Diagonal Edges Research Articles

Microstrip Patch Antenna Design for Enhanced Bandwidth and Harmonic Suppression

Antennas are essential components in wireless communication systems, often requiring a delicate balance between achieving wide bandwidth and suppressing harmonics effectively. This study focuses on the integration of defected ground structures (DGS) to enhance antenna performance. Through rigorous experimentation and analysis, the research aimed to optimize microstrip patch antenna designs for improved bandwidth while maintaining efficient harmonic suppression. The investigation involved parametric studies to determine the optimal dimensions and configurations of DGS for wideband-stop characteristics. Simulation tools were utilized to analyse the impact of DGS on the antenna's behaviour, leading to the development of an accurate equivalent circuit model. Current distribution analysis provided insights into the radiation pattern and impedance matching of the antennas with and without DGS. Experimental results demonstrated significant improvements in antenna performance. The measured reflection coefficient values indicated successful harmonic suppression, with reductions around 22 dB at the third harmonic frequency. The input impedance values were optimized to utilize a modified ground plane featuring diagonal edges and a rectangular slot cut to design compact antennas, contributing to enhanced bandwidth and improved overall performance. Radiation pattern measurements validated the effectiveness of the optimized designs. This study demonstrates successful integration of DGS into slot antennas, achieving wider bandwidth with robust harmonic suppression. Experimental results validate design strategies, offering insights for high-performance slot antennas in modern communication systems.

Enhance Hydrogen Evolution Reaction Performance via Double-Stacked Edges of Black Phosphorene.

Based on the density functional theory (DFT) calculations, we explored the structures and HER catalytic properties of reconstructed and double-stacked black phosphorene (BP) edges. Ten bilayer BP edges were constructed by the double stacking of three typical monolayer edges, i.e., zigzag (ZZ) edge, armchair (AC) edge, skewed diagonal (SD) edge, and their reconstructed derivatives with their layer's configurations, edge deformations and thermodynamic stabilities were discussed. Based on these edges, five chemical sites on four bilayer BP edges were selected to be promising candidates for a HER catalyst, which present higher HER activities than that of Pt(111). Besides, among these four edges, two edges have even lower energetic barriers for the Tafel reaction. Compared with the monolayer edges, these selected bilayer BP edges confirm the remarkable enhancement of the HER catalytic properties, which can be attributed to their unique edge structures and the enhanced electronic densities after the hydrogen adsorptions. Finally, the thermostability of these edges at room temperature has also been proved by the DFT-MD simulations. This theoretic study deepens our fundamental understanding of the double-stacked edge structures of the BP and provides a new way for the rational design of highly efficient and noble-metal-free HER catalysts.

Computing Data-driven Multilinear Metro Maps

ABSTRACT Traditionally, most schematic metro maps in practice as well as metro map layout algorithms adhere to an octolinear layout style with all paths composed of horizontal, vertical, and 45 ∘ -diagonal edges. Despite growing interest in more general multilinear metro maps, generic algorithms to draw metro maps based on a system of k ≥ 2 not necessarily equidistant slopes have not been investigated thoroughly. In this paper, we present and implement an adaptation of the octolinear mixed-integer linear programming approach of Nöllenburg and Wolff (2011) that can draw metro maps schematized to any set C of arbitrary orientations. We further present a data-driven approach to determine a suitable set C by either detecting the best rotation of an equidistant orientation system or by clustering the input edge orientations using a k-medians algorithm. We demonstrate the new possibilities of our method using several real-world examples.

A novel dual-sense polarization reconfigurable dual-band microstrip antenna

In this paper, a novel dual-band, dual-sense, polarization reconfigurable dual coupled line square microstrip patch antenna is proposed. It comprises of a diagonal edge truncated square microstrip patch with a dual coupled line structure. The dual-band operation is realized by using dual coupled lines. They also aid in generating dual-sense of circular polarization (CP) at two resonances. The diagonal edge truncated square patch consists of four PIN diodes along with the bias circuit. It realizes a dual-sense of polarization reconfiguration like right-handed circular polarization (RHCP)/left-handed circular polarization (LHCP), linear polarization (LP)/LHCP, RHCP/LP at lower resonance f1 = 2.4 GHz and higher resonance f2 = 2.6 GHz respectively for different states of the diodes. The proposed antenna is designed, simulated, fabricated, and experimentally tested for validation. The experimental results of −10 dB reflection coefficient, 3 dB axial ratio for CP, gain, and radiation pattern characteristics at the two bands are acceptable and are found to be in concurrence with simulation results in all the states. The proposed antenna would be useful for multifunctional wireless communication applications.

A practical design of cold-formed steel bolted moment connection: numerical investigation with an improved bolt slip-bearing model

Cold-formed steel (CFS) is in the spotlight as a structural material for buildings and civil infrastructures because it is easy to produce and is cost effective. Recent studies have advanced the popularity and usability of CFS even more by showing its potential as a structural member suitable for special moment-resisting structures. Within the framework of those studies, CFS bolted moment-resisting connections allow the through-plate to protrude beyond the beam depth in both the upper and lower directions, like wings, which could hamper placing decks on the beams. This study proposes a modification to such through-plates, in which one protruded portion is eliminated and the depth of the other is extended instead in order to enhance the practicality in field applications. Finite element analysis is used to investigate and verify the proposed design candidates and finally, suggest an optimum design configuration. Since the bolted connection has a significant impact on the structural response of the CFS beam, an improved bolt modeling approach is suggested based on the bolt modeling approaches proposed by past researchers. The suggested bolt modeling approach is shown to provide better accuracy in simulating plastic deformations in the bolted connection area and the consequent failure behavior when compared to the existing approach. The numerical analysis results show that the through-plate with one wing-side cut should have the depth of the other wing-side such that the diagonal edge could make an angle larger than 35 degrees. To prevent the possibility of buckling in the changed through-plate, attaching the flange plate perpendicular to the diagonal edge is highly recommended. The findings from this study are expected to provide a guidance for the through-plate design in practical structure design. • A practical design for through-plate in CFS bolted connections is suggested. • Modeling approach for bolted connections based on measured torque is proposed. • In modeling of bolted connection, effect of rotational constraint is critical. • Significance of bolt slip-bearing mechanism included in bolt modeling is emphasized.

Controlling localized states in a two-leg ladder lattice with diagonal edges via gain/loss [Invited

Gain and loss engineering can bring fascinating physical phenomena and lead to useful potential applications in optics and photonics. Here we study a two-leg ladder lattice with diagonal-edge open boundary condition which supports zero-energy modes with localization phenomena. By considering the on-site gain and loss on two legs respectively, we see the phase transition of features from localization at edges to extension into bulk. Meanwhile, the effective magnetic flux can further enhance the localization effect. Simulations are performed to verify the manipulation of localization via gain and loss in our model. This work offers the opportunity for controlling the localized states in a finite system through the non-Hermiticity and shows potential application towards implementing high-power laser arrays in both real space and synthetic dimensions.

Trace Concealment Histogram-Shifting-Based Reversible Data Hiding with Improved Skipping Embedding and High-Precision Edge Predictor (ChinaMFS 2022)

Reversible data hiding (RDH) is a special class of steganography, in which the cover image can be perfectly recovered upon the extraction of the secret data. However, most image-based RDH schemes focus on improving capacity–distortion performance. In this paper, we propose a novel RDH scheme which not only effectively conceals the traces left by HS but also improves capacity–distortion performance. First, high-precision edge predictor LS-ET (Least Square predictor with Edge Type) is proposed, and the predictor divides pixels into five types, i.e., weak edge, horizontal edge, vertical edge, positive diagonal edge, and negative diagonal edge. Different types of target pixels utilize different training pixels with stronger local consistency to improve accuracy. Then, a novel prediction-based histogram-shifting (HS) framework is designed to conceal embedding traces in the stego images. Finally, we improve both the data-coding method and the skipping embedding strategy to improve the image quality. Experimental results demonstrate that the capacity–distortion performance of the proposed scheme outperforms the other trace concealment schemes and is comparable to the state-of-the-art schemes utilizing sorting technique, multiple histogram modification, and excellent LS-based predictors. Moreover, it can conceal the embedding traces left by the traditional HS schemes to a certain extent, reducing the risk of being steganalyzed.

Variational quantum eigensolver ansatz for the J1−J2 -model

The ground state properties of the two-dimensional ${J}_{1}\ensuremath{-}{J}_{2}$-model are very challenging to analyze via classical numerical methods due to the high level of frustration. This makes the model a promising candidate for which quantum computers could be helpful to possibly explore regimes that classical computers cannot reach. The ${J}_{1}\ensuremath{-}{J}_{2}$-model is a quantum spin model composed of Heisenberg interactions along the rectangular lattice edges and along diagonal edges between next-nearest-neighbor spins. We propose an ansatz for the variational quantum eigensolver to approximate the ground state of an antiferromagnetic ${J}_{1}\ensuremath{-}{J}_{2}$ Hamiltonian for different lattice sizes and different ratios of ${J}_{1}$ and ${J}_{2}$. Moreover, we demonstrate that this ansatz can work without the need for gates along the diagonal next-nearest-neighbor interactions. This simplification is of great importance for solid-state-based hardware with qubits on a rectangular grid, where it eliminates the need for swap gates. In addition, we provide an extrapolation for the number of gates and parameters needed for larger lattice sizes, showing that these are expected to grow linearly in the qubit number up to lattice sizes which eventually can no longer be treated with classical computers.

Applications for Green Technology Practices in Analyzing the Edge Detection Techniques on Digital Image Processing by using MATLAB

Increasing awareness and growing focus on environmental issues such as climate change, energy use, and the loss of non-renewable resources have created a great need for research that provides possible solutions to these problems. Environmental science and engineering research continue to play an important role in revealing new “green” future opportunities. Digital Image Processing plays a major role in contributing to its relevant research works under these Environmental and Green Technologies. By applying tools related to Environment technology this Digital Image Processing produces numerous applications. In such cases, Edges provide an important dynamic change in digital image processing. It is a process of finding and finding edges with sharp changes made by the power of its images. This is the best way to get an accurate edge in good shape and also different edge finders will work in better different conditions. Different methods of edge detection were compared comparatively to determine which method was most suitable for obtaining edges without any noise conditions. Here, the three types of edges have horizontal, vertical and diagonal edges. In this paper, we review the different editing methods and compare different identification methods, advantages, and disadvantages. Implementation is done using MATLAB. A sudden change of discontinuity is evident in the image.

Graphene-based flat microstrip patch antenna with circular polarization controllability

In this paper, an antenna designed based on chemical potential by changing fermi energy for DC orientation. In addition, the effect of gaps in the antenna have been investigated to provide circular polarization. It was concluded that the number of gaps had no effect on the polarization of RHCP and LHCP. It also examines how to add extra two sections at the edges of the proposed antenna to create polarization. According to this study, adding two diagonal edges in one direction in the patch antenna does not create circular polarization. But these additional sections, with the phase difference ± 90 with each other, construct two components of the orthogonal field to create a circular polarization. The theoretical relationship between chemical potential and axial ratio has also been investigated, which has not been mentioned in recent articles. Thus, in this paper, only the possibility of achieving an antenna with optimal compatibility in the frequency range of 1.58–1.63 THz at the resonance frequency has been investigated. Also, ideal conditions in RHCP and LHCP modes, antenna axial ratio of less than 3 dB in the frequency range of 1.58–1.63 THz in the resonant frequency is obtained. Finally, efficiency is 58% at the frequency of 1.6 THz.

Analysis of an optimal policy in dynamic bipartite matching models

A dynamic bipartite matching model is given by a bipartite matching graph which determines the possible matchings between the various types of supply and demand items. Both supply and demand items arrive to the system according to a stochastic process. Matched pairs leave the system and the others wait in the queues, which induces a holding cost. We model this problem as a Markov Decision Process and study the discounted cost and the average cost problem. We assume that the cost function is linear on the queue sizes. We show that for the N-shaped matching graph, an optimal matching control prioritizes the matchings in the pendant edges and is of threshold type for the diagonal edge. In addition, for the average cost problem, we compute the optimal threshold value. We then show how the obtained results can be used to characterize the structure of an optimal matching control for a quasi-complete graph with an arbitrary number of nodes. For arbitrary bipartite graphs, we show that, when the cost of the pendant edges is larger than in the neighbors, an optimal matching policy prioritizes the items in the pendant edges. We also study the W-shaped matching graph and, when the cost of the pendant edges is larger than the cost of the middle edge, we conjecture that an optimal matching policy is also of threshold type with priority to the pendant edges; however, when the cost of the middle edge is larger, we present simulations that show that it is not optimal to prioritize items in the pendant edges.

Constrained percolation in two dimensions

We prove absence of infinite clusters and contours in a class of critical constrained percolation models on the square lattice. The percolation configuration is assumed to satisfy certain hard local constraints, but only weak symmetry and ergodicity conditions are imposed on its law. The proofs use new combinatorial techniques exploiting planar duality. Applications include absence of infinite clusters of diagonal edges for critical dimer models on the square-octagon lattice, as well as absence of infinite contours and infinite clusters for critical XOR Ising models on the square grid. We also prove that there exists at most one infinite contour for high-temperature XOR Ising models, and no infinite contour for low-temperature XOR Ising model.

Contextual experience modifies functional connectome indices of topological strength and efficiency

Stimuli presented at short temporal delays before functional magnetic resonance imaging (fMRI) can have a robust impact on the organization of synchronous activity in resting state networks. This presents an opportunity to investigate how sensory, affective and cognitive stimuli alter functional connectivity in rodent models. In the present study we assessed the effect on functional connectivity of a familiar contextual stimulus presented 10 min prior to sedation for imaging. A subset of animals were co-presented with an unfamiliar social stimulus in the same environment to further investigate the effect of familiarity on network topology. Rats were imaged at 11.1 T and graph theory analysis was applied to matrices generated from seed-based functional connectivity data sets with 144 brain regions (nodes) and 10,152 pairwise correlations (after excluding 144 diagonal edges). Our results show substantial changes in network topology in response to the familiar (context). Presentation of the familiar context, both in the absence and presence of the social stimulus, strongly reduced network strength, global efficiency, and altered the location of the highest eigenvector centrality nodes from cortex to the hypothalamus. We did not observe changes in modular organization, nodal cartographic assignments, assortative mixing, rich club organization, and network resilience. We propose that experiential factors, perhaps involving associative or episodic memory, can exert a dramatic effect on functional network strength and efficiency when presented at a short temporal delay before imaging.

Adaptive PVD and LSB based high capacity data hiding scheme

In this paper, a new data hiding scheme using a mixture of adaptive pixel value differencing (PVD) and least significant bit substitution (LSB) is proposed for increasing the data hiding capacity. The scheme is a generalization of Jung (J Real-Time Image Proc. 14:127–36, 2018) which is the first work to use PVD and LSB methods simultaneously on a single image. However, the PVD used by Jung (J Real-Time Image Proc. 14:127–36, 2018) is not an adaptive method means it does not consider the vertical and diagonal edges of the image for hiding the secret data. In the proposed scheme, the vertical and diagonal edges in addition to horizontal edges are used for hiding the secret data so that a large amount of secret data is hidden without any perceived change. Experimental results show that the performance of the proposed scheme is superior to the existing schemes in terms of both data hiding capacity and image quality. Moreover, it is very simple as it does not require much computation for embedding the secret data.

An Efficient Rectilinear and Octilinear Steiner Minimal Tree Algorithm for Multidimensional Environments

The rectilinear/octilinear Steiner problem is the problem of connecting a set of terminals $Z$ using orthogonal and diagonal edges with minimum length. This problem has many applications, such as the EDA, VLSI circuit design, fault-tolerant routing in mesh-based broadcast, and Printed Circuit Board (PCB). This paper proposes an obstacle-avoiding 4/8/10/26-directional heuristic algorithm for this problem based on the Areibi’s concept, Higher Geometry Maze Routing, and Sollin’s minimal spanning tree algorithm. The major contributions of this paper are (1) our work is the first report for the octilinear SMTs in the multidimensional environments, (2) we provide an optimal point-to-point routing without any refinement, and (3) the proposed algorithm has higher adaptability to deal with any irregular environment, and can be extended to the $\lambda $ -geometry without any extra work, where $\lambda =2$ , 4, 8 and $\infty $ corresponding to rectilinear, 45°, 22.5° and Euclidean geometries respectively.

Edge Detection Algorithm for $Musca-Domestica$ Inspired Vision System

Compound vision sensors, mimicking the compound eye of the common housefly, possess motion hyperacuity, resulting in better motion detection and tracking capabilities as compared to traditional camera systems. Therefore, these sensors have applications requiring near instantaneous obstacle avoidance in its field-of-view. However, the obstacle detection algorithms used by current compound vision systems are insufficient to enable these capabilities due to their ability to only detect horizontal or vertical edges. In this paper, we propose an improved edge detection and location algorithm for fly inspired vision sensors which can correctly classify horizontal, vertical, forward diagonal, and backward diagonal edges.

Sensitivity Analysis and Optimization of Delta Wing Design Parameters using CFD-Based Response Surface Method

This paper explores the effect of design variables on the objective functions of clipped delta wing with a modified double-wedge airfoil section based on parametric analysis and CFD-based optimization using response surface method. This type of wing is used in air-launch-to-orbit vehicles. The thickness, wing-span, tip chord, leading edge radius, front diagonal edge and rear diagonal edge lengths are defined as design variables and aerodynamic efficiency, drag and lift coefficients as objective functions. The analysis was performed at Mach 0.85 and 1.2 and for several angle of attack (AOA). The optimization process is performed by numerical stimulation of the flow around the wing at different Mach numbers and AOAs for the deformed geometry at each step including 368 cases. Minimizing the drag force and maximizing both lift coefficient and aerodynamic efficiency have been selected as optimization goal. The evolutionary optimization technique of NSGA-II (Non-dominated Sorted Genetic Algorithm-II) in combination with the RSM has been used, which leads to distinct but very close candidates for each flight conditions. Defining the critical design point, it can be deduced the aerodynamic efficiency will be increased by 50% compared with base wing model. Finally, it is shown that the best point for optimizing the air-launched vehicle equipped with delta wing in the ascent trajectory, is the maximum angle of attack that occurs at Mach 1.2.

Quantum Image Edge Extraction Based on Improved Sobel Operator

Edge extraction is a basic task in image processing. This paper proposes a quantum image edge extraction algorithm based on improved sobel operator for the generalized quantum image representation (GQIR) to solve the real-time problem. The quantum image model of GQIR can store arbitrary quantum images with a size of H × W. Our scheme can calculate the gradients of image intensity of all the pixels simultaneously. Then, the concrete circuits of quantum image edge extraction algorithm are implemented by using a series of quantum operators which have been designed. Compared with existing quantum edge extraction algorithms, our scheme can achieve more accurate edge extraction, especially for diagonal edges. Finally, the complexity of the quantum circuits were been analyzed based on the basic quantum gates and give the simulation experiment results on classical computer.

A Compact Circularly Polarized MIMO Dielectric Resonator Antenna Over Electromagnetic Band-Gap Surface for 5G Applications

We present a wideband circularly polarized (CP) multiple-input multiple-output (MIMO) dielectric resonator antenna (DRA) with enhanced diversity. In the DRA element, two diagonal edges of the DR were truncated at 45° to obtain a wider axial ratio larger than 0.65 GHz. The DRA element was excited by a cross-ring slot with specific slot-arm ratio through microstrip-line (MSTL) implemented at the backside of the FR4 substrate to generate CP fields. Small triangular stands at the edge of the DR were employed to hold it in place to avoid any degradation from the uncontrollable bonding agent used for attaching DR onto the FR4 substrate. The DRA achieved an impedance bandwidth better than 0.8 GHz with an antenna gain of 4.83 dBi. Using the DRA with the MSTL feed, two-element CP-DRA array was implemented with electromagnetic band-gap (EBG) structure etched onto the ground plane of the MSTL. The proposed architecture achieves isolation better than 26 dB over the desired frequency band without any performance degradation while maintaining its compact size in the array. Various diversity analysis was carried out on the implemented circularly polarized MIMO DRA. The measured results demonstrated that the proposed singly fed DRA with EBG on the ground plate is suitable for implementing wideband circular polarized MIMO antennas in a compact size.

Sparsely encoded distinctive visual features for object recognition

An image feature descriptor named “sparsely encoded distinctive visual features (SEDVF)” is proposed for object recognition. SEDVF is built with the integration of local and global visual features. Visual information on edge orientation, magnitude, color, and pixel intensity is sparsely encoded by a bit plane slicing technique. Distinctive features are obtained using winner-takes-all principle. Edge gradient multiorientation detector method (EGMOD) is proposed to obtain the gradient orientations. EGMOD extracts four-directional (horizontal, vertical, and both diagonal) edge information with the proposed multioriented Scharr operator in YIQ color space. Magnitude features are extracted by incorporating chromatic information along horizontal and vertical directions in the RGB color space. SEDVF can be used as a color feature descriptor that has good discriminative power of visual features. The proposed descriptor is extensively tested for performance evaluation using K-nearest neighbor classifier on three standard datasets, including Columbia object image library, Amsterdam library of object images, and PVOC 2007, respectively. Experimental results reveal outperformance of SEDVF as compared to the state-of-the-art object recognition methods.