Symmetric Scheme Research Articles

Self‐dual association schemes, fusions of Hamming schemes, and partial geometric designs

AbstractPartial geometric designs can be constructed from basic relations of association schemes. An infinite family of partial geometric designs were constructed from the fusion schemes of certain Hamming schemes in work by Nowak et al. (2016). A general method to create partial geometric designs from association schemes is given by Xu (2023). In this paper, we continue the research by Xu (2023). We will first study the properties and characterizations of self‐dual association schemes. Then using the characterizations of self‐dual association schemes and the representation theory (character tables) of commutative association schemes, we obtain characterizations and classifications of self‐dual (symmetric or nonsymmetric) association schemes of rank 4 that produce as many as possible nontrivial partial geometric designs or 2‐designs. In particular, for a primitive self‐dual symmetric association scheme of rank 4, if is a power of 3 and each of , , and induces a partial geometric design, then we will prove that is algebraically isomorphic to a fusion scheme of the Hamming scheme for some odd number .

Steganalysis of Neural Networks Based on Symmetric Histogram Distribution

Deep neural networks have achieved remarkable success in various fields of artificial intelligence. However, these models, which contain a large number of parameters, are widely distributed and disseminated by researchers, engineers, and even unauthorized users. Except for intelligent tasks, typically overparameterized deep neural networks have become new digital covers for data hiding, which may pose significant security challenges to AI systems. To address this issue, this paper proposes a symmetric steganalysis scheme specifically designed for neural networks trained for image classification tasks. The proposed method focuses on detecting the presence of additional data without access to the internal structure or parameters of the host network. It employs a well-designed method based on histogram distribution to find the optimal decision threshold, with a symmetric determining rule where the original networks and stego networks undergo two highly symmetrical flows to generate the classification labels; the method has been shown to be practical and effective. SVM and ensemble classifiers were chosen as the binary classifier for their applicability to feature vectors output from neural networks based on different datasets and network structures. This scheme is the first of its kind, focusing on steganalysis for neural networks based on the distribution of network output, compared to conventional digital media such as images, audio, and video. Overall, the proposed scheme offers a promising approach to enhancing the security of deep neural networks against data hiding attacks.

Optimizing design choices for neural quantum states

Neural quantum states are a new family of variational ans\"atze for quantum-many body wave functions with advantageous properties in the notoriously challenging case of two spatial dimensions. Since their introduction a wide variety of different network architectures has been employed to study paradigmatic models in quantum many-body physics with a particular focus on quantum spin models. Nonetheless, many questions remain about the effect that the choice of architecture has on the performance on a given task. In this work, we present a unified comparison of a selection of popular network architectures and symmetrization schemes employed for ground state searches of prototypical spin Hamiltonians, namely the two-dimensional transverse-field Ising model and the J1-J2 model. In the presence of a non-trivial sign structure of the ground states, we find that the details of symmetrization crucially influence the performance. We describe this effect in detail and discuss its consequences, especially for autoregressive models, as their direct sampling procedure is not compatible with the symmetrization procedure that we found to be optimal.

Geophysical research of underground hydraulic structures, old Glubochinsky water tunnel case study

Research objective is to study the features of geophysical fields and parameters in the area of the artificial underground water tunnel and estimate the capabilities of geophysical methods of identifying hidden underground industrial facilities. Methods of research. Measurements of self-potential signals (SP) were carried out using nonpolarizing electrodes and an electrical exploration receiver. The magnetic exploration was carried out by a proton magnetometer. Electrotomography was carried out using multielectrode electrical survey equipment with a Schlumberger symmetrical scheme of surveys. The microseismic background was recorded using an autonomous seismic station. The georadar survey was carried out using the SIR-3000 ground penetrating radar and antennas with the frequencies of 100 MHz and 270 MHz. Results. Based on the survey results, graphs of magnetic and self-potential fields, electrotomographic and microseismic sections, and radarogram were built on the research profile. The research has shown different levels of the magnetic field and the SP in the area of volcanic rocks and dikes of gabbro-dolerites occurrence. A significant increase in microseismic noise was observed with an increase in the weathering crust thickness. A local decrease in the SP potential, abnormally high values of specific electrical resistivity and intensive reflections of radio waves from the tunnel top were recorded above the underground water tunnel. Conclusions. Qualitative and quantitative geophysical characteristics were obtained in the area of the old underground water tunnel. The research showed different levels of the magnetic field and spontaneous polarization potentials in the occurrence area of rocks of different composition. A significant increase in microseismic noise was recorded with an increase in the weathering crust thickness. Geophysical signs of the boundaries between geological structures and artificial underground objects are revealed. The exact position and depth of the old underground tunnel of Glubochinsky hydraulic structures was determined.

Energy Efficient and Secure Neural Network–based Disease Detection Framework for Mobile Healthcare Network

Adopting mobile healthcare network (MHN) services such as disease detection is fraught with concerns about the security and privacy of the entities involved and the resource restrictions at the Internet of Things (IoT) nodes. Hence, the essential requirements for disease detection services are to (i) produce accurate and fast disease detection without jeopardizing the privacy of health clouds and medical users and (ii) reduce the computational and transmission overhead (energy consumption) of the IoT devices while maintaining the privacy. For privacy preservation of widely used neural network– (NN) based disease detection, existing literature suggests either computationally heavy public key fully homomorphic encryption (FHE), or secure multiparty computation, with a large number of interactions. Hence, the existing privacy-preserving NN schemes are energy consuming and not suitable for resource-constrained IoT nodes in MHN. This work proposes a lightweight, fully homomorphic, symmetric key FHE scheme (SkFhe) to address the issues involved in implementing privacy-preserving NN. Based on SkFhe, widely used non-linear activation functions ReLU and Leaky ReLU are implemented over the encrypted domain. Furthermore, based on the proposed privacy-preserving linear transformation and non-linear activation functions, an energy-efficient, accurate, and privacy-preserving NN is proposed. The proposed scheme guarantees privacy preservation of the health cloud’s NN model and medical user’s data. The experimental analysis demonstrates that the proposed solution dramatically reduces the overhead in communication and computation at the user side compared to the existing schemes. Moreover, the improved energy efficiency at the user is accomplished with reduced diagnosis time without sacrificing classification accuracy.

A lightweight and secure multilayer authentication scheme for wireless body area networks in healthcare system

<span lang="EN-US">Wireless body area networks (WBANs) have lately been combined with different healthcare equipment to monitor patients' health status and communicate information with their healthcare practitioners. Since healthcare data often contain personal and sensitive information, it is important that healthcare systems have a secure way for users to log in and access resources and services. The lack of security and presence of anonymous communication in WBANs can cause their operational failure. There are other systems in this area, but they are vulnerable to offline identity guessing attacks, impersonation attacks in sensor nodes, and spoofing attacks in hub node. Therefore, this study provides a secure approach that overcomes these issues while maintaining comparable efficiency in wireless sensor nodes and mobile phones. To conduct the proof of security, the proposed scheme uses the Scyther tool for formal analysis and the Canetti–Krawczyk (CK) model for informal analysis. Furthermore, the suggested technique outperforms the existing symmetric and asymmetric encryption-based schemes.</span>

Guided Wave-Based Damage Detection of Square Steel Tubes Utilizing Structure Symmetry

Square steel tube, which is widely used in civil engineering, can suffer from a wide variety of damages and aging defects, thus its nondestructive testing (NDT) has attracted wide attention. This work proposes an ultrasonic guided wave (UGW)-based damage detection method for square steel tubes using structure symmetry. Firstly, the dispersion characteristics of square steel tubes are obtained using the semi-analytical finite element (SAFE) method, after which the optimal guided wave modes for damage located on the long and short edges of the steel tube are selected by modal analysis. Then, using the symmetry of the square steel tube’s section, the symmetric layout scheme of the transmitters and the receivers is designed; on this basis, a signal processing strategy for damage detection is proposed by subtracting the receiving signals obtained from symmetric positions. Finally, the effectiveness of the proposed damage detection method is verified by numerical simulations and laboratory experiments. The results show that the proposed method has good inspection accuracy for crack and hole damages on both the long and short edges of square steel tube because the dispersion effect and clutters can be reduced utilizing structure symmetry. It is worth mentioning that the inspection effect for corner holes can be enhanced by modifying the position of the receivers.

Opening Possible Worlds: the Application of the Tool of Network Theory to the Short Stories by Bitė Vilimaitė

The main aim of the article is to discuss the validity of the Network Theory suggested by Franco Moretti and the possibility of applying it while analyzing short stories. There were two main tasks to be fulfilled – to describe briefly the main statements of Network Theory applied to literature and after the analysis of the texts using the theoretical tool suggested by Moretti to reveal the main features of the prose texts by Lithuanian writer Bitė Vilimaitė (1943–2014), who is considered to be one of the greatest masters of the short story in Lithuanian literature. The examples of the texts for the analyses have been chosen randomly from Vilimaitėʼs selection of the short stories “The Sun of the Fern-grove” (Papartynų saulė, 2002). The networks of the plots of three texts have shown that Vilimaitė uses symmetric and asymmetric schemes, which are being strengthened by specific vertices without any edges. The schemes of the plot help to concentrate on particular characters and analyze their actions or intentions closer, and the vertices without any edges (as an old woman, several witnesses or two dogs in analyzed texts) can be treated as particular starting points for potential stories, which could be developed in the context of the main narrative. Such vertices stipulate an assumption that Vilimaitė uses Hemingway’s principle of iceberg; subsidiary characters (or vertices without the edges in the schemes) are vivid enough to create concrete associations, form a particular background for the vertices with edges (the characters, which are related between themselves by verbal or non-verbal communication) and enrich the scale of possible reactions of the reader.

NUMERICAL SIMULATION OF FRACTIONAL POWER DIFFUSION BIOSENSORS

The main aim of this paper is to propose new mathematical models for simulation of biosensors and to construct and investigate discrete methods for the efficient solution of the obtained systems of nonlinear PDEs. The classical linear diffusion operators are substituted with nonlocal fractional powers of elliptic operators. The splitting type finite volume scheme is used as a basic template for the introduction of new mathematical models. Therefore the accuracy of the splitting scheme is investigated and compared with the symmetric Crank-Nicolson scheme. The dependence of the approximation error on the regularity of the solution is investigated. Results of computational experiments for different values of fractional parameters are presented and analysed.

Phase center motion based time modulated arrays with preprocessed time schemes for selective harmonic beamforming in B5G communication systems

AbstractThe possibilities of achieving beamforming antenna arrays for beyond fifth generation (B5G) communication systems by controlling the inherently generated harmonic beam patterns in “time modulation” based antenna arrays, are proposed in this article. The idea of “time modulation” is to assimilate an additional dimension “time” by using high‐speed switches for synthesizing the array radiation patterns. This in turn generates an infinite number of harmonic frequency patterns apart from the main beam at the fundamental frequency. In general, harmonic frequency patterns may be regarded as wastage of power, but with proper controlling, these spatially independent patterns created at multiple harmonics can be selectively utilized for specific purposes. In this article, the lower‐order harmonic frequency patterns of “time modulated” linear arrays (TMLA) are exploited to produce simultaneous multi‐beamforming for B5G multipoint communication. The capabilities of selective harmonic frequency patterns for multi‐beamforming are mathematically verified by proposing different beamforming switching network combinations. In this regard, phase centered motion (PCM) based TMLA is examined for simultaneous, as well as, monopulse beam scanning. PCM‐based unidirectional and bidirectional beamforming patterns with optimal time schemes are proposed. The mathematical validation of preprocessed symmetric and asymmetric time schemes, as well as, the PCM‐based optimized selective harmonic multi‐beamforming radiation patterns are discussed in detail to show the effectiveness of the proposed method.

Metamaterial-Based Pattern-Switchable Linear Array for 2-D Discrete Beam-Scanning Using Hybrid Digital Coding Method

A new low-cost, pattern-switchable, metamaterial-inspired, dielectric resonator (DR) 1-D linear array for 2-D beam-steering is presented by using a hybrid digital coding method. By loading the metasurface on the DR, a low-profile DR radiator is developed. To realize both phase and pattern digital coding, a beam-switching metasurface-loaded 1 bit DR antenna is explored by using a symmetrical feeding scheme and a Yagi-like endfire radiation mechanism. The novel hybrid digital coding method is realized by using p-i-n diodes to co-control the phase (1 bit, 0°/180°) and radiation states (three-beam). Based on the hybrid digital coding method, the developed 1-D linear array creatively achieves low-cost quasi-2-D discrete beam scanning. The pattern reconfiguration technique contributes to the E-plane beam scanning, while the H-plane beam steering is attributed to the phase digital coding sequence. To validate this working mechanism, a four-element linear array is implemented and tested. The realized overlapped −10 dB impedance bandwidth is about 17.6% (covering LTE B42/43 bands), and the realized peak gain is 9.05 dBi. By controlling the switch states of 16 p-i-n diodes, the proposed four-element linear array achieves digital 2-D beam steering (12 beams). The presented antenna features a miniaturized size, wideband, low cost, and good 2-D beam-steering capacity. It provides a new and feasible solution for low-cost 2-D beam scanning, demonstrating a good application potential for intelligent communication systems and low-cost arrays.

Separable Paravector Orientation Tensors for Enhancing Retinal Vessels.

Robust detection of retinal vessels remains an unsolved research problem, particularly in handling the intrinsic real-world challenges of highly imbalanced contrast between thick vessels and thin ones, inhomogeneous background regions, uneven illumination, and complex geometries of crossing/bifurcations. This paper presents a new separable paravector orientation tensor that addresses these difficulties by characterizing the enhancement of retinal vessels to be dependent on a nonlinear scale representation, invariant to changes in contrast and lighting, responsive for symmetric patterns, and fitted with elliptical cross-sections. The proposed method is built on projecting vessels as a 3D paravector valued function rotated in an alpha quarter domain, providing geometrical, structural, symmetric, and energetic features. We introduce an innovative symmetrical inhibitory scheme that incorporates paravector features for producing a set of directional contrast-independent elongated-like patterns reconstructing vessel tree in orientation tensors. By fitting constraint elliptical volumes via eigensystem analysis, the final vessel tree is produced with a strong and uniform response preserving various vessel features. The validation of proposed method on clinically relevant retinal images with high-quality results, shows its excellent performance compared to the state-of-the-art benchmarks and the second human observers.

DDIFN: A Dual-discriminator Multi-modal Medical Image Fusion Network

Multi-modal medical image fusion is a long-standing important research topic that can obtain informative medical images and assist doctors diagnose and treat diseases more efficiently. However, most fusion methods extract and fuse features by subjectively defining constraints, which easily distorts the unique information of source images. In this work, we present a novel end-to-end unsupervised network to fuse multi-modal medical images. It is composed of a generator and two symmetrical discriminators. The former aims to generate a ”real-like” fused image based on a specifically designed content and structure loss, while the latter are devoted to distinguishing the differences between the fused image and the source ones. They are trained alternately until discriminators cannot distinguish the fused image from the source ones. In addition, the symmetrical discriminator scheme is conducive to maintaining the feature consistency among different modalities. More importantly, to enhance the retention degree of texture details, U-Net is adopted as the generator heuristically, where the up-sampling method is modified to bilinear interpolation for avoiding checkerboard artifacts. As for the optimization, we define the content loss function, which preserves the gradient information and pixel activity of source images. Both visual analysis and quantitative evaluation of experimental results show the superiority of our method as compared to the cutting-edge baselines.

Schematic 4-designs

We study 4-designs with three intersection numbers. By the Cameron-Delsarte theorem, the blocks form a symmetric three-class association scheme. This imposes strong restrictions on the parameters of such designs. We calculate the eigenvalues of the association scheme from the design parameters and determine all admissible parameters with at most 1000 points. An infinite family of admissible parameters is discovered. Designs with small admissible parameters exist and are related to the quadratic residue codes.

Symmetric key-based authentication and key agreement scheme resistant against semi-trusted third party for fog and dew computing

Symmetric key-based authentication and key agreement scheme resistant against semi-trusted third party for fog and dew computing

The influence of vacancy generation on the impurity distribution in the target under the conditions of surface treatment by a particle beam

AbstractThe paper presents a nonlinear coupled isothermal model of the process of surface treatment by a particle beam. The model takes into account the interaction between the diffusion of impurity and propagation of mechanical disturbances, as well as the transfer of the introduced impurity with the vacancy mechanism and under the action of stresses. The nonlinear problem is solved numerically using an implicit symmetric difference scheme of the second order approximation in time and spatial coordinates. The finite time of mass flux relaxation and the dependence of diffusion coefficient on the composition and on the concentration of vacancies lead to peculiarities in the propagation of both the concentration wave and the wave of mechanical disturbances. Vacancy generation contributes to the acceleration of impurity propagation and increased strain/stresses.

Pseudo-Hamiltonian neural networks with state-dependent external forces

Hybrid machine learning based on Hamiltonian formulations has recently been successfully demonstrated for simple mechanical systems, both energy conserving and not energy conserving. We introduce a pseudo-Hamiltonian formulation that is a generalization of the Hamiltonian formulation via the port-Hamiltonian formulation, and show that pseudo-Hamiltonian neural network models can be used to learn external forces acting on a system. We argue that this property is particularly useful when the external forces are state dependent, in which case it is the pseudo-Hamiltonian structure that facilitates the separation of internal and external forces. Numerical results are provided for a forced and damped mass–spring system and a tank system of higher complexity, and a symmetric fourth-order integration scheme is introduced for improved training on sparse and noisy data.

Unifying a posteriori error analysis of five piecewise quadratic discretisations for the biharmonic equation

Abstract An abstract property (H) is the key to a complete a priori error analysis in the (discrete) energy norm for several nonstandard finite element methods in the recent work [Lowest-order equivalent nonstandard finite element methods for biharmonic plates, Carstensen and Nataraj, M2AN, 2022]. This paper investigates the impact of (H) to the a posteriori error analysis and establishes known and novel explicit residualbased a posteriori error estimates. The abstract framework applies to Morley, two versions of discontinuous Galerkin, C 0 interior penalty, as well as weakly overpenalized symmetric interior penalty schemes for the biharmonic equation with a general source term in H −2(Ω).

The search for small association schemes with noncyclotomic eigenvalues

In this article we determine feasible parameter sets for (what could potentially be) commutative association schemes with noncyclotomic eigenvalues that are of smallest possible rank and order. A feasible parameter set for a commutative association scheme corresponds to a standard integral table algebra with integral multiplicities that satisfies all of the parameter restrictions known to hold for association schemes. For each rank and involution type, we generate an algebraic set for which any suitable integral solution corresponds to a standard integral table algebra with integral multiplicities, and then try to find the smallest suitable solution. The main results of this paper show the eigenvalues of association schemes of rank 4 and nonsymmetric association schemes of rank 5 will always be cyclotomic. In the rank 5 cases, the results rely on calculations done by computer for Gröbner bases or for bases of rational vector spaces spanned by polynomials. We give several examples of feasible parameter sets for small symmetric association schemes of rank 5 that have noncyclotomic eigenvalues.

Stress-strain magnetoactive propulsion system

It is possible to create deformations in magnetically active polymeric materials by applying magnetic fields to them. This work develops a symmetrical design scheme of the device, in which the drive and control are carried out by two actuators located on opposite sides. The symmetric scheme with control from two sides allows transporting objects (cargo) in mutually opposite directions (forward and backward). It is proposed to use a magnetically active gel together with a magnetically active elastomer as magnetically active materials. The resulting force effect in the device actuator is produced by interaction of magnetic fields of electromagnets with magnetic fields of permanent magnets. Expressions for obtaining alternating magnetic fields which create conditions for generating alternating magnetic forces in the actuator of the device are given. A prototype design with a controller control device in which signals are generated for an optimum current pulse generator with adjustable duty cycle and duration is presented.