. This approach brings a novel solution to the problem of optimal stabilization for a stochastic dynamical system with a random structure, Markov switches and Poisson perturbations.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030582
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 583: Two-Step Cluster Analysis of Passenger
Mobility Segmentation during the COVID-19 Pandemic
Authors: Veronika Harantová, Jaroslav Mazanec, Vladimíra Štefancová, Jaroslav Mašek, Hana Brůhová Foltýnová
First page: 583
Abstract: In this paper, we analyse the specific behaviour of passengers in personal transport commuting to work or school during the COVID-19 pandemic, based on a sample of respondents from two countries. We classified the commuters based on a two-step cluster analysis into groups showing the same characteristics. Data were obtained from an online survey, and the total sample size consists of 2000 respondents. We used five input variables, dividing the total sample into five clusters using a two-step cluster analysis. We observed significant differences between gender, status, and car ownership when using public transport, cars, and other alternative means of transportation for commuting to work and school. We also examined differences between individual groups with the same socioeconomic and socio-demographic factors. In total, the respondents were classified into five clusters, and the results indicate that there are differences between gender and status. We found that ownership of a prepaid card for public transport and social status are the most important factors, as they reach a significance level of 100%, unlike compared to other factors with importance ranging from 60 to 80%. Moreover, the results demonstrate that prepaid cards are preferred mainly by female students. Understanding these factors can help in planning transport policy by knowing the habits of users.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030583
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 584: Analytical Description of the Diffusion
in a Cellular Automaton with the Margolus Neighbourhood in Terms of the
Two-Dimensional Markov Chain
Authors: Anton E. Kulagin, Alexander V. Shapovalov
First page: 584
Abstract: The one-parameter two-dimensional cellular automaton with the Margolus neighbourhood is analyzed based on considering the projection of the stochastic movements of a single particle. Introducing the auxiliary random variable associated with the direction of the movement, we reduce the problem under consideration to the study of a two-dimensional Markov chain. The master equation for the probability distribution is derived and solved exactly using the probability-generating function method. The probability distribution is expressed analytically in terms of Jacobi polynomials. The moments of the obtained solution allowed us to derive the exact analytical formula for the parametric dependence of the diffusion coefficient in the two-dimensional cellular automaton with the Margolus neighbourhood. Our analytic results agree with earlier empirical results of other authors and refine them. The results are of interest for the modelling two-dimensional diffusion using cellular automata especially for the multicomponent problem.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030584
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 585: An Improved DEA Prospect Cross-Efficiency
Evaluation Method and Its Application in Fund Performance Analysis
Authors: Yangxue Ning, Yan Zhang, Guoqiang Wang
First page: 585
Abstract: It is well known that a traditional data envelopment analysis (DEA) cross-efficiency evaluation model assumes that the decision-makers are completely rational, which causes the evaluation results to be inconsistent with the actual situation. To remedy this, in this paper, we propose an improved DEA prospect cross-efficiency evaluation method called EPCE model. The EPCE model captures the risk attitude of decision-makers and retains the decision information in the evaluation process. In particular, this new approach generates a more practical, realistic weighting scheme to measure the cross-efficiency and provides a reliable technique for ordering the decision-making units (DMUs) from the perspective of multi-criteria decision analysis. Finally, to demonstrate the validity and reliability of the proposed approach, we show an empirical analysis of mutual fund investment selection from Chinese fund market.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030585
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 586: Identification of Cross-Country Fault
with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet
Transform
Authors: Pampa Sinha, Kaushik Paul, Chidurala Saiprakash, Almoataz Y. Abdelaziz, Ahmed I. Omar, Chun-Lien Su, Mahmoud Elsisi
First page: 586
Abstract: The transmission lines of an electricity system are susceptible to a wide range of unusual fault conditions. The transmission line, the longest part of the electricity grid, sometimes passes through wooded areas. Storms, cyclones, and poor vegetation management (including tree cutting) increase the risk of cross-country faults (CCFs) and high-impedance fault (HIF) syndrome in these regions. Recognizing and classifying CCFs associated with HIF syndrome is the most challenging part of the project. This study extracted signal characteristics associated with CCF and HIF syndrome using the Tunable Q Wavelet Transform (TQWT). An adaptive tunable Q-factor wavelet transform (TQWT) based feature-extraction approach for CCHIF fault signals with high impact, short response period, and broad resonance frequency bandwidth was presented. In the first part, the time–frequency distribution of the vibration signal is used to determine the distinctive frequency range. Adaptive optimal matching of the impact characteristic components in the vibration signal was achieved by optimizing the number of decomposition layers, quality factor, and redundancy of TQWT based on the characteristic frequency band. In the last, the TQWT inverse transform was utilized to recreate the best sub-band to boost its weak impact characteristics. The effectiveness of the approach is confirmed by simulation and experimental findings in signal processing. The best decomposition level for signature features that can be extracted has been decided by Minimum Description length (MDL). The IEEE 39-bus system is used to test the suggested approach with reactor switching and the Ferranti effect.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030586
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 587: Analysis of the Performance of Chamfered
Finite-Length Journal Bearings under Dynamic Loads
Authors: Hazim U. Jamali, Hakim S. Sultan, Oday I. Abdullah, Adnan Naji Jameel Al-Tamimi, Mahmood Shaker Albdeiri, Alessandro Ruggiero, Zahraa A. AL-Dujaili
First page: 587
Abstract: Misalignment is one of the most common challenges that the normal operation of journal bearings faces. This type of problem may be the result of a wide range of reasons, such as bearing wear, shaft deformation, and errors related to the manufacturing and installation process. The main undesirable consequences of the misalignment, such as pressure rise and lubricant film reduction, are concentrated on the bearing edges. Therefore, chamfering the bearing edges reduces such misalignment-related drawbacks. This work presents a novel numerical solution to the problem of finite-length journal bearing considering edge chamfering. This solution involves the determination of the levels of lubricant layer thickness and pressure distribution in addition to the journal trajectory under impact load with the related stability limits. The finite difference method is used in this solution, and the equations of motion are also solved numerically using the Runge–Kutta method. The Results of this novel analysis show that chamfering the bearing edges increases the film thickness and reduces pressure spikes associated with the system operation under the case of 3D misalignment. Furthermore, the chamfered bearing shows a wide stability range under impact loads, where the normal bearing is unstable as the critical speed increases by 26.98%, which has positive consequences on the journal’s trajectory.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030587
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 588: On Some Expansion Formulas for Products
of Jacobi’s Theta Functions
Authors: Hong-Cun Zhai, Jian Cao, Sama Arjika
First page: 588
Abstract: In this paper, we establish several expansion formulas for products of the Jacobi theta functions. As applications, we derive some expressions of the powers of (q;q)∞ by using these expansion formulas.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030588
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 589: Design Optimization of a Synchronous
Homopolar Motor with Ferrite Magnets for Subway Train
Authors: Vladimir Dmitrievskii, Vladimir Prakht, Vadim Kazakbaev
First page: 589
Abstract: Brushless synchronous homopolar machines (SHM) have long been used as highly reliable motors and generators with an excitation winding on the stator. However, a significant disadvantage that limits their use in traction applications is the reduced specific torque due to the incomplete use of the rotor surface. One possible way to improve the torque density of SHMs is to add inexpensive ferrite magnets in the rotor slots. This paper presents the results of optimizing the performances of an SHM with ferrite magnets for a subway train, considering the timing diagram of train movement. A comparison of its characteristics with an SHM without permanent magnets is also presented. When using the SHM with ferrite magnets, a significant reduction in the dimensions and weight of the motor, as well as power loss, is shown.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030589
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 590: A Multi Parameter Forecasting for Stock
Time Series Data Using LSTM and Deep Learning Model
Authors: Shahzad Zaheer, Nadeem Anjum, Saddam Hussain, Abeer D. Algarni, Jawaid Iqbal, Sami Bourouis, Syed Sajid Ullah
First page: 590
Abstract: Financial data are a type of historical time series data that provide a large amount of information that is frequently employed in data analysis tasks. The question of how to forecast stock prices continues to be a topic of interest for both investors and financial professionals. Stock price forecasting is quite challenging because of the significant noise, non-linearity, and volatility of time series data on stock prices. The previous studies focus on a single stock parameter such as close price. A hybrid deep-learning, forecasting model is proposed. The model takes the input stock data and forecasts two stock parameters close price and high price for the next day. The experiments are conducted on the Shanghai Composite Index (000001), and the comparisons have been performed by existing methods. These existing methods are CNN, RNN, LSTM, CNN-RNN, and CNN-LSTM. The generated result shows that CNN performs worst, LSTM outperforms CNN-LSTM, CNN-RNN outperforms CNN-LSTM, CNN-RNN outperforms LSTM, and the suggested single Layer RNN model beats all other models. The proposed single Layer RNN model improves by 2.2%, 0.4%, 0.3%, 0.2%, and 0.1%. The experimental results validate the effectiveness of the proposed model, which will assist investors in increasing their profits by making good decisions.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030590
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 591: Existence of Self-Excited and Hidden
Attractors in the Modified Autonomous Van der Pol-Duffing Systems
Authors: A. E. Matouk, T. N. Abdelhameed, D. K. Almutairi, M. A. Abdelkawy, M. A. E. Herzallah
First page: 591
Abstract: This study investigates the multistability phenomenon and coexisting attractors in the modified Autonomous Van der Pol-Duffing (MAVPD) system and its fractional-order form. The analytical conditions for existence of periodic solutions in the integer-order system via Hopf bifurcation are discussed. In addition, conditions for approximating the solutions of the fractional version to periodic solutions are obtained via the Hopf bifurcation theory in fractional-order systems. Moreover, the technique for hidden attractors localization in the integer-order MAVPD is provided. Therefore, motivated by the previous discussion, the appearances of self-excited and hidden attractors are explained in the integer- and fractional-order MAVPD systems. Phase transition of quasi-periodic hidden attractors between the integer- and fractional-order MAVPD systems is observed. Throughout this study, the existence of complex dynamics is also justified using some effective numerical measures such as Lyapunov exponents, bifurcation diagrams and basin sets of attraction.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030591
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 592: Effect of Macrophages and Latent
Reservoirs on the Dynamics of HTLV-I and HIV-1 Coinfection
Authors: A. M. Elaiw, N. H. AlShamrani, E. Dahy, A. A. Abdellatif, Aeshah A. Raezah
First page: 592
Abstract: Human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) are two retroviruses that have a similar fashion of transmission via sharp objects contaminated by viruses, transplant surgery, transfusion, and sexual relations. Simultaneous infections with HTLV-I and HIV-1 usually occur in areas where both viruses have become endemic. CD4+T cells are the main targets of HTLV-I, while HIV-1 can infect CD4+T cells and macrophages. It is the aim of this study to develop a model of HTLV-I and HIV-1 coinfection that describes the interactions of nine compartments: susceptible cells of both CD4+T cells and macrophages, HIV-1-infected cells that are latent/active in both CD4+T cells and macrophages, HTLV-I-infected CD4+T cells that are latent/active, and free HIV-1 particles. The well-posedness, existence of equilibria, and global stability analysis of our model are investigated. The Lyapunov function and LaSalle’s invariance principle were used to study the global asymptotic stability of all equilibria. The theoretically predicted outcomes were verified by utilizing numerical simulations. The effect of including the macrophages and latent reservoirs in the HTLV-I and HIV-1 coinfection model is discussed. We show that the presence of macrophages makes a coinfection model more realistic when the case of the coexistence of HIV-1 and HTLV-I is established. Moreover, we have shown that neglecting the latent reservoirs in HTLV-I and HIV-1 coinfection modeling will lead to the design of an overflow of anti-HIV-1 drugs.
Citation: Mathematics
PubDate: 2023-01-22
DOI: 10.3390/math11030592
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 593: Highly Accurate and Efficient Time
Integration Methods with Unconditional Stability and Flexible Numerical
Dissipation
Authors: Yi Ji, Yufeng Xing
First page: 593
Abstract: This paper constructs highly accurate and efficient time integration methods for the solution of transient problems. The motion equations of transient problems can be described by the first-order ordinary differential equations, in which the right-hand side is decomposed into two parts, a linear part and a nonlinear part. In the proposed methods of different orders, the responses of the linear part at the previous step are transferred by the generalized Padé approximations, and the nonlinear part’s responses of the previous step are approximated by the Gauss–Legendre quadrature together with the explicit Runge–Kutta method, where the explicit Runge–Kutta method is used to calculate function values at quadrature points. For reducing computations and rounding errors, the 2m algorithm and the method of storing an incremental matrix are employed in the calculation of the generalized Padé approximations. The proposed methods can achieve higher-order accuracy, unconditional stability, flexible dissipation, and zero-order overshoots. For linear transient problems, the accuracy of the proposed methods can reach 10−16 (computer precision), and they enjoy advantages both in accuracy and efficiency compared with some well-known explicit Runge–Kutta methods, linear multi-step methods, and composite methods in solving nonlinear problems.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030593
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 594: Pricing of Arithmetic Average Asian
Option by Combining Variance Reduction and Quasi-Monte Carlo Method
Authors: Lingling Xu, Hongjie Zhang, Fu Lee Wang
First page: 594
Abstract: Financial derivatives have developed rapidly over the past few decades due to their risk-averse nature, with options being the preferred financial derivatives due to their flexible contractual mechanisms, particularly Asian options. The Black–Scholes stock option pricing model is often used in conjunction with Monte Carlo simulations for option pricing. However, the Black–Scholes model assumes that the volatility of asset returns is constant, which does not square with practical financial markets. Additionally, Monte Carlo simulation suffers from slow error convergence. To address these issues, we first correct the asset volatility in the Black–Scholes model using a GARCH model. Then, the low error convergence rate of the Monte Carlo method is improved using variance reduction techniques. Meanwhile, the quasi-Monte Carlo approach based on low discrepancy sequences is used to refine the error convergence rate. We also provide a simulation experiment and result analysis to validate the effectiveness of our proposed method.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030594
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 595: Evaluating the Performance of Synthetic
Double Sampling np Chart Based on Expected Median Run Length
Authors: Moi Hua Tuh, Cynthia Mui Lian Kon, Hong Siang Chua, Man Fai Lau, Yee Hui Robin Chang
First page: 595
Abstract: To keep an eye on the status of high-quality processes for fraction nonconforming, the synthetic double sampling (SDS) np chart is a helpful tool. The SDS np chart is a hybrid between the double sampling (DS) np chart and the conforming run length (CRL) chart. The performance of a control chart is typically judged solely using the average run length (ARL). However, as the shape of the run length (RL) distribution varies with the magnitude of the shift in the process fraction nonconforming, the ARL no longer provides clear interpretation of a chart’s performance. Subsequently, enhanced DS np charts that use median run length (MRL) and expected median run length (EMRL) measures, including SDS np with MRL have recently been proposed for addressing this setback. To broaden the functionality of SDS np, in this work, the unexplored use of EMRL as alternative performance measure is developed by means of Markov chain model. Additionally, in both the zero-state (ZS) and steady-state (SS) modes, the novel optimal designs algorithms are described for computing the optimal charting parameters of the SDS np chart, for both MRL1 and EMRL1 minimizations, without any unfavourable feature of bilateral sensitivity. Both the MRL and EMRL performances of SDS np, synthetic np, and DS np charts are compared. Optimal designs charting parameters and sensitivity analyses are provided to aid the practical application of SDS np chart.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030595
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 596: Exact Closed-Form Solution for the
Oscillator with a New Type of Mixed Nonlinear Restitution Force
Authors: Livija Cveticanin
First page: 596
Abstract: This paper shows an oscillator with a spring made of material where the stress is a function not only of strain but also strain rate. The corresponding restitution force is of strong nonlinear monomial type and is the product of displacement and velocity of any order. The mathematical model of the oscillator is a homogenous strong nonlinear second-order differential equation with an integer- or non-integer-order mixed term. In the paper, an analytical procedure for solving this new type of strong nonlinear equation is developed. The approximate solution is assumed as the perturbed version of the exact solution in the form of a sine Ateb function. As a result, it is obtained that the amplitude, period, and frequency of vibration depend not only on the coefficient and order of nonlinearity, but also on the initial velocity. The procedure is tested on two examples: oscillator perturbed with small linear damping and small linear displacement functions. The analytically obtained results are compared with the exact numerical ones and show good agreement. It is concluded that the mathematical model and also the procedure developed in the paper would be convenient for prediction of motion for this type of oscillator without necessary experimental testing.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030596
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 597: Coexisting Attractors and Multistate
Noise-Induced Intermittency in a Cycle Ring of Rulkov Neurons
Authors: Irina A. Bashkirtseva, Alexander N. Pisarchik, Lev B. Ryashko
First page: 597
Abstract: We study dynamics of a unidirectional ring of three Rulkov neurons coupled by chemical synapses. We consider both deterministic and stochastic models. In the deterministic case, the neural dynamics transforms from a stable equilibrium into complex oscillatory regimes (periodic or chaotic) when the coupling strength is increased. The coexistence of complete synchronization, phase synchronization, and partial synchronization is observed. In the partial synchronization state either two neurons are synchronized and the third is in antiphase, or more complex combinations of synchronous and asynchronous interaction occur. In the stochastic model, we observe noise-induced destruction of complete synchronization leading to multistate intermittency between synchronous and asynchronous modes. We show that even small noise can transform the system from the regime of regular complete synchronization into the regime of asynchronous chaotic oscillations.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030597
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 598: A Hybrid Marine Predator Sine Cosine
Algorithm for Parameter Selection of Hybrid Active Power Filter
Authors: Shoyab Ali, Annapurna Bhargava, Akash Saxena, Pavan Kumar
First page: 598
Abstract: Power quality issues are handled very well by filter technologies. In recent years, the advancement of hybrid active power filters (HAPF) has been enhanced due to ease of control and flexibility as compared to other filter technologies. These filters are a beneficial asset for a power producer that requires a smooth filtered output of power. However, the design of these filters is a daunting task to perform. Often, metaheuristic algorithms are employed for dealing with this nonlinear optimization problem. In this work, a new hybrid metaheuristic algorithm (Marine Predator Algorithm and Sine Cosine Algorithm) has been proposed for selecting the best parameters for HAPF. The comparison of different algorithms for obtaining the HAPF parameters is also performed to show case efficacy of the proposed hybrid algorithm. It can be concluded that the proposed algorithm produces robust results and can be a potential tool for estimating the HAPF parameters. The confirmation of the performance of the proposed algorithm is conducted with the results of fitness statistical results, boxplots, and different numerical analyses.
Citation: Mathematics
PubDate: 2023-01-23
DOI: 10.3390/math11030598
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 599: Generation of Boxes and Permutations
Using a Bijective Function and the Lorenz Equations: An Application to
Color Image Encryption
Authors: Víctor Manuel Silva-García, Rolando Flores-Carapia, Manuel Alejandro Cardona-López, Miguel Gabriel Villarreal-Cervantes
First page: 599
Abstract: Some images that contain sensitive information and travel through the network require security. Therefore, a symmetric cryptosystem that encrypts images and resists known attacks is developed. Subsequently, in this work, an encryption algorithm known as Image Cipher utilizing Lorenz equation and a Bijective Function—ICLEBF are proposed. In the proposal, the Lorenz equations and the Bijective function are used to generate boxes, the permutation, and schedule keys, considering that all these elements are different in each encryption process. The encryption procedure consists of 14 rounds, where a different box is applied in each round. In this type of algorithm, the impact of quantum computers will be less forceful and can be useful for that epoch. On the other hand, the quality of the encrypted images and the loss of sharpness in decoded images with damage are measured. In addition, an attack from five types of noise (one of which is a developed proposal) is carried out by applying it to encrypted images. Finally, the results of the proposed ICLEBF are compared with other recent image encryption algorithms, including the Advanced Encryption Standard. As a result, this proposal resists known attacks and others that the current standard does not support.
Citation: Mathematics
PubDate: 2023-01-24
DOI: 10.3390/math11030599
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 600: Time-Varying Pseudoinversion Based on
Full-Rank Decomposition and Zeroing Neural Networks
Authors: Hadeel Alharbi, Houssem Jerbi, Mourad Kchaou, Rabeh Abbassi, Theodore E. Simos, Spyridon D. Mourtas, Vasilios N. Katsikis
First page: 600
Abstract: The computation of the time-varying matrix pseudoinverse has become crucial in recent years for solving time-varying problems in engineering and science domains. This paper investigates the issue of calculating the time-varying pseudoinverse based on full-rank decomposition (FRD) using the zeroing neural network (ZNN) method, which is currently considered to be a cutting edge method for calculating the time-varying matrix pseudoinverse. As a consequence, for the first time in the literature, a new ZNN model called ZNNFRDP is introduced for time-varying pseudoinversion and it is based on FRD. FourFive numerical experiments investigate and confirm that the ZNNFRDP model performs as well as, if not better than, other well-performing ZNN models in the calculation of the time-varying pseudoinverse. Additionally, theoretical analysis and numerical findings have both supported the effectiveness of the proposed model.
Citation: Mathematics
PubDate: 2023-01-24
DOI: 10.3390/math11030600
Issue No: Vol. 11, No. 3 (2023)
- Mathematics, Vol. 11, Pages 601: Global Value Chains and Industry 4.0 in
the Context of Lean Workplaces for Enhancing Company Performance and Its
Comprehension via the Digital Readiness and Expertise of Workforce in the
V4 Nations
Authors: Tomas Kliestik, Marek Nagy, Katarina Valaskova
First page: 601
Abstract: Industry 4.0 affects nearly every aspect of life by making it more technologically advanced, creative, environmentally friendly and ultimately, more interconnected. It also represents the beginning of the interconnectedness and metaverse associated with Industry 5.0. This issue is becoming decisive for advancement in all areas of life, including science. The primary goal of this study is to concisely explain how current Industry 4.0 trends might interact with existing work systems in global value chains to accelerate their operational activity in the context of firms from the Visegrad Four (V4) nations. Through an examination of the digital abilities in these nations, the purpose of the study is also to demonstrate how well citizens, employees, and end users are able to comprehend the problem at hand. The most recent resources for the topics are covered in the first section of the work. The next one uses graphic analysis and mutual comparison methods, generally comparing existing data over time; it is secondary research, and through these methods the Industry 4.0 applications can significantly speed up the work process itself when compared to the traditional lean process, primarily because of its digital structure. It is difficult to predict which of the V4 will be digitally prepared, as the precedent shifts are based on distinct indicators; therefore, it is crucial that all V4 nations expand their digital adaptability dramatically each year, primarily as a result of spending on scientific research, and education that is organised appropriately. The extra value of this effort may be attributed to how lean processes are intertwined with the Industry 4.0 trend’s digital experience, which already includes the Industry 5.0 trend’s artificial intelligence and metaverse, which represent the potential for further research in the future.
Citation: Mathematics
PubDate: 2023-01-24
DOI: 10.3390/math11030601
Issue No: Vol. 11, No. 3 (2023)