Multilayer Topology Research Articles

The Improved Nonparametric Regression Model for the IoT Link Load Balancing Control Algorithm

In order to improve the load balance control effect of the Internet of Things link, this paper combines the nonparametric regression model to improve the load balancing algorithm of the Internet of Things link. Moreover, this paper proposes a load balancing research strategy based on data plane data flow, which is aimed at improving the load balancing problem of data flow in the link. The data center network uses a multilayer fat tree topology to store information in the flow table corresponding to the switch for data flow processing and forwarding operations. In addition, this paper constructs a load balancing model for intelligent Internet of Things link and verifies the model in this paper through experimental research. The research results show that the load balancing control algorithm for Internet of Things link based on the nonparametric regression model proposed in this paper can effectively improve the internal scheduling of the Internet of Things link system and promote the load balancing effect.

Surface Spin-Wave Propagation in the Orthogonal Transverse Junction of YIG-Based Magnonic Stripes

In this article, we experimentally demonstrate the propagation of magnetostatic surface spin wave (MSSW) in the orthogonally joined yttrium iron garnet stripes in the form of T-shaped connection. By the means of microwave spectroscopy technique, we show how the transmission is affected by the distance between orthogonal yttrium iron garnet stripes. Micromagnetic modeling demonstrates the presence of nonreciprocal propagation of spin waves (SWs) between all three ports of the T-junction. A mechanism for controlling the spatial-frequency selection of a propagating signal by variation of the air gap in the area of connected orthogonal sections is shown. The proposed structure can act as a magnonic splitter for 3-D topology of multilevel magnonic networks (MNs). The transition to a multilayer topology of MNs opens the possibility of increase of the packing density of computational units based on the principles of magnonics.

Impact of interactions between layers on source localization in multilayer networks

Nowadays it is not uncommon to have to deal with dissemination on multilayer networks and often finding the source of said propagation can be a crucial task. We examine the issue of locating the source of Susceptible–Infected spreading process in a multilayer network using the Bayesian inference and the maximum likelihood method established for general networks and adapted here to cover multilayer topology. We show how its accuracy depends on network and spreading parameters and find the existence of two parameter ranges with different behavior. If inter-network spreading rate is low, observations in different layers interfere, lowering accuracy below that of relying on single layer observers only. If it is high, on the other hand, observations synergize, raising accuracy above the level of single layer network of the same size and observer density. We also show a heuristic method to determine the case in a system and potentially improve accuracy by rejecting interfering observations. This paper is dedicated to the memory of Professor Dietrich Stauffer, who was a pioneer in new approaches in statistical physics and its interdisciplinary applications.

Design of wideband multi-layer quadrature hybrid couplers with butterfly shaped resonators

AbstractIn this paper, a wideband quadrature hybrid coupler is presented. The proposed structure has a multi-layer microstrip topology. In this topology, there are three substrate layers including prepreg material and four conductive layers. In order to achieve equal power division between through and coupled arms of the directional coupler while maintaining a 90° phase shift, aperture coupling between the resonators located at both top and bottom layers is utilized. So as to avoid any unwanted effects of prepreg material in such multilayer topology, via shielding around resonators are inserted. In this study, coupling from input ports to output ports is accomplished by the shielded butterfly shaped slot etched to the ground layer of top and bottom layers. The proposed design operates within 3–12 GHz. The acquired phase imbalance between the coupled ports is <±2.5°. The results of the manufactured quadrature hybrid coupler agree well with the simulated results.

Part consolidation for additive manufacturing: A multilayered topology optimization approach

AbstractPart consolidation (PC) is becoming a viable cost savings approach due to the increased design freedom associated with industry adoption of additive manufacturing. However, there is little research focused on mathematical approaches for assembly level design generation, with most work aimed at providing best practices for merging several parts into one. This article presents a novel topology optimization approach to PC that determines the ideal number of parts, their geometry, and optimal joining pattern, without bias towards the original assembly. Multiple layered design domains are created, and a joining domain that determines the connections between parts is introduced. A multiobjective problem statement optimizes the complex trade‐off between compliance, support structure volume, surface area, and number of joints, to minimize the total cost of the final assembly. Design variable initialization and boundary condition placement are discussed for problems with multiple domains. Three test cases are presented and solved for a range of cost trade‐offs to demonstrate optimized solutions as design objectives are varied.

Ethanol Fuel Demand Forecasting in Brazil Using a LSTM Recurrent Neural Network Approach

Ethanol is a biofuel widely consumed in Brazil, which functions as a substitute for gasoline since the late 1970s. Due to several fluctuations in the characteristics of the Brazilian vehicle fleet and the political-economic conditions of the country, forecasting ethanol consumption has become a difficult task to perform. Under this scenario, the aim of this paper was to forecast ethanol consumption in Brazil using an approach of Long-Short Term Memory (LSTM) Recurrent Neural Networks (RNN) and Autoregressive Integrated Moving Average (ARIMA) models. The above, taking into consideration univariate and multivariate models for each case. Likewise, single-layer and multi-layer topologies of LSTM RNN were explored in this study. The results show that LSTM models overperformed ARIMA models even working with a relatively small training dataset of just 180 instances. This, for both univariate and multivariate models. A novel approach for searching suitable LSTM Neural Network topologies is proposed in this paper.

Multi-Layer and Conformally Integrated Structurally Embedded Vascular Antenna (SEVA) Arrays.

This work presents the design and fabrication of two multi-element structurally embedded vascular antennas (SEVAs). These are achieved through advances in additively manufactured sacrificial materials and demonstrate the ability to embed vascular microchannels in both planar and complex-curved epoxy-filled quartz fiber structural composite panels. Frequency-reconfigurable antennas are formed by these structures through the pressure-driven transport of liquid metal through the embedded microchannels. The planar multi-layer topology examines the ability to fabricate two co-located radiating structures separated by a single ply of quartz fabric within the composite layup. The multi-element linear array topology composed of microchannels embedded on to a single-layer are used to demonstrate the ability to conformally-integrate these channels into a complex curved surface that mimics an array of antennas on the leading edge of an Unmanned Aerial Vehicle (UAV). A parallel-strip antipodal dipole feed structure provides excitation and serves as the interface for fluid displacement within the microchannels to facilitate reconfiguration. The nominal design of the SEVAs achieve over a decade of frequency reconfiguration with respect to the fundamental dipole mode of the antenna. Experimental and predicted results demonstrate the operation for canonical states of the antennas. Additional results for the array topology demonstrate beam steering and contiguous operation of interconnected elements in the multi-element structure.

Design of efficient multilayer RAM cell in QCA framework

PurposeQuantum-dot cellular automata (QCA) is a promising technology, which seems to be the prospective substitute for complementary metal-oxide semiconductor (CMOS). It is a high speed, high density and low power paradigm producing efficient circuits. These days, most of the smart devices used for computing, make use of random access memory (RAM). To enhance the performance of a RAM cell, researchers are putting effort to minimize its area and access time. Multilayer structures in QCA framework are area efficient, fast and immune to the random interference. Unlike CMOS, QCA multilayer architectures can be designed using active components on different layers. Thus, using multilayer topology in the design of a RAM cell, which is not yet reported in the literature can improve the performance of RAM and hence, the computing device. This paper aims to present the modular design of RAM cell with multilayer structures in the QCA framework. The fundamental modules such as XOR gate, 2:1 multiplexer and D latch are proposed here using multilayer formations with the goal of designing a RAM cell with the provision of read, write, set and reset control.Design/methodology/approachAll the modules used to design a RAM cell are designed using multilayer approach in QCA framework.FindingsThe proposed multilayer RAM cell is optimized and has shown an improvement of 20% in cell count, 30% in area, 25% in area latency product and 48.8% in cost function over the other efficient RAM designs with set/reset ability reported earlier. The proposed RAM cell is further analyzed for the fault tolerance and power dissipation.Research limitations/implicationsDue to the multilayer structure, the complexity of the circuit enhances which can be eliminated using simple architectures.Originality/valueThe performance metrics and results obtained establish that the multilayer approach can be implemented in the QCA circuit to produce area efficient and optimized sequential circuits such as a latch, flip flop and memory cells.

Частотно-селективное распространение спиновых волн в трехмерном магнонном Т-образном сплиттере

Using numerical and experimental methods, the mechanism of control of the transmission of a spin-wave signal in a three-dimensional magnon splitter, formed by an orthogonal junction of magnetic strips of yttrium iron garnet, has been investigated. It is shown that by variation the size of the air gap between the spin-waveguide sections, it is possible to control the selection of the signal propagating in the output sections of the structure. From an applied point of view, the results obtained can be used to create an interconnection element in multilevel magnon information processing devices for the formation of multilayer magnon network topologies and miniaturization of computing devices based on the principles of magnonics. Key words: spin waves, magnonics, three-dimensional interconnections, micromagnetic modeling.

Fullwave Maxwell inverse design of axisymmetric, tunable, and multi-scale multi-wavelength metalenses.

We demonstrate new axisymmetric inverse-design techniques that can solve problems radically different from traditional lenses, including reconfigurable lenses (that shift a multi-frequency focal spot in response to refractive-index changes) and widely separated multi-wavelength lenses (λ = 1 µm and 10 µm). We also present experimental validation for an axisymmetric inverse-designed monochrome lens in the near-infrared fabricated via two-photon polymerization. Axisymmetry allows fullwave Maxwell solvers to be scaled up to structures hundreds or even thousands of wavelengths in diameter before requiring domain-decomposition approximations, while multilayer topology optimization with ∼105 degrees of freedom can tackle challenging design problems even when restricted to axisymmetric structures.

Compensating atmospheric turbulence with CNNs for defocused pupil image wavefront sensors

Abstract Adaptive optics are techniques used for processing the spatial resolution of astronomical images taken from large ground-based telescopes. In this work, computational results are presented for a modified curvature sensor, the tomographic pupil image wavefront sensor (TPI-WFS), which measures the turbulence of the atmosphere, expressed in terms of an expansion over Zernike polynomials. Convolutional neural networks (CNN) are presented as an alternative to the TPI-WFS reconstruction. This technique is a machine learning model of the family of artificial neural networks, which are widely known for its performance as modeling and prediction technique in complex systems. Results obtained from the reconstruction of the networks are compared with the TPI-WFS reconstruction by estimating errors and optical measurements (root mean square error, mean structural similarity and Strehl ratio). The reconstructed wavefronts from both techniques are compared for wavefronts of 153 Zernike modes. For this case, a detailed comparison and grid search to find the most suitable neural network is performed, searching between multi-layer perceptron, CNN and recurrent networks topologies. In general, the best network was a CNN trained for TPI-WFS reconstruction, achieving better performance than the reconstruction software from TPI-WFS in most of the turbulent profiles, but the most significant improvements were found for higher turbulent profiles that have the lowest r0 values.

Toward a Multi-Layered Chiasme-Focused Topology: A Reading of Merleau-Ponty’s Later Writings

Toward a Multi-Layered Chiasme-Focused Topology: A Reading of Merleau-Ponty’s Later Writings

Low-Cost Automated Design of Compact Branch-Line Couplers.

Branch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important pre-requisite for their application in modern devices. State-of-the-art approaches to design compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line sections of the circuit, with their composite counterparts, referred to as compact cells (CCs). Due to the efficient use of available space, CC-based couplers are often characterized by small footprints. The design of compact BLCs is normally conducted based on engineering experience. The process is laborious and requires many adjustments of topology followed by manual or, semi-automatic tuning of design parameters. In this work, a framework for low-cost automated design of compact BLCs using pre-defined CCs is proposed. The low cost of the presented design technique is ensured using equivalent-circuit models, space mapping correction methods, and trust-region-based local optimization algorithms. The performance of the framework is demonstrated based on three examples, concerning the design of unequal-power split coupler, comparison of automatically generated compact BLCs, as well as rapid re-design of the coupler for different substrates. Furthermore, the approach has been benchmarked against the state-of-the-art methods for low-cost design of circuits.

Multilayer Topology Optimization of Wideband SIW-to-Waveguide Transitions

This article utilizes a topology optimization approach to design planar multilayer transitions between substrate integrated waveguides (SIWs) and rectangular waveguides (RWGs). The optimization problem is formulated based on the modal field analyses and Maxwell’s equations in the time domain solved by the finite-difference time-domain (FDTD) method. We present a time-domain boundary condition based on the Klein–Gordon equation to split traveling waves at homogeneous waveguide ports. We employ the boundary condition to compute portal quantities and to devise an adjoint-field system that enabled an efficient computation of the objective function gradient. We solve design problems that include more than 105 000 design variables by using less than 400 solutions of Maxwell’s equations. Moreover, a new formulation that effectively combats the development of in-band resonances in the design is presented. The transition configuration allows the direct mount of conventional RWG sections on the circuit board and aims to cover the entire K-band. The guiding structure of the optimized transition requires blind vias, which is realized by a simple and cost-efficient technique. In addition, the transition is optimized for three different setups that can be used to provide different field polarizations. The proposed transitions show less than 1-dB insertion loss and around 15-dB return loss over the frequency interval 18–28 GHz. Several prototypes are fabricated with an excellent match between the simulation and measurement results.

Diffusion-bonded W-band monopulse array antenna for space debris radar

In this letter, the design and fabrication of a W-band high-gain monopulse array antenna are presented. The antenna is conceived as a proof of concept for a space debris detection project to develop an on-board radar for a satellite system. The antenna array consists of 16 by 16 circularly polarized radiating cavities fed by a corporate waveguide network with an amplitude taper. An underlying monopulse beamforming network is implemented in waveguide technology as well, providing monopulse capability in both main radiating planes. By means of diffusion bonding, the antenna has been fabricated in a single piece, despite its intricate, multilayer topology. Moreover, the experimental performance shows high agreement with simulations, which is remarkable due to the high sensitivity to manufacturing tolerances at this frequency. Over a 10% bandwidth is experimentally achieved for efficiency over a 75%, axial ratio under 3 dB and impedance matching under −10 dB.

Synchronization Patterns in Modular Neuronal Networks: A Case Study of C. elegans

We investigate synchronization patterns and chimera-like states in the modular multilayer topology of the connectome of Caenorhabditis elegans. In the special case of a designed network with two layers, one with electrical intra-community links and one with chemical inter-community links, chimera-like states are known to exist. Aiming at a more biological approach based on the actual connectivity data, we consider a network consisting of two synaptic (electrical and chemical) and one extrasynaptic (wireless) layers. Analyzing the structure and properties of this layered network using Multilayer-Louvain community detection, we identify modules whose nodes are more strongly coupled with each other than with the rest of the network. Based on this topology, we study the dynamics of coupled Hindmarsh-Rose neurons. Emerging synchronization patterns are quantified using the pairwise Euclidean distances between the values of all oscillators, locally within each community and globally across the network. We find a tendency of the wireless coupling to moderate the average coherence of the system: for stronger wireless coupling, the levels of synchronization decrease both locally and globally, and chimera-like states are not favored. By introducing an alternative method to define meaningful communities based on the dynamical correlations of the nodes, we obtain a structure that is dominated by two large communities. This promotes the emergence of chimera-like states and allows to relate the dynamics of the corresponding neurons to biological neuronal functions such as motor activities.

Design of New Dual-Stator Field Modulation Machines

This article proposes a general design method for dual-stator field modulation machines (DSFMMs) that can be separated into two field modulation machine (FMM) portions sharing the key components with each other. The existing permanent-magnet synchronous machines and FMMs can be categorized into R/S types, where R denotes the part that can generate the rotating magnetic field, and S represents the stationary modulator. R and S can be used to derive various DSFMM topologies that take advantage of the high toque density. The combined machines employ the multilayer topology that provides space for multi-PM-excitation and multimodulation. The general design principle, simplest R/S-type machine, and the coupled armature winding configuration are discussed, and the modulated air-gap working harmonic components are investigated. Four representative dual-stator machines are developed based on the proposed method. The proposed hybrid-magnet DSFMM (HM-DSFMM) has the merits of high power factor, low cogging torque, and low torque ripple. The prototype of the HM-DSFMM is manufactured and tested. The result comparisons of the finite-element-analysis prediction and measurement verify the electromagnetic design.

Synergistic Topology Generation and Route Synthesis for On-Chip Performance-Critical Signal Groups

As very large scale integration technology scales to deep submicron, design for interconnections becomes increasingly challenging. The traditional bus routing follows a sequential bit-by-bit order, and few works explicitly target interbit regularity for signal groups via multilayer topology selection. To overcome these limitations, we present $\mathsf {Streak}$ , an efficient framework that combines topology generation and wire synthesis with a global view of optimization and constrained metal layer track resource allocation. In the framework, an identification stage decomposes binding groups into a set of representative objects; with the generated backbones, equivalent topologies are accompanied by the bits in every object; then a formulation guides the routing considering wire congestion and design regularity. Furthermore, a bottom-up clustering methodology based on layer prediction targets to enhance the routability; a post-refinement stage is developed to match the source-to-sink distance deviation among bits in one group. Experimental results using industrial benchmarks demonstrate the effectiveness of the proposed technique.

Layer-Edge Patterns Exploration and Presentation in Multiplex Networks: From Detail to Overview via Selections and Aggregations

Multiplex networks have been widely used to describe the multi-type connections of entities in the real world. However, researches for multiplex networks visualization unilaterally focus on the presentation of topological structure, lacking of specific high-level information presentation for quantitative comparison of interlayer structure. Users cannot participate in the exploration and freely choose the layers (or sub-graphs, regions, etc.) of interest for structural comparison. Contraposing the layer-edge patterns visual analysis tasks of multiplex networks, this paper puts forward a novel solution for exploration and analysis that tightly couples topological structure and high-level patterns. It mainly contains a multi-force directed model to realize the balanced layout of nodes in multi-layer topology, as well as two kinds of high-level patterns of which the visual representations are, respectively, designed by a familiar metaphor—that is, the similar pattern representation based on the area-proportional Venn diagrams and the interaction pattern representation based on the directed arrows. Furthermore, views association is implemented through underlying data sharing and multiple interactions which can be used to gain insights through the creation of selections of interest and produce high-level infographic-style overviews simultaneously. The experiments on real-world data demonstrate the support of the proposed method for layer-edge patterns analysis tasks in multiplex networks and the effectiveness for analyzing the multi-layer structure of multiplex networks.

Technical Methods and Facilities of Printed-Film Topology Reengineering of Radio-Electronic Products

t—The methods and facilities of reengineering the topology of multilayered printed modules and case-type integrated microcircuits are considered. Concepts of reengineering modernization of the products of radio-electronics are formulated. Basic technological processes of schematic configuration reengineering of printed-film electronic products are presented, which are based on different physical principles of destructive (machining and chemical etching) and nondestructive study: optical scanning, radio-wave imaging, and X-ray analysis. The method of infrared imaging (electric-induction) analysis of printed circuit boards with multilayer topology was proposed for the first time.