Transmission Problem Research Articles

Radiofrequency transmission through rectangular apertures in perimetrally uncoated low emissivity windows

Perimetrally uncoated windows can be a simple and low cost solution to the problem of radio frequency (RF) transmission in low-e glass when the requirements are not too demanding. However, this kind of non-uniform and relatively large structures are difficult to characterize experimentally. The aim of this work is to develop and experimentally verify a method for the simulation of the RF transmission of perimetrally uncoated windows. We propose to study these windows as a composition of four rectangular apertures in a metallic sheet. Using numerical simulations, we are able to obtain the transmission coefficient of these apertures. Then, a multilayer model based on transmission line theory is used to consider the effect of the different glazings and cameras which can be part of a window. Finally, the results of this study are compared to the measurements of complete windows in the 1000 MHz–6000 MHz frequency range.

Stability for an Interface Transmission Problem of Wave-Plate Equations with Dynamical Boundary Controls

Stability for an Interface Transmission Problem of Wave-Plate Equations with Dynamical Boundary Controls

Research on Improving the Performance of Waterborne Surface Insulation Paint

With the rapid development of China's economy, the demand for electric energy in society is increasing, which puts forward higher requirements for the structure and scale of the national power network. High voltage direct current transmission is considered a new technology that can effectively alleviate the problems of power resource allocation and transmission. Insulation technology is an important part of high-voltage DC transmission and transformation technology. Currently, research on external insulation components such as silicone rubber sleeves is relatively mature, and there is relatively little research on DC internal insulation components such as epoxy poured insulators. Under direct current conditions, the surface of insulation materials is prone to charge accumulation effects, resulting in significant differences in insulation and flashover characteristics compared to AC insulation materials.

High-spatiotemporal-resolution PM2.5 forecasting by hybrid deep learning models with ensembled massive heterogeneous monitoring data

High-resolution real-time air quality forecasting can alert decision-makers and residents about forthcoming air pollution events and refine air quality management. The Environmental Protection Administration in Taiwan has deployed numerous low-cost air quality microsensors near industrial zones lately to facilitate local air quality monitoring. Nevertheless, the frequent occurrence of missing sensor data due to problems of mobile transmission, frontend/backend device malfunction, or other unforeseen issues would raise difficulty in making quick responses to air pollution incidents. This study proposed a hybrid deep learning model (AE-CNN-BP) collaborating an Autoencoder (AE), a Convolutional Neural Network (CNN), and a Back Propagation Neural Network (BPNN) to effectively extract crucial features from big data for making successive high-spatiotemporal-resolution forecasts of PM2.5 concentrations 4 h ahead. The proposed model was trained and tested in three industrial zones densely installed with microsensors in Kaohsiung City of Taiwan. A high pollution incident was selected to evaluate model performance. The results show that the proposed model could reliably produce nice high-spatiotemporal-resolution forecasts for 12 air quality monitoring stations and 485 microsensors, with Coefficient of Determination (R2) values and Root Mean Squared Error (RMSE) of 0.82 (0.76) and 11.05 (12.75) μg/m3 in the training (testing) stage, respectively. For the selected incident, the Mean Absolute Percentage Error (MAPE) values of the proposed model were 22.3% and 27.1% at T+1 and T+4, respectively. This study demonstrates that the proposed deep learning model based on ensemble datasets of sparsely distributed monitoring stations and densely deployed microsensors can offer reliable high-spatiotemporal-resolution air quality forecasts, benefiting environmental studies and informed policymaking by accounting for local-scale variations in PM2.5 concentrations.

A layer potential approach to inverse problems in brain imaging

Abstract We study the inverse source localisation problem using the electric potential measured point-wise inside the head with stereo-ElectroEncephaloGraphy (sEEG), the electric potential measured point-wise on the scalp with ElectroEncephaloGraphy (EEG) or the magnetic flux density measured point-wise outside the head with MagnetoEncephaloGraphy (MEG). We present a method that works on a wide range of models of primary currents; in particular, we give details for primary currents that are assumed to be smooth vector fields that are supported on and normally oriented to the grey/white matter interface. Irrespective of the data used, we also solve the transmission problem of the electric potential associated with a recovered source; hence we solve the cortical mapping problem. To ensure that the electric potential and normal currents are continuous in the head, the electric potential is expressed as a linear combination of double layer potentials and the magnetic flux density is expressed as a linear combination of single layer potentials. Numerically, we solve the problems on meshed surfaces of the grey/white matter interface, cortical surface, skull and scalp. A main feature of the numerical approach we take is that, on the meshed surfaces, we can compute the double and single layer potentials exactly and at arbitrary points. Because we explicitly study the transmission of the electric potential in head when using magnetic data, the coupling of electric and magnetic data in the source recovery problem is made explicit and shows the advantage of using simultaneous electric and magnetic data. We provide numerical examples of the source recovery and inverse cortical mapping using synthetic data.

Study of a Transmission Problem with Friction Law and Increasing Continuous Terms in a Thin Layer

The aim of this paper is to establish the asymptotic analysis of nonlinear boundary value problems. The non-stationary motion is given by the elastic constructive law. The contact is described with a version of Tresca’s law of friction. A variational formulation of the model, in the form of a coupled system for the displacements and the nonlinear source terms, is derived. The existence of a unique weak solution of the model is established. We also give the problem in transpose form, and we demonstrate different estimates of the displacement and of the source term independently of the small parameter. The main corresponding convergence results are stated in the different theorems of the last section.

Power supply station equipment status monitoring and evaluation system based on wireless network technology

With the continuous development of the power industry and the acceleration of the process of intelligence, monitoring and analyzing the status of power supply equipment is crucial for ensuring power supply and safety. Traditional power monitoring systems still have certain problems in data transmission. Using wireless network technology (WNT) to detect and analyze the status of power supply station equipment can not only achieve real-time monitoring and remote control, improve equipment operation and management efficiency, but also achieve automated monitoring and analysis of equipment status, providing technical support for the intelligence of power supply station equipment. In order to verify the effectiveness of the WNT-based power supply station equipment status monitoring and analysis system, a comparative experiment was conducted with traditional wired network monitoring methods. The final experimental results show that the average feedback time for testing the WNT power supply station equipment status monitoring and analysis system is 7.71 s, which is 38.22 s shorter than traditional methods. The average fault location accuracy is 95.98 %, which is 35.91 % higher than traditional methods. The average management efficiency is 92.88 %, which is 34.71 % higher than traditional methods. Through testing data, it can be concluded that the power supply station equipment status monitoring and analysis system based on WNT has greater advantages than traditional power equipment monitoring methods.

Robust Packetized MPC for Networked Systems Subject to Packet Dropouts and Input Saturation With Quantized Feedback.

This article develops a robust packetized predictive control framework to deal with the quantized-feedback control problem of networked systems subject to Markovian packet dropouts and input saturation. In the proposed framework, the Markov chain model of packet dropout is established from the link of the controller to the actuator. To deal with the quantized measurements, a robust packetized predictive control method is presented with a quantized-feedback law. The problem of unreliable transmission is addressed by proposing a packet dropout compensation strategy with a forgetting factor. An augmented Markovian jump system model is established to take the packet dropouts into account. The synthesis of packetized predictive control is then developed by minimizing a worst case cost function with respect to the model uncertainties. The recursive feasibility of the proposed controller design problem and the mean-square stability of the closed-loop systems are proved, respectively. The proposed packetized predictive control method is demonstrated by simulating a four-tank process system.

Biomimicry Architecture for Healthy Built Environment: A Review of Existing Literature

Health issues in the 21st century have become essential in addition to sustainable development issues. Health is an urgent need to find solutions to problems so that human health is always maintained. Health issues are also influenced by the built environment, one of which is studied in the concept of healthy building. A healthy building has several criteria that can be a point of view to see if the building is healthy or unhealthy. Physiological, psychological and disease transmission problems are the main problems faced by users who use unhealthy buildings. Biomimicry architecture emerged due to technological and scientific advances, in which cross-disciplinary science has become the power of knowledge today. Biomimicry architecture is a design approach that uses nature to solve human problems. Health problems and the need to produce healthy buildings can use biomimicry architecture as a problem-solving method. This paper uses a descriptive qualitative content analysis method on various written references related to biomimicry architecture and how biomimicry architecture produces healthy buildings. The conclusion of this study shows that biomimicry architecture is an approach to using natural inspiration to solve human problems, one of which is building health. Implementing principles found in nature delivers buildings designed with a biomimicry architectural approach to be healthier. That is due to the successful application of natural traits that are always adaptive, efficient, effective and live in line with the environment in the built environment.

Reputation-Aware Rate Maximization for Cross-Media Cooperative Transmission in Smart Ocean IoT

In smart ocean Internet of Things (IoT) systems, autonomous underwater vehicles (AUVs) are responsible for underwater information collection. Due to the nature of the medium of water, the acoustic communications for AUVs are of low bandwidth and adverse environmental conditions causing severe transmission problems. In order to realize cross-media transmission from AUVs to the offshore platform, unmanned surface vehicles (USVs) have been suggested to forward the collected information in a coordinated manner. Against this backdrop, this contribution develops a cooperative USV-to-USV (U2U) cross-media cooperative communications scheme. Then, we formulate a rate maximization problem with the objective of optimizing the reputation-aware USV selection strategy. Furthermore, to characterize the impact of the mobility of AUVs/USVs, a long-term dynamic process is constructed. Meanwhile, we also develop an efficient algorithm which transforms the reputation-aided dynamic USVs selection problem into the infinite time horizon average one restricted by time average rate constraints in the collection of penalty processes with the help of the Lyapunov optimization framework and drift-plus-penalty method. Finally, numerical results are presented to validate the convergence behavior and the performance for the designed dynamic USVs selection algorithm.

On the uniqueness theorems for transmission problems related to models of elasticity, diffusion and electrocardiography

Abstract We consider a generalization of the inverse problem of the electrocardiography in the framework of the theory of elliptic and parabolic differential operators. More precisely, starting with the standard bidomain mathematical model related to the problem of the reconstruction of the transmembrane potential in the myocardium from known body surface potentials, we formulate a more general transmission problem for elliptic and parabolic equations in the Sobolev type spaces and describe conditions, providing uniqueness theorems for its solutions. Next, the new transmission problem is interpreted in the framework of the elasticity theory applied to composite media. Finally, we prove a uniqueness theorem for an evolutionary transmission problem that can be easily adopted to many models involving the diffusion type equations.

Numerical analysis for electromagnetic scattering with nonlinear boundary conditions

This work studies time-dependent electromagnetic scattering from obstacles whose interaction with the wave is fully determined by a nonlinear boundary condition. In particular, the boundary condition studied in this work enforces a power law type relation between the electric and magnetic fields along the boundary. Based on time-dependent jump relations of classical boundary operators, we derive a nonlinear system of time-dependent boundary integral equations that determines the tangential traces of the scattered electric and magnetic fields. These fields can subsequently be computed at arbitrary points in the exterior domain by evaluating a time-dependent representation formula. Fully discrete schemes are obtained by discretizing the nonlinear system of boundary integral equations with Runge–Kutta based convolution quadrature in time and Raviart–Thomas boundary elements in space. Error bounds with explicitly stated convergence rates are proven, under the assumption of sufficient regularity of the exact solution. The error analysis is conducted through novel techniques based on time-discrete transmission problems and the use of a new discrete partial integration inequality. Numerical experiments illustrate the use of the proposed method and provide empirical convergence rates.

Regularity of viscosity solutions to fully nonlinear elliptic transmission problems

We develop the regularity theory of viscosity solutions to transmission problems for fully nonlinear second order uniformly elliptic equations. Our results give a complete theory of existence, uniqueness, comparison principle, and regularity of solutions to flat interface transmission problems; and the C0,α, C1,α and C2,α regularity of viscosity solutions up to the transmission surface for the case of curved interfaces.

Transmission problems? An embedded approach for unification of Latin prefixes and text variants during text matching

Abstract The manuscript tradition of pre-modern texts poses a specific problem for scholars in the field of Digital Humanities: before printing made the production of standardized editions of texts feasible, copying texts by hand (and often by different people) was inherently an error-prone process, which not only led to differences in wording but also in spelling—across multiple transmitted variants. This applies especially to ancient texts, where the temporal distances to the archetypes tend to be fairly large. In computerized research, especially in the case of text matching within the field of citation research and text mining, these differences in wording and spelling—however small they might be—may prevent a successful matching of texts. This case study presents a solution for the problem of textual differences arising from (non-)assimilated prefixes in Latin, a feature where modern editions mostly differ from author to author, but sometimes even between two editions of the same text. With regard to the letters of the church father Jerome as well as Virgil’s Eclogues, Georgics, and Aeneid, two approaches are compared in terms of error rate and efficiency for a given set of prefixes: (1) performing and (2) reversing corpus-wide assimilation. Moreover, the broader implications of the (in-)accessibility of text-critical data in digital editions are discussed. Finally, general desiderata regarding text-critical data for computerized research on classical texts are elaborated.

Uniqueness in determining rectangular grating profiles with a single incoming wave (part II): TM polarization case

This paper is concerned with an inverse transmission problem for recovering the shape of a penetrable rectangular grating sitting on a perfectly conducting plate. We consider a general transmission problem with the coefficient λ ≠ 1 which covers the transverse magnetic (TM) polarization case. It is proved that a rectangular grating profile can be uniquely determined by the near-field observation data incited by a single plane wave and measured on a line segment above the grating. In comparison with the transverse electric (TE) case (λ = 1), the wave field cannot lie in H 2 around each corner point, bringing essential difficulties in proving uniqueness with one plane wave. Our approach relies on singularity analysis for Helmholtz transmission problems in a right-corner domain and also provides an alternative idea for treating the TE transmission conditions which were considered in the authors’ previous work (Xiang and Hu 2023 Inverse Problems 39 055004).

Well-posedness and polynomial energy decay rate of a transmission problem for Rayleigh beam model with heat conduction

In this paper, we investigate the stability of the transmission problem for Rayleigh beam model with heat conduction. First, we reformulate our system into an evolution equation and prove our problem’s well-posedness. Next, we demonstrate the resolvent of the operator is compact in the energy space, then by using the general criteria of Arendt–Batty, we prove that the thermal dissipation is enough to stabilize our model. Finally, a polynomial energy decay rate has been obtained which depends on the mass densities and the moments of inertia of the Rayleigh beams.

Composite reliability assessment of systems with grid‐edge renewable resources via quasi‐sequential Monte Carlo and cross‐entropy techniques

AbstractThe still growing share of intermittent renewable sources in the electric energy matrix is a factor that greatly increases the complexity of modelling electrical power systems. Although its exploitation is conditioned to the geographic location where the natural resource emerges itself, when this location coincides with the grid‐edge of the system, close to the consumer, the composite reliability assessment is exposed to the combination of two problems: (i) representation of the intermittent energy availability of generators; and (ii) failure event rarity. To address the first problem, a fast Monte Carlo tool capable of representing chronological aspects can be used. For the second problem, an efficient variance reduction technique that adapts well to the composite problem of generation and transmission must be established. Therefore, a quasi‐sequential Monte Carlo simulation tool aided by importance sampling via the cross‐entropy method is proposed as an efficient and robust procedure for evaluating the composite reliability of systems with renewable participation at grid‐edge. The method is evaluated through a modified version of the IEEE Reliability Test System ‐ 1996, which presents renewable generation in consumer load buses and rarity in the composite failure.

About the problem of wordplay transmission (based on the material of English and Russian advertising texts)

The object of the study is examples of the use of wordplay in the advertising texts translated from English into Russian. The subject of the study is the translation techniques used by translators to preserve the communicative orientation and impact on the reader. The choice of the research object is due to the prevalence of advertising text in the modern world, which implies the need to develop common translation standards and examples of solutions to emerging difficulties. The problem of translating different types of wordplay has been little studied in modern linguistics, which determines the need for further research. Even less studied is the problem of translating wordplay in advertising slogans in a comparative aspect. The analysis of the collected material allowed us to identify three main translation strategies: the transmission of wordplay, in which the method of wordplay formation is preserved; transmission, in which the preservation of the method of wordplay formation is impossible or undesirable; transmission, in which the preservation of wordplay itself is impossible. In the latter case, translators often have to sacrifice the communicative effect, which is not desirable from the standpoint of modern translation studies. The article concludes that the linguistic features of slogans and, in particular, the use of wordplay in them must be taken into account when translating in order to ensure maximum preservation of communicative intent and communicative effect.

A Long Short-Term Memory-Based Model for Kinesthetic Data Reduction

This paper proposes a novel mathematical model for teleoperation over communication networks. For teleoperation over a communication network, a high packet rate can result in inefficient data transmission and cross-traffic problems, leading to extra delay and jitter. This paper proposes an LSTM-based mathematical model which focuses on kinesthetic data reduction without loss of transparency during the transmission process through joint training combined with haptic data and perceptual deadband. Since the LSTM network can deal with a time series of haptic data, we further test the system performance through practically collected data. We investigate the packet rate and perceptual transparency of the proposed mathematical model by comparing with the conventional deadband. Additionally, we compare the proposed mathematical model with the perceptual deadband-based codecs. Simulation results show that the proposed solution further reduces the packet rate when dealing with haptic data without noticeable distortion. Also, comparing with the current JND perceptual threshold, the proposed mathematical model helps improve the practicality of the bilateral teleoperation system without losing transparency.

Fast and accurate boundary element methods for large-scale computational acoustics

The boundary element method (BEM) is a powerful algorithm to solve the Helmholtz equation for harmonic acoustic waves. The explicit use of Green’s functions avoids domain truncation of unbounded regions and accurately models wave propagation through homogeneous materials. Furthermore, fast multipole and hierarchical compression techniques provide efficient computations for dense matrix multiplications. However, the convergence of the iterative linear solvers deteriorates significantly when frequencies are high or materials have large contrasts in density or speed of sound. This talk presents several algorithmic improvements of the BEM. First, a preconditioner based on on-surface radiation conditions drastically reduces the iteration count of linear solvers at high frequencies. Second, anovel boundary integral formulation remains well-conditioned for high-contrast transmission problems. We used our fast and accurate BEM implementation to simulate focused ultrasound propagation in the human body, which can be translated to important biomedical applications such as the non-invasive treatment of liver cancer and neuromodulation of the brain. We validated the methodology within the benchmarking exercise of the International Transcranial Ultrasonic Stimulation Safety and Standards (ITRUSST) consortium. As a second application, we simulated the collective resonances of water-entrained arrays of air bubbles. Finally, we implemented all functionality in our open-source Python library, OptimUS.