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Doubly salient permanent magnet machine (DSPMM), which is a branch of stator-Permanent Magnet (PM) machine, is becoming more and more attractive due to higher power density and fault-tolerant capability, better mechanical robustness, simpler rotor configuration, lower PM consumption and higher PM material utilization efficiency. Thus, it has great application potential in the fields of transportation electrification and renewable energy generation. However, due to the special doubly salient structure, PM flux-linkage and inductance have the same variation period, which would complicate the relationship between the current and torque, and bring difficulties in the modeling and control (even after Park's transformation). In order to solve these problems, this paper will develop, analyze and compare the different current waveforms which could theoretically reduce the torque ripple and the transformations which could decouple the model in the rotating stationary frame for a simplified DSPMM model neglecting the higher harmonics. Based on the mathematical analysis, this paper would provide a clear relationship between the current waveforms and the torque with the DSPMM parameters, and the possible transformation which could simplify the model and be used in the control system. [ABSTRACT FROM AUTHOR]

In this short paper, we look into a conclusion drawn by Alzalg (J Optim Theory Appl 169:32-49, 2016). We think the conclusion drawn in the paper is incorrect by pointing out three things. First, we provide a counterexample that the proposed inner product does not satisfy bilinearity. Secondly, we offer an argument why a pth-order cone cannot be self-dual under any reasonable inner product structure on $$\mathbb {R}^n$$ . Thirdly, even under the assumption that all elements operator commute, the inner product becomes an official inner product and the arbitrary-order cone can be shown as a symmetric cone, we think this condition is still unreasonable and very stringent so that the result can only be applied to very few cases. [ABSTRACT FROM AUTHOR]

Along with the significant growth of applications and facilities provided by the Internet of Things (IoT) in recent years, security challenges and related issues to privacy become considerable interest of researchers. On the other hand, the de facto IoT routing protocol for low-power and lossy networks called RPL is vulnerable to various types of routing attacks. Many researchers have investigated RPL security solutions focusing on effective detection of prevalent and destructive routing attacks such as blackhole attack, selective forwarding attack, rank attack and so on. Recent studies are proposing trust-based mechanisms with the aim of replacing traditional cryptography-based operations with lightweight security models in order to cover the inherent challenges of IoT devices, including energy and computational limitations. Therefore, in this paper, focusing on the problem of RPL vulnerability against well-known routing attacks, we have proposed a trust-based attack detection model, which investigates traffic behavior in different attack scenarios and detects malicious nodes relying on behavior deviation exactly at the same time as the start of any attack activity. Expected behavior is predicted by our learning model trained from the historical routing behavior pattern, using recurrent neural networks as a powerful deep learning method, which leads to attack detection with high-level accuracy and precision. Both mathematical analysis and simulation results on multiple RPL attack scenarios show clearly that the proposed trust-based defense mechanism is an effective approach capable of timely and precisely detection of routing behavior pattern deviation of malicious nodes exactly at the start time of the attack occurrence, which leads to attack detection and attacker identification based on trust scores extracted from the detected fluctuations between expected and real routing behavior patterns. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel protection scheme for N-qubit Greenberger–Horne–Zeilinger (GHZ) states against amplitude damping noise, using unilateral operations. The key innovation lies in the implementation of local operations on a single qubit, irrespective of the total number of qubits, thereby significantly reducing the operational complexity and resource requirements compared to existing methods. The scheme involves a unilateral rotation to transform the GHZ state into a less vulnerable configuration before exposing it to noise, followed by a weak measurement and another unilateral rotation to recover the initial state. We provide a comprehensive mathematical analysis of the proposed unilateral protection scheme, deriving expressions for both fidelity and success probability. The practical feasibility of our scheme is demonstrated through simulations using the Qiskit SDK, in which we provide the corresponding quantum circuit for performing the partial weak measurement used in our scheme. Comparative analysis with pioneer protection schemes reveals a substantial enhancement in success probability and fidelity for both GHZ and generalized GHZ states, emphasizing the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

The main goal of mathematical modeling and analysis of queueing systems is to understand the dynamic behavior of the underlying processes, enabling informed and intelligent management decisions. While the queueing systems with random factors have received extensive scrutiny, this paper introduces an uncertain queueing model that considers the belief degree of customer behavior. In this model, customers arrive in groups and the interarrival times and service times are treated as uncertain variables. To evaluate the performance of this proposed uncertain queueing model, the busy index and busy period are also discussed, and the analytical formulas and uncertainty distribution are derived respectively. Additionally, two numerical examples are also given to illustrate the obtained results. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for constructing high-order linearly implicit exponential integrators that conserve a quadratic invariant. This is then applied to the scalar auxiliary variable (SAV) approach. Quadratic invariants are significant objects that are present in various physical equations and also in computationally efficient conservative schemes for general invariants. For instance, the SAV approach converts the invariant into a quadratic form by introducing scalar auxiliary variables, which have been intensively studied in recent years. In this vein, Sato et al. (Appl. Numer. Math. 187, 71-88 2023) proposed high-order linearly implicit schemes that conserve a quadratic invariant. In this study, it is shown that their method can be effectively merged with the Lawson transformation, a technique commonly utilized in the construction of exponential integrators. It is also demonstrated that combining the constructed exponential integrators and the SAV approach yields schemes that are computationally less expensive. Specifically, the main part of the computational cost is the product of several matrix exponentials and vectors, which are parallelizable. Moreover, we conduct some mathematical analyses on the proposed schemes. [ABSTRACT FROM AUTHOR]

The Jacobi set of a bivariate scalar field is the set of points where the gradients of the two constituent scalar fields align with each other. It captures the regions of topological changes in the bivariate field. The Jacobi set is a bivariate analog of critical points, and may correspond to features of interest. In the specific case of time-varying fields and when one of the scalar fields is time, the Jacobi set corresponds to temporal tracks of critical points, and serves as a feature-tracking graph. The Jacobi set of a bivariate field or a time-varying scalar field is complex, resulting in cluttered visualizations that are difficult to analyze. This paper addresses the problem of Jacobi set simplification. Specifically, we use the time-varying scalar field scenario to introduce a method that computes a reduced Jacobi set. The method is based on a stability measure called robustness that was originally developed for vector fields and helps capture the structural stability of critical points. We also present a mathematical analysis for the method, and describe an implementation for 2D time-varying scalar fields. Applications to both synthetic and real-world datasets demonstrate the effectiveness of the method for tracking features. [ABSTRACT FROM AUTHOR]

Object detection is one of the core tasks of computer vision, and bounding box (bbox) regression is one of the basic tasks of object detection. In recent years of related research, bbox regression is often used in the Intersection over Union (IoU) loss and its improved version. In this paper, for the first time, we introduce the Dice coefficient into the regression loss calculation and propose a new measure which is superior to and can replace the IoU. We define three properties of the new measure and prove the theory by mathematical reasoning and analysis of the existing work. This paper also proposes the N-IoU regression loss family. And the superiority of the N-IoU regression loss family is proved by designing simulation experiments and comparative experiments. The main results of this paper are: (1) The proposed new measure is better than IoU which can be used to evaluate bounding box regression, and the three properties of the new measure can be used as a broad criterion for the design of regression loss functions; and (2) we propose N-IoU loss. The parameter n of N-IOU can be debugged, which can be widely adapted to different application scenarios with higher flexibility, and the regression performance is better. [ABSTRACT FROM AUTHOR]

A unique photonic technique has been suggested and explained for different types of waveform generation, the proposed technique employs double LiNbO3 Mach–Zehnder single drive cascading modulators for pulse shaping and responsive modulators for polarization. By ordering the incident light polarized states it can produce accordingly dual distinct Spectra on two components of orthogonal polarization. The desired waveform would be obtained by detecting the photocurrents from the photodetector. This paper describes the complete mathematical analysis of polarization dependent cascade Mach–Zehnder modulators to generate a variety of microwave forms. Comprehensive mathematical analyses including simulations have been presented, and therefore we have successfully developed as well as generated delta waveform, half-wave rectifier waveform, full-wave rectifier waveform, and square wave types waveform. At the end of the paper experimental analysis has been done for the proof of concept purpose while the experimental results of a variety of microwave waveforms are compared with theoretical ones. There are good agreements between theoretical results with experimental ones. [ABSTRACT FROM AUTHOR]

We show that the result on cyclic weak contractions of Harjani et al. (J. Nonlinear Sci. Appl. 6:279-284, ) holds without the assumption of compactness of the underlying space, and also without the assumption of continuity of the given mapping. [ABSTRACT FROM AUTHOR]

With this note, we want to open a discussion on the duality theory for Interval Optimization. We begin by showing that some duality results Wu ( J Optim Theory Appl 144:615-628, ) are useless. [ABSTRACT FROM AUTHOR]

Studying convection–diffusion problems of delayed type in physics helps us to understand transport phenomena and has practical applications in various fields. The mathematical analysis of this model has practical applications in various fields, such as flow dynamics, material science, and environmental modeling. In this paper, the theory of reproducing kernel spaces (RKS) is utilized to solve singularly perturbed 2D parabolic convection–diffusion problems of delayed type. To this end, a series form for the solution is first constructed in reproducing kernel Hilbert space, and then, the approximate solution is given as an N -term summation. The main contribution of the present research is that, for the first time, a novel formula is found for the homogenization of 2D initial-boundary-value problems. Furthermore, a semi-analytical RKS method is employed without employing the Gram–Schmidt orthogonalization algorithm. We derive theorems to reveal stability and convergence properties which are examined by numerical experiments. The technique is especially suited for problems having boundary-layer behavior. Numerical results are provided to demonstrate the efficiency, stability, and superiority of the proposed technique. [ABSTRACT FROM AUTHOR]

Formerly the geometry was based on shapes, but since the last centuries this founding mathematical science deals with transformations, projections, and mappings. Projective geometry identifies a line with a single point, like the perspective on the horizon line and, due to this fact, it requires a restructuring of the real mathematical and numerical analysis. In particular, the problem of interpolating data must be refocused. In this paper, we define a linear structure along with a metric on a projective space, and prove that the space thus constructed is complete. Then, we consider an iterated function system giving rise to a fractal interpolation function of a set of data. [ABSTRACT FROM AUTHOR]

In Bayesian statistics, posterior contraction rates (PCRs) quantify the speed at which the posterior distribution concentrates on arbitrarily small neighborhoods of a true model, in a suitable way, as the sample size goes to infinity. In this paper, we develop a new approach to PCRs, with respect to strong norm distances on parameter spaces of functions. Critical to our approach is the combination of a local Lipschitz-continuity for the posterior distribution with a dynamic formulation of the Wasserstein distance, which allows to set forth an interesting connection between PCRs and some classical problems arising in mathematical analysis, probability and statistics, e.g., Laplace methods for approximating integrals, Sanov's large deviation principles in the Wasserstein distance, rates of convergence of mean Glivenko–Cantelli theorems, and estimates of weighted Poincaré–Wirtinger constants. We first present a theorem on PCRs for a model in the regular infinite-dimensional exponential family, which exploits sufficient statistics of the model, and then extend such a theorem to a general dominated model. These results rely on the development of novel techniques to evaluate Laplace integrals and weighted Poincaré–Wirtinger constants in infinite-dimension, which are of independent interest. The proposed approach is applied to the regular parametric model, the multinomial model, the finite-dimensional and the infinite-dimensional logistic-Gaussian model and the infinite-dimensional linear regression. In general, our approach leads to optimal PCRs in finite-dimensional models, whereas for infinite-dimensional models it is shown explicitly how the prior distribution affect PCRs. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the asymptotic behavior of a modified chemostat model. We first demonstrate the existence of equilibria. Then, we present a mathematical analysis for the model, the invariance, the positivity, the persistence of the solutions, and the asymptotic global stability of the interior equilibrium. Some numerical simulations are carried out to illustrate the main results. [ABSTRACT FROM AUTHOR]

The analysis of the mathematical and mechanical properties of thermoelastic coupling tensors in anisotropic laminates is the topic of this paper. Some theoretical results concerning the compliance tensors are shown and their mechanical consequences analyzed. Moreover, the case of thermally stable laminates, important for practical applications, is also considered. The study is carried out in the framework of the polar method, a mathematical formalism particularly well-suited for the analysis of planar anisotropic problems, introduced by Prof. G. Verchery in 1979. [ABSTRACT FROM AUTHOR]

Holden described, without mathematical analysis, a kinematical method for constructing from platonic solids polylinks with flat or solid polygonal links. No statement was made about the number of polylinks. Geometric parameters of examples shown were found by trial and error. In the present paper, it is shown that each platonic solid defines a one-parametric manifold of polylinks. The geometry of flat links and of links with circular cross section is expressed in terms of the free parameter. The solution is based on a theorem which generalizes known solutions of special cases. [ABSTRACT FROM AUTHOR]

In the present paper, necessary and sufficient conditions are given for the equality of the power rezidue symbols $$ {\left( {\frac{\alpha }{a}} \right)_n} $$ and $$ {\left( {\frac{\alpha }{a}} \right)_n} $$ in the cyclotomic field ℚ(ζ n), 2 ∤ n, for a ∈ ℤ, ( a, n) = 1. This result is a generalization of the classical Eisenstein reciprocity law and its continuation in a Hasse’s paper. Bibliography: 3 titles. [ABSTRACT FROM AUTHOR]

The global stress distribution and state parameter analysis of the building's main structure is an urgent problem to be solved in the online state assessment technology of building structure health. In this paper, a stress curve clustering algorithm of fiber Bragg grating stress sensor based on density clustering algorithm is proposed. To solve the problem of large dimension and sparse sample space of sensor stress curve, the distance between samples is measured based on improved cosine similarity. Aiming at the problem of low efficiency and poor effect of traditional clustering algorithm, density clustering algorithm based on mutual nearest neighbor is used to cluster. Finally, the classification of the daily stress load characteristics of the sensor is realized, which provides a basis for constructing the mathematical analysis model of building health. The experimental results show that the stress curve clustering method proposed in this paper is better than the latest clustering algorithms such as HDBSCAN, CBKM, K-mean++,FINCH and NPIR, and is suitable for the feature classification of stress curves of fiber Bragg grating sensors. [ABSTRACT FROM AUTHOR]

This paper aims at mathematical analyzing of a parabolic chemotaxis model with nonlinear cross-diffusion transposed from the euclidean case into weighted networks. Taking into account certain applications in neurobiology, data transmission and wound healing process, a modified Keller–Segel model with volume-filling effect is studied. The novelty with respect to other related papers lies in the numerical investigation of chemotaxis process in weighted networks and of asymptotic self-similar behavior of solutions by time dependent scaling. The global existence and the large-time dynamics of solutions are detailed. Finally, the theoretical characteristics of the discrete solutions are explored numerically. [ABSTRACT FROM AUTHOR]

The global stress distribution and state parameter analysis of the building's main structure is an urgent problem to be solved in the online state assessment technology of building structure health. In this paper, a stress curve clustering algorithm of fiber Bragg grating stress sensor based on density clustering algorithm is proposed. To solve the problem of large dimension and sparse sample space of sensor stress curve, the distance between samples is measured based on improved cosine similarity. Aiming at the problem of low efficiency and poor effect of traditional clustering algorithm, density clustering algorithm based on mutual nearest neighbor is used to cluster. Finally, the classification of the daily stress load characteristics of the sensor is realized, which provides a basis for constructing the mathematical analysis model of building health. The experimental results show that the stress curve clustering method proposed in this paper is better than the latest clustering algorithms such as HDBSCAN, CBKM, K-mean++,FINCH and NPIR, and is suitable for the feature classification of stress curves of fiber Bragg grating sensors. [ABSTRACT FROM AUTHOR]

Recent work by Volz (J Math Biol 56:293-310, 2008) has shown how to calculate the growth and eventual decay of an SIR epidemic on a static random network, assuming infection and recovery each happen at constant rates. This calculation allows us to account for effects due to heterogeneity and finiteness of degree that are neglected in the standard mass-action SIR equations. In this note we offer an alternate derivation which arrives at a simpler-though equivalent-system of governing equations to that of Volz. This new derivation is more closely connected to the underlying physical processes, and the resulting equations are of comparable complexity to the mass-action SIR equations. We further show that earlier derivations of the final size of epidemics on networks can be reproduced using the same approach, thereby providing a common framework for calculating both the dynamics and the final size of an epidemic spreading on a random network. Under appropriate assumptions these equations reduce to the standard SIR equations, and we are able to estimate the magnitude of the error introduced by assuming the SIR equations. [ABSTRACT FROM AUTHOR]

Abstract  We generalize a result of F. Luca and A. Sankaranarayanan by proving that the set of n for which ϕ(1) ⃛ ϕ(n) is squareful is of zero density. A similar statement holds for σ (n) instead of ϕ(n) and for some other multiplicative functions. [ABSTRACT FROM AUTHOR]

Double random phase encoding (DRPE) is one of the most classic methods in optical image encryption. Since the linear property of DRPE makes the encryption system based on DRPE vulnerable to attacks, the researchers have introduced the scrambling and diffusion structure on the basis of DRPE. However, it is found in this study that the added scrambling and diffusion operations cannot destroy the linear property of DRPE totally, and there are still some security holes. This paper proposes an attack scheme for a class of the DRPE encryption systems based on scrambling and diffusion, and reveals the equivalent encryption methods to the original cryptosystems. The experimental results show that the structural similarity index measure and correlation coefficient index of the plaintext image and original image recovered by the attack method are close to 1. The effectiveness of the scheme is proved by mathematical analysis and experimental results. [ABSTRACT FROM AUTHOR]

Quantum circuit simulation is an important tool for evaluating designed quantum algorithms. Full-state simulation gives the entire state vectors produced by the running of algorithms. Distributed simulation aims to take advantage of resources on multiple machines (a.k.a. nodes) for high-performance simulation. As a quantum circuit may have many levels, simulation on each level is called a step. The reduction in the cost on each step results in a significant saving in total cost. In existing distributed full-state simulations, the communication cost in each step dominates. In this paper, we propose a new simulation technique, namely QuanPath, which completely eliminates communications and synchronizations on each step until the final merge step. Each node can compute its portion of the state vector independently in parallel. We present detailed mathematical analyses to guarantee the correctness of QuanPath. In the final merge step, an efficient communication scheme is further designed. Experimental results show that when simulating quantum algorithms, QuanPath achieves thousands times of reduction in communication cost and obtains dozens times of simulation acceleration compared with existing techniques. In addition, QuanPath realizes almost linear speedup, so it presents good scalability. [ABSTRACT FROM AUTHOR]

This paper is dedicated to the scientific and pedagogical activities of Nikolay Dmitrievich Kopachevsky (1940–2020) — a well-known mathematician, head of the Department of Mathematical Analysis of the V. I. Vernadsky Crimean Federal University, organizer and head of the Crimean Autumn Mathematical School-Symposium (KROMSH). [ABSTRACT FROM AUTHOR]

This study examines Einstein's field equations in the context of general relativity, comparing five distinct methodologies: (a) vanishing complexity, (b) embedding class one or the Karmarkar condition, (c) conformally flat spacetime, (d) conformal killing symmetry, and (e) the Karmarkar scalar condition. The first four methods reveal a significant connection between two metric potentials, while the fifth method provides a coordinate-independent condition expressed in terms of structural scalars. The paper provides a comprehensive comparative analysis of a new exact solution derived by assuming a common metric function and solving the remaining metric functions through corresponding bridge equations to evaluate their effectiveness and validity. Critical parameters such as thermodynamic factors, causality conditions, stability, and mass function analysis are investigated. [ABSTRACT FROM AUTHOR]

This paper presents a stabilized meshfree method formulated based on the strong formulation and local approximation using radial basis functions (RBFs). The purpose of this paper is two folds. First, a regularization procedure is developed for stabilizing the solution of the radial point collocation method (RPCM). Second, an adaptive scheme using the stabilized RPCM and residual based error indicator is established. It has been shown in this paper that the features of the meshfree strong-form method can facilitated an easier implementation of adaptive analysis. A new error indicator based on the residual is devised and used in this work. As shown in the numerical examples, the new error indicator can reflect the quality of the local approximation and the global accuracy of the solution. A number of examples have been presented to demonstrate the effectiveness of the present method for adaptive analysis. [ABSTRACT FROM AUTHOR]

The underground pipeline network in the city is so intertwined that the concealed excavation of a metro station inevitably leads to a series of underground pipelines, causing settlement deformation and further risk of leakage. The existing theoretical methods for analysing settlement deformation are mostly for circular chambers, whereas metro stations have a nearly square cross-sectional form and different construction methods are very different, which have a greater impact on the deformation of the overlying pipelines. In this paper, based on the random medium theory and Peck's formula, the improved random medium model for predicting ground deformation is modified, the correction coefficients λ and η for the influence of different construction methods are proposed, the prediction model of underground pipeline deformation under different construction methods is obtained, and the numerical models of four work methods commonly used in urban tunnel construction: pillar hole method, side hole method, middle hole method and Pile-Beam-Arch (PBA) method are constructed through simulation, and the mathematical analysis software was used to fit the results to the model and obtain the range of correction coefficients λ and η for each of the four methods, and the accuracy and applicability of the theoretical model was verified by combining with actual engineering cases. The influence on the overlying pipes is in descending order: side hole method, pillar hole method, middle hole method and PBA method. The theoretical model provided in this paper for predicting the deformation of pipes in any overlying strata of the tunnel is well suited to the actual project and has a high degree of correlation with the measured results. [ABSTRACT FROM AUTHOR]

Currently, one of the most urgent problems of digital image processing is the search for new mathematical approaches to the analysis and processing of multichannel images. The relevance of these studies is due to the need of optimization of available methods of digital image processing and increase the quality of the results obtained. In this paper, a new approach to processing of digital RGB-images based on the Blaschke theory of three-webs is proposed. Invariants of three-channel images with respect to the widest "topological" transformation group are determined. [ABSTRACT FROM AUTHOR]

Autonomous network management is crucial for Fifth Generation (5G) and Beyond 5G (B5G) networks, where a constantly changing environment is expected and network configuration must adapt accordingly. Modeling tools are required to predict the impact on performance (packet and delay loss) when new traffic demands arrives and when changes in routing paths are applied in the network. Mathematical analysis and network simulators are techniques for modeling networks but both have limitations, as the former provides low accuracy and the latter requires high execution times. To overcome these limitations, machine learning (ML) algorithms, and more specifically, graph neural networks (GNNs), are proposed for network modeling due to their ability to capture complex relationships from graph-like data while predicting network properties with high accuracy and low computational requirements. However, one of the main issues when using GNNs is their lack of generalization capability to larger networks, i.e., when trained in small networks (in number of nodes, paths length, links capacity), the accuracy of predictions on larger networks is poor. This paper addresses the GNN generalization problem by the use of fundamental networking concepts. Our solution is built from a baseline GNN model called RouteNet (developed by Barcelona Neural Networking Center-Universitat Politècnica de Catalunya (BNN-UPC)) that predicts the average delay in network paths, and through a number of simple additions significantly improves the prediction accuracy in larger networks. The improvement ratio compared to the baseline model is 101, from a 187.28% to a 1.828%, measured by the Mean Average Percentage Error (MAPE). In addition, we propose a closed-loop control context where the resulting GNN model could be potentially used in different use cases. [ABSTRACT FROM AUTHOR]

We considered in Example 3.1 of the paper [1] an S-structure on R2 n+ s. We concluded that when s > 1 this manifold cannot be of constant φ-sectional curvature. Unfortunately this result is wrong. In fact, essentially due to a sign mistake in defining the φ-structure and a consequent transposition of the elements of the φ-basis (3.2), some of the Christoffel’s symbols were incorrect. In the present rectification, using a more slendler tecnique, we prove that our manifold is of constant φ-sectional curvature −3 s and then it is η-Einstein. [ABSTRACT FROM AUTHOR]

This article provides instructions in preparing a paper for publication in the "Journal of Optimization Theory and Applications." Some of these guidelines are the following: 1)submission of manuscripts in triplicate; 2) reference to English as the official language of the journal; 3) inclusion of an abstract of at least 50 to 100 words in each contribution; and, 4) the abstract should be followed by a list of four to five key words identifying the subject.

Presents manuscript guidelines for papers to be published in the "Journal of Optimization Theory and Applications."

In [1] Kohli and Vashistha gave an analogue of probabilistic version of Pant's Theorem ([2], Theorem 1). We note that mappings defined in Examples 3.6 to 3.8 of [1] are not self maps as claimed in the Definitions 3.1 and 3.2. In this context, we provide some relevant examples to complete the interesting results. [ABSTRACT FROM AUTHOR]

This is an attachment to a letter of the author to Alexander Zvonkin (dated November 1, 1995). It is reproduced here with the kind permission of the author. [ABSTRACT FROM AUTHOR]

Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed systems problem. This paper presents an efficient solution to the load balancing problem in such systems that improves on and overcomes problems of previous solutions. The load balancing problem is formulated as a stochastic optimization problem, and an efficient algorithmic solution is obtained based on a subtle mathematical analysis of the problem. Finally, extensive evaluation of the solution on simulated data shows that it outperforms previous solutions. Moreover, the resulting dispatching policy can be computed very efficiently, making the solution practically viable. [ABSTRACT FROM AUTHOR]

This paper develops a coupled chemo-mechanical model for stress-assisted diffusion in the framework of micropolar elasticity. The two-way interaction of mechanical and chemical driving forces as well as internal microstructure of the polar media is taken into account. The fundamental governing equations of chemo-mechanics with kinetics driven by diffusion and stress are developed, and mathematical expressions for stress and concentration fields are derived. Using Airy stress functions, a simplified formulation for two-dimensional chemo-elasticity problems under chemical equilibrium is presented. Using a perturbation approach to solve the presented system of equations, closed-form expressions for different field parameters can be obtained. As an illustrative case study, expressions for the stress and solute concentration in an infinite plate with circular hole embedded in a chemical medium have been written. The derived equation and proposed solution approach can be applied to various plane micropolar chemo-elasticity problems for studying the interaction between mechanical and chemical driving forces as well as material length-scale parameters. [ABSTRACT FROM AUTHOR]

This paper is concerned with time-asymptotic nonlinear stability of rarefaction waves to the Cauchy problem for one-dimensional compressible non-isentropic magnetohydrodynamics (MHD) equations (including its isentropic case), which describe the motion of a conducting fluid in a magnetic field. Through some elaborate and rigorous mathematical analysis, we can construct the rarefaction waves v r , u r , θ r , b r (x / t) where magnetic component b r x / t is a nontrivial profile, namely a non-constant function. Then the solution of the compressible MHD equations is proved to tend towards the rarefaction waves time-asymptotically under small initial perturbations and weak wave strength, and also under a technical assumption that the parameter β = v + b + is bounded by a specific constant. The proof of the main result is based on elementary L 2 energy methods. [ABSTRACT FROM AUTHOR]

We study linear time-dependent Maxwell equations on a cuboid consisting of two homogeneous subcuboids. At the interface, we allow for nonzero surface charge density and surface current. This model is a first step towards a detailed mathematical analysis of the interaction of single-layer materials with electromagnetic fields. The main results of this paper provide several wellposedness and regularity statements for the solutions of the Maxwell system. To prove the statements, we employ extension arguments using interpolation theory, as well as semigroup theory and regularity theory for elliptic transmission problems. [ABSTRACT FROM AUTHOR]

Fractional calculus is an important branch of mathematical analysis and played a fundamental role in different fields including signal processing and image processing. In this paper, we proposed a sparse super-resolution (SR) technique by using the Grünwald-Letnikov (G–L) fractional differential operator, which aims to reconstruct high-resolution images by recovering pixel information from low-resolution images. We suggested a modified fractional derivative mask based on G–L for image enhancement. The proposed method suppresses block artifacts, staircase edges, and false edges near the edges. The proposed method is very flexible and preserves detailed features. The obtained experiments demonstrated that fractional operator can nonlinearly preserve the low-frequency contour information in the smooth region and also nonlinearly improve well the high-frequency edge and texture of the image. In sparse SR images, the dictionary is constructed by texture information of the images by using integer derivatives. In this work, we computed dictionary matrices by applying the fractional masks. In fact, the extracted features based on fractional derivatives are utilized in the dictionary training procedure and sparse coding. The experimental results and analysis on natural images indicated that the proposed method achieved much better results than other algorithms in terms of both quantitative measures and visual perception. [ABSTRACT FROM AUTHOR]

Fog computing is a computing structure which is distributed in nature. Low latency, reasonably low communication overhead and ability to support real time applications are the reasons for which fog computing approach said to provide better performance than cloud computing. Although, it is an extension of the cloud computing. Fog computing also inherits some critical security and privacy issues of cloud computing. Secure key management and user authentication are among the key issues faced by fog computing. Various schemes with probable solutions of these issues have been proposed by many authors in this context. Among them, a notable scheme has been presented by Wajid et al. known as SAKA-FC, where authors used three-factor authentication with privacy preservation for remote user based on ECC, hash functions, fuzzy extractor and symmetric bivariate polynomial function. This paper analyses the SAKA-FC protocol and found that it is not resilient against fog server insider attack, message intercept attack and replay attack. Consequently, an improved, lightweight and secure authentication scheme in context of fog-centric IoT communication is proposed in this paper to eradicate all the above mentioned security shortfalls of Wajid et al scheme. The proposed scheme is verified using mathematical security analysis and simulated using AVISPA which proves that the proposed scheme prevents all pertinent security threats. The performance analysis of our scheme proves its effectiveness over other related existing schemes in this context. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical framework using multiple reconfigurable intelligent surfaces (RISs) for enhancing the secrecy performance of wireless systems. In particular, multiple RISs are exploited to support transmitter-legitimate user communication under the existence of an eavesdropper. Two practical scenarios are investigated, i.e., there are only transmitter-eavesdropper links (case 1) and there are both transmitter-eavesdropper and transmitter-RIS-eavesdropper links (case 2). We mathematically obtain the closed-form expressions of the average secrecy capacity (ASC) of the considered system in these two investigated cases over Nakagami-m fading channels. The impacts of the system parameters, such as the locations of the RISs, the number of REs, and the Nakagami-m channels, are deeply evaluated. Computer simulations are used to validate our mathematical analysis. Numerical results clarify the benefits of using multiple RISs for improving the secrecy performance of wireless systems. Specifically, the ASCs in cases 1 and 2 are significantly higher than that in the case without RISs. Importantly, when the locations of the RISs are fixed, we can arrange the larger RSIs near either the transmitter or legitimate user to achieve higher ASCs. In addition, when the numbers of reflecting elements (REs) in the RISs increase, the ASCs in cases 1 and 2 are greatly enhanced. [ABSTRACT FROM AUTHOR]

We are interested in a reduced model for corrosion of iron, in which ferric cations and electrons evolve in a fixed oxide layer subject to a self-consistent electrostatic potential. Reactions at the boundaries are modeled thanks to Butler–Volmer formulas, whereas the boundary conditions on the electrostatic potential model capacitors located at the interfaces between the materials. Our model takes inspiration in existing papers, to which we bring slight modifications in order to make it consistent with thermodynamics and its second principle. Building on a free energy estimate, we establish the global in time existence of a solution to the problem without any restriction on the physical parameters, in opposition to previous works. The proof further relies on uniform estimates on the chemical potentials that are obtained thanks to Moser iterations. Numerical illustrations are finally provided to highlight the similarities and the differences between our new model and the one previously studied in the literature. [ABSTRACT FROM AUTHOR]

In the last decade, the interactions among histone modifications and DNA methylation and their effect on the DNA structure, i.e., chromatin state, have been identified as key mediators for the maintenance of cell identity, defined as epigenetic cell memory. In this paper, we determine how the positive feedback loops generated by the auto- and cross-catalysis among repressive modifications affect the temporal duration of the cell identity. To this end, we conduct a stochastic analysis of a recently published chromatin modification circuit considering two limiting behaviors: fast erasure rate of repressive histone modifications or fast erasure rate of DNA methylation. In order to perform this mathematical analysis, we first show that the deterministic model of the system is a singular singularly perturbed (SSP) system and use a model reduction approach for SSP systems to obtain a reduced one-dimensional model. We thus analytically evaluate the reduced system's stationary probability distribution and the mean switching time between active and repressed chromatin states. We then add a computational study of the original reaction model to validate and extend the analytical findings. Our results show that the absence of DNA methylation reduces the bias of the system's stationary probability distribution toward the repressed chromatin state and the temporal duration of this state's memory. In the absence of repressive histone modifications, we also observe that the time needed to reactivate a repressed gene with an activating input is less stochastic, suggesting that repressive histone modifications specifically contribute to the highly variable latency of state reactivation. [ABSTRACT FROM AUTHOR]

This report presents a comprehensive approach to dispersion management, including various techniques, mathematical analysis, and their advantages and disadvantages in different scenarios. A deep mathematical analysis of chirped fiber Bragg grating (CFBG) is conducted for various chirping techniques and apodization profiles, highlighting the importance of this aspect in dispersion management. Additionally, a detailed study of the implementation of CFBG and dispersion compensating fiber (DCF) is performed to determine which technique is suitable for long-haul links and which is best for WDM networks, both for low and high capacity. The report also sheds light on how dispersion compensation techniques can be useful in mm wave propagation. The paper provides new insights into the field of dispersion management and the results of the study make it an interesting and valuable addition to the literature. [ABSTRACT FROM AUTHOR]

In this paper, we tame the uncertainty about the volatility in time-averaging principle for stochastic differential equations driven by G-Brownian motion (G-SDEs) based on the Lyapunov condition. That means we treat the time-averaging principle for stochastic differential equations based on the Lyapunov condition in the presence of a family of probability measures, each corresponding to a different scenario for the volatility. The main tool for the mathematical analysis is the G-stochastic calculus, which is introduced in the book by Peng (Nonlinear Expectations and Stochastic Calculus Under Uncertainty. Springer, Berlin, 2019). We show that the solution of a standard equation converges to the solution of the corresponding averaging equation in the sense of sublinear expectation with the help of some properties of G-stochastic calculus. Numerical results obtained using PYTHON illustrate the efficiency of the averaging method. [ABSTRACT FROM AUTHOR]

Architectural imperatives due to the slowing of Moore's Law, the broad acceptance of relaxed semantics and the O(n!) worst case verification complexity of generating sequential histories motivate a new approach to concurrent correctness. Desiderata for a new correctness condition are that it be independent of sequential histories, compositional, flexible as to timing, modular as to semantics and free of inherent locking or waiting. We propose Quantifiability, a novel correctness condition that models a system in vector space to launch a new mathematical analysis of concurrency. The vector space model is suitable for a wide range of concurrent systems and their associated data structures. This paper formally defines quantifiability and demonstrates that quantifiability is compositional and non-blocking and that it implies observational refinement. Analysis is facilitated with linear algebra, better supported and of much more efficient time complexity than traditional combinatorial methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider a mathematical model of a coronavirus disease involving the Caputo–Fabrizio fractional derivative by dividing the total population into the susceptible population S (t) , the vaccinated population V (t) , the infected population I (t) , the recovered population R (t) , and the death class D (t) . A core goal of this study is the analysis of the solution of a proposed mathematical model involving nonlinear systems of Caputo–Fabrizio fractional differential equations. With the help of Lipschitz hypotheses, we have built sufficient conditions and inequalities to analyze the solutions to the model. Eventually, we analyze the solution for the formed mathematical model by employing Krasnoselskii's fixed point theorem, Schauder's fixed point theorem, the Banach contraction principle, and Ulam–Hyers stability theorem. [ABSTRACT FROM AUTHOR]

The health organizations around the world are currently facing one of the greatest challenges, to overcome the current global pandemic, COVID-19. It erupted in December 2019, in Wuhan City, China. It spreads rapidly throughout the world within couple of months. In this paper, the data of the COVID-19 have been collected, organized, analyzed and interpreted using the discrete-time model of SIR epidemic model. Moreover, results for several countries from different regions of the world have been obtained. Furthermore, comparative study has been carried out for the countries under consideration. The comparison was performed for the data of different countries on same dates of each month. However, the calculations are carried out for thirteen consecutive weeks, to investigate the rate of spread and the control of the disease in these countries. This guides us to some important concepts like factors favoring the spread of virus and those resisting the spread. Different regions are studied and their data have been evaluated to know which regions are the most effected. This study helps to know the important factors about the behavior of the coronavirus in different environments, such as lockdowns, temperatures, humidity and other restrictions. The proposed concepts and equations can be used to project the upcoming behavior of the pandemic. [ABSTRACT FROM AUTHOR]