Fitting Technique Research Articles

Crustal deformation and thickness variation from Zagros to Alborz in Iran: New insights from H-κ-c method

The collision between Arabia and Eurasia has had a significant impact on the Iranian plateau, making it a prime location for investigating crustal deformation. The Neotethys Ocean closure and subsequent collision during the Cenozoic era led to extensive deformation in the northern part of the Iranian plateau, in particular development of the Alborz mountain range. In this study, we aim to determine crustal thickness and azimuthal anisotropic parameters in order to gain insights into the patterns of crustal deformation in the region. Using the H-κ-c method (Li et al., 2019), we conducted an investigation into the impact of seismic anisotropy on the estimation of the crustal thickness (H) and Vp/Vs ratio (κ) at 26 seismic stations. Our analysis unveiled significant variations in Moho depth across the studied region. The collisional zones featured a deeper Moho depth when compared to Central Iran. In particular, the Central Iran region demonstrated a relatively thinner crust, characterized by an average Moho depth of 43 km, while the Sanandaj-Sirjan zone showcased a thicker crust, boasting a Moho depth of 59 km. The Alborz mountain ranges demonstrated an average Moho depth of 50 km. Notably, the Central Iran stations exhibited elevated κ values, potentially attributable to fluid contents and thick sedimentary cover. To characterize the anisotropic properties of the crust, we employed curve fitting techniques on the sinusoidal moveouts of the Ps-converted phases originating from the Moho and major intracrustal interfaces. Our analysis identified intracrustal discontinuities at seven stations, indicating the presence of two distinct anisotropic crustal layers. These anisotropic layers displayed maximum delay times of up to 0.6 s. Furthermore, our examination of crustal and mantle anisotropy patterns revealed that the deformation observed in the region cannot be solely attributed to a vertically coherent regime.

Effect of injecting inert gas at different spontaneous combustion stages on active groups in coal

Inert gas injection into the mine gob where coal spontaneous combustion occurs can effectively avoid the loss of coal resources, reduce greenhouse gas emissions and realize the green and sustainable mining of coal resources. In this paper, a continuous process of abruptly changing coal from an oxygenated atmosphere to an inert atmosphere in one experiment was realized by a gas atmosphere conversion device, and the effect of inert gas injection on reactive groups in coal at different stages of oxidation was studied based on electron spin resonance technique and spectral peak splitting fitting technique. The experimental results show that the g factor of lignite decreases slowly and then increases with the rising temperature under dry air, and the g factor turning point temperature is 80 °C. The concentration of radicals in lignite increases continuously with rising temperature. The injection of N2 and CO2 at 130 °C has the most significant inhibitory effect on the g factor of coal, with 41.61 % and 65.11 %, respectively. After injecting N2 and CO2 at different stages, the radical concentration of coal suddenly decreases and then continues to increase with the extension of constant temperature time, and the injection of N2 and CO2 at 130 °C has the most significant inhibitory effect on the radical concentration of coal, 28.35 % and 35.44 %, respectively. The radicals in coal can be classified into oxygen-containing radicals, aliphatic radicals, simple aromatic radicals, and π- or σ-type oxygen-containing radicals by the spectroscopic peak splitting technique. The injection of inert gas produces a significant inhibition effect on oxygen-containing radicals in coal. And finally, the inhibition pathway of inert gas on oxygen-containing radicals in coal was revealed from the perspective of radical reaction.

Enhancing second-order blind identification for underdetermined operational modal analysis through bandlimited source separation

Blind source separation (BSS) has been demonstrated to be a promising method for operational modal analysis (OMA). However, the conventional BSS-based modal identification methods can only handle the determined or overdetermined identification where the number of sensors must equal or exceed that of active modes, limiting their wider application. Furthermore, the existing methods for underdetermined BSS require sparsity assumption of sources, optimization of model parameters, or structural prior information, undermining the non-parametric and “blind” properties of BSS. This paper proposes a novel method for underdetermined OMA. Firstly, the bandlimited source separation using sinc-dictionaries is performed to efficiently transform the underdetermined problem into several determined or overdetermined ones. An improved second-order blind identification (SOBI) involving Hilbert transform and random time-lagged covariances is then applied for each bandlimited signal to recover modal responses and mode shapes. To attenuate noise, an adaptive singular spectrum analysis (SSA) can be optionally applied to the recovered modal responses for the highly noisy systems. Finally, the natural frequencies and damping ratios are estimated by the single-degree-of-freedom (SDOF) fitting technique. Several numerical examples, an experimental frame case, and a field test of a pedestrian bridge are studied to verify the effectiveness of the proposed strategy.

A Competitive Segmentation of the Human Brain using Artificial Neural Network Approach Towards MRI

The diagnosis of brain abnormalities, prognosis monitoring, and treatment evaluation all rely heavily on the magnetic resonance scan of brain tissue segmentation. Although numerous automated or semi-automatic methods have been proposed in the literature to reduce the need for human intervention, the degree of accuracy is frequently still significantly lower than that of manual segmentation. We give a clever technique for fragmenting the cerebrum utilizing a managed counterfeit brain organization system called artificial neural network (ANN) and volumetric shape models. In the beginning, in addition to the usual spatial-based and intensity-based image features, a level-set oriented brain boundary fitting technique is used to accomplish this. This is controlled by the picture intensity. The ANN is then informed of the number of important structures. Additionally, rather than directly applying standard guidelines to local appearances, this ANN learns local adaptive feature classification conditions. The outcomes demonstrate that the proposed strategy achieves competitive results in a relatively shorter time spent training.

Mortality Index Simulation for Forecasting Malaysian Mortality Rates

Mortality studies are very important in demography and actuarial areas because they assist policymakers and life insurers in managing longevity and mortality risks. In recent decades, many extrapolative mortality models have been developed following the Lee-Carter model. Despite the widely used Lee-Carter model for projecting mortality rates, the literature that has a thorough explanation of it is limited. In this study, we aim to provide a comprehensive explanation of the model with a focus on its fitting and simulation forecasting techniques. We fitted the mortality rates of the Malaysian population for the years 1991 to 2012 using the Lee-Carter model. We then projected the mortality rates for the years 2013 to 2018 using an autoregressive integrated moving average (ARIMA) (0,1,0) model by using a simulation of the mortality index. Findings showed that the Lee-Carter model performs well for this dataset based on the computed standard accuracy measures. The estimated age parameters exhibited a high mortality rate in the age group of 0-4 years, while the estimated time-varying parameter indicated a decreasing trend. This study presents a thorough interpretation of the Lee-Carter model and a detailed simulation of the ARIMA (0,1,0) model and hence provides a comprehensive reference for beginners in mortality studies.

Advancements in Polymer Friction and Wear: A Scratch-Modeling Approach

Due to its many applications, including assessing strength, fracture toughness, and so on, the scratch method has attracted much attention in the research community. Finding the tribological characteristics of polymers, such as friction and wear, proved difficult for scratch approaches. This study tested a constant loading scratch method with a Rockwell indenter on the polymeric surface to develop an accessible wear and friction calculation model. Scratch load, speed, and passes, three primary factors, are considered to observe the polymers' response, particularly in terms of width, penetration depth, residual depth, and percentage of recovery. Considering all these scratch parameters, the experiments were conducted on five polymers: polytetrafluoroethylene (PTFE), polyether ether ketone (PEEK), polypropylene (PP), high-density polyethylene (HDPE), and polymethylmethacrylate (PMMA). The scratch characteristics are considered to calculate the friction coefficient and wear throughout the scratching process. Increased groove width, penetration depth, and residual depth and a decrease in recovery percentage are the effects of the number of scratch passes. The strain hardening caused by the multiple movements of the indenter on the same grooves causes a behavior change. With an increase in the scratch pass, the coefficient of friction decreases and stabilizes, and the volumetric wear increases, suggesting that more scratch passes will cause more material loss. This study derived two distinct models by applying the least-square curve fitting technique to evaluate friction and material wear characteristics. This model demonstrates a high degree of compatibility with the specific characteristics of polymeric materials and exhibits a significantly low margin of error.

Interfacial reactivity in the Co/CuO samples as investigated by x-ray photoelectron spectroscopy

The interfacial reactivity at the Co/CuO interfaces has been investigated in situ by the technique of x-ray photoelectron spectroscopy. Thin films of cobalt were evaporated on the CuO substrates by the technique of e-beam. The depositions were undertaken by maintaining the substrates at ambient temperature. Significant differences have been observed in the Cu 2p core level spectra recorded for these samples and that for pure CuO. The Co 2p core level spectrum also shows differences upon comparison with the spectrum for elemental cobalt. These differences arise from chemical interaction occurring at the Co/CuO interface. The curve fitting technique has been utilized to estimate the relative percentages of the constituents at the interface. The interface width has been determined from the relative percentage of the unoxidized cobalt present in the overlayer. The dependence of the interface width has also been explored as a function of annealing temperature. The interface width is much less for the room temperature deposited sample as compared to that for annealed samples. The spectral data also indicate increase in the diffusion of copper oxide through the cobalt overlayer with increasing temperature.

CHIMERA Occultation Constraints on the Abundance of Kilometer-scale Kuiper Belt Objects

Occultations provide indirect sensitivity to the number density of small Kuiper Belt objects (KBOs) too faint to directly detect telescopically. We present results from the Caltech HI-speed Multicolor camERA (CHIMERA) survey with the Palomar Hale Telescope, which monitored stars over the central of the M22 globular cluster along the ecliptic plane for serendipitous occultations by kilometer-scale KBOs over 63 hr across 24 nights at a 33 Hz frame rate simultaneously in and . We adapted dense-field photometry and occultation template fitting techniques to this data set, finding a 95% confidence upper limit on the occultation rate, corresponding to an ecliptic sky density of ≲107 deg−2 of >1 km diameter classical KBOs. We discuss a few of the occultation-like light curve signatures at the edge of the sensitivity limit responsible for setting the upper bounds, and their likely nonviability as true occultations.

OFF-LOADING PRESSURE RELIEF WITH FOAM CUT OUT CUSHIONS: EXPERIENCES FROM RANCHO LOS AMIGOS NATIONAL REHABILITATION CENTER.

This paper explores the efficacy of the cushion fitting technique using foam cut out cushions for off-loading bony prominences in the sitting position, with a particular focus on reducing the high risk of developing pressure injuries among aging wheelchair users. This technique, historically employed at Rancho Los Amigos National Rehabilitation Center, has shown promising results in reducing pressure injuries for patients with spinal cord injuries. However, its widespread adoption remains limited. This manuscript aims to raise awareness about foam cut out cushions, its historical context, and its contemporary relevance by presenting customized solutions for individual patients with specific deformities. Key clinical points are highlighted, emphasizing the importance of skilled clinicians in the fitting process and the need to consider foam cut out cushions alongside other preventive measures. Case examples illustrate successful outcomes, demonstrating improved pelvic stability, posture, and off-loading of bony prominences. By promoting foam cut out cushions as a valuable cushioning option, this manuscript equips clinicians with knowledge to utilize this technique effectively.

Hydrothermal synthesis of cerium-doped Zn2SiO4 phosphor for futuristic lighting applications

In this study, Zn2SiO4:Ce3+ phosphor with varying weight percentages of cerium (Ce) was synthesized by using the hydrothermal process. The effect of Ce ion incorporation on the nanostructures, morphology, and optical characteristics was investigated by X-ray Powder Diffraction (PXRD), Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray spectroscopy (EDX), Diffuse Reflectance Spectroscopy (DRS) using UV–Vis spectra, Photoluminescence (PL) spectroscopy, Commission Internationale de I'Elaairage (CIE)-1931 RGB color space diagrams and decay lifetime. According to PXRD measurements, Ce3+ ions were incorporated into the host material of Zn2SiO4, considerably altering their crystallinity. Due to strong crystallization, willemite crystal dispersion can be seen in FESEM images as rhombohedral-shaped crystals that successfully form closely packed grains, when the concentration of Ce3+ doping increased from 0 to 4 wt %, there was a noticeable reduction in the optical energy bandgap of the phosphor, which decreased from 5.01 to 3.22 eV. Photoluminescence spectra exhibited enhanced luminescent peak intensity at 591 nm emission, due to transitions of Ce3+ ions excited at 395 nm. Additionally, the luminescence intensity and decay lifetime of the Ce3+ ions in the Zn2SiO4 samples were determined using the tri-exponential fitting technique, and the average lifetime is 24.1 ns. This work provides valuable insight into the effect of doping element Ce3+ with various concentrations on the properties of luminescent Zn2SiO4, paving the way for its potential applications in advanced lighting technologies.

Approximate Solution of a Class of Highly Oscillatory Integral Equations Using an Exponential Fitting Collocation Method

This paper deals with the numerical solution of a class of highly oscillatory Volterra integral equations by collocation methods based on the exponential fitting technique. By reviewing the oscillatory structures of solutions of these problems, we construct an exponential fitting collocation method which is best tuned to capture the qualitative behaviour of the solution of these equations. We also investigate the convergence properties of the proposed collocation solution based on the interpolation remainder. Some numerical examples are provided which illustrate the efficiency and accuracy of the proposed method and confirm its superiority over the polynomial collocation methods.

Preliminary Study of Photometric Redshifts Based on the Wide Field Survey Telescope

The Wide Field Survey Telescope (WFST) is a dedicated time-domain multi-band (u, g, r, i, and z) photometric survey facility under construction. In this paper, we present a preliminary study that assesses the quality of photometric redshifts based on WFST by utilizing mock observations derived with the galaxy catalog in the COSMOS/UltraVISTA field. We apply the template fitting technique to estimate photometric redshifts by using the ZEBRA photometric-redshift code and adopting a modified set of adaptive templates. We evaluate the bias (median relative offset between the output photometric redshifts and input redshifts), normalized median absolute deviation (σ NMAD) and outlier fraction (f outlier) of photometric redshifts in two typical WFST observational cases, the single 30 s exposure observations (hereafter shallow mode) and co-added 50 minutes exposure observations (hereafter deep mode). We find bias ≲0.006, σ NMAD ≲ 0.03, and f outlier ≲ 5% in the shallow mode and bias ≈0.005, σ NMAD ≈ 0.06, and f outlier ≈ 17%–27% in the deep mode, respectively, under various lunar phases. Combining the WFST mock observational data with that from the upcoming CSST and Euclid surveys, we demonstrate that the z phot results can be significantly improved, with f outlier ≈ 1% and σ NMAD ≈ 0.02.

An improved physics-free genetic impedance fitting technique for precise high-frequency modeling of two-terminal electrical systems

There is an increasing industrial demand of using impedance fitting techniques to enable an equivalent circuit to approximate the electrical behavior of an electrical system. However, due to the high dependence on the prior physical information of the electrical system, previous impedance fitting techniques have long suffered from unacceptable implementation complexity and unsatisfactory fitting precision. To realize easy, cheap, and precise impedance fitting, a Physics-free genetic impedance fitting technique (PFGIFT) is proposed in this paper. Firstly, PFGIFT utilizes a five-component RLC-parallel (FCRLCP) equivalent circuit, which gets rid of expensive physics-based equivalent circuit modeling, to approximate the impedance of a two-terminal electrical system. Then, a novel bounded gaussian mixture model based genetic algorithm (BGMMBGA) is proposed to fully leverage the fitting capability of the FCRLCP equivalent circuit by embedding parameter tuning expertise into the evolutionary process. Under the combined effects of FCRLCP equivalent circuit and BGMMBGA, PFGIFT achieves precise impedance fitting performance without the use of expensive knowledge about physical information. The effectiveness of PFGIFT is verified separately on a human-designed impedance fitting task and an industrial application of fitting the common-mode impedance of a motor drive system.

Entropy analysis of nickel(II) porphyrins network via curve fitting techniques

Nickel(II) porphyrins typically adopt a square planar coordination geometry, with the nickel atom located at the center of the porphyrin ring and the coordinating atoms arranged in a square plane. The additional atoms or groups coordinated to the nickel atom in nickel(II) porphyrins are called ligands. Porphyrins have been investigated as potential agents for imaging and treating cancer due to their ability to selectively bind to tumor cells and be used as sensors for a variety of analytes. Nickel(II) porphyrins are relatively stable compounds, with high thermal and chemical stability. They can be stored in a solid state or in solution without significant degradation. In this study, we compute several connectivity indices, such as general Randi’c, hyper Zagreb, and redefined Zagreb indices, based on the degrees of vertices of the chemical graph of nickel porphyrins. Then, we compute the entropy and heat of formation NiP production, among other physical parameters. Using MATLAB, we fit curves between various indices and the thermodynamic properties parameters, notably the heat of formation and entropy, using various linearity- and non-linearity-based approaches. The method’s effectiveness is evaluated using R^2, the sum of squared errors, and root mean square error. We also provide visual representations of these indexes. These mathematical frameworks might offer a mechanism to investigate the thermodynamical characteristics of NiP’s chemical structure under various circumstances, which will help us understand the connection between system dimensions and these metrics.

A Probabilistic Adaptive Cerebral Cortex Segmentation Algorithm for Magnetic Resonance Human Head Scan Images

The total efficiency of Magnetic Resonance Imaging (MRI) results in the need for human involvement in order to appropriately detect information contained in the image. Currently, there has been a surge in interest in automated algorithms that can more precisely divide medical image structures into substructures than prior attempts. Instant segregation of cerebral cortex width from MRI scanned images is difficult due to noise, Intensity Non-Uniformity (INU), Partial Volume Effects (PVE), MRI's low resolution, and the very complicated architecture of the cortical folds. In this paper, a Probabilistic Adaptive Cerebral Cortex Segmentation (PACCS) approach is proposed for segmenting brain areas of T1 weighted MRI of human head images. Skull Stripping (SS), Brain Hemisphere Segmentation (BHS) and CCS are the three primary processes in the suggested technique. In step 1, Non-Brain Cells (NBC) is eliminated by a Contour-Based Two-Stage Brain Extraction Method (CTS-BEM). Step 2 details a basic BHS technique for Curve Fitting (CF) detection in MRI human head images. The left and right hemispheres are divided using the discovered Mid-Sagittal Plane (MSP). At last, to enhance a probabilistic CCS structure with adjustments such as prior facts change to remove segmentation bias; the creation of express direct extent training; and a segmentation version based on a regionally various Gaussian Mixture Model- Hidden Markov Random Field – Expectation Maximization (GMM-HMRF-EM). The underlying partial extent categorization and its interplay with found image intensities are represented as a spatially correlated HMRF within the GMM-HMRF-EM method. The proposed GMM-HMRF method estimates HMRF parameters using the EM technique. Finally, the outcomes of segmentation are evaluated in terms of precision, recall, specificity, Jaccard Similarity (JS), and Dice Similarity (DS). The proposed method works better and more consistently than the present locally Varying MRF (LV-MRF), according to the experimental findings obtained by using the suggested GMM-HMRF-EM methodology to 18 individuals' brain images.

New Mathematical Technique for Step Rate Test Analysis Aids Determination of Fracture Pressure and Overcomes the Uncertainty of Conventional Analysis.

Experience in the oil industry has shown that it is challenging to sustain successful long-term matrix injection, as injection water quality cannot be maintained rigorously due to facility hiccups and membrane clogging. Most oil field operators have resolved this problem of injectivity decline by increasing the surface injection pressure to part the formation and inject just above the fracture gradient with strict offtake management for zonal conformance. This is not an easy task as injection much above fracture opening pressure can lead to water fingering and poor sweep that results in uneconomical waterflood recovery. The operators, thus, strive to inject at a pressure just above the fracture opening pressure so that the fracture opens near the wellbore but does not extend and then maintain the pressure just above the fracture closing pressure. Therefore, determination of the fracture opening pressure and fracture closing pressure has remained critical data for the success of waterflood projects. The most reliable industry approach to estimating fracture opening and fracture closing pressures comes from the step rate test (SRT). This traditional approach of Cartesian analysis of pressure-rate plot fits straight lines through the data in a plot of injection pressure against injection rate and then estimates the fracture pressure from the intersection of these lines having different slopes. The data received often do not exhibit one clear change in slope, thus resulting in multiple possible solutions, making it difficult for the operator to use the data for high CAPEX facilities design. Most past studies indicate the subjectivity of this Cartesian slope fitting technique. Alternative solutions through multirate superposition analysis found limited application in the analysis of SRT data due to considerable sensitivity to the value of initial pressure used for superposition and lack of stability of rate and pressure data. In this article, a new technique of SRT analysis is presented, which provides a unique solution for fracture opening and fracture closing pressures. It helps to overcome the limitations of the traditional technique of arbitrary fitting of straight lines. It uses the mathematical understanding of cumulative derivatives to recognize that the matrix opens when the cumulative growth of the rate of injectivity shows a change. It estimates the derivative of the injection rate with respect to injection pressure at each step. Then, it estimates the fracture pressure from the plot of the cumulative of this derivative against pressure at each step. It helps to overcome the challenge SRT solutions posed by the nonlinear trend of pressure data at each injection step both before fracture and after fracture is initiated. It also overcomes the limitations of the multirate superposition technique, as it is not sensitive to the value of initial pressure used for superposition.

Automatic Generation of Auxiliary Basis Sets in Spherical Representation Using the Cholesky Decomposition.

Density fitting techniques that use automatically generated auxiliary basis sets generally rely on the formation of basis function products. Recently, Lehtola [ J. Chem. Theory Comput. 2021, 17, 6886-6900] presented a procedure making use of a purely spherical representation by adding auxiliary basis functions coupled to the required angular momentum quantum numbers for the product of spherical harmonics and then removing linear dependencies by means of a Cholesky decomposition. In this work, we extend this idea by making use of the explicit equations for the product of two spherical harmonics in the angular part of the basis function product. Some of the resulting terms are not directly accessible when popular standard integral libraries are used, which could prevent the widespread use of the exact product form. For these terms, we introduce four approximations of increasing sophistication that require integrals involving only standard Gaussian-type orbitals and thus can be computed with standard libraries. We assess the accuracy of the different schemes in the context of the aCD for the reconstruction of the electron repulsion integral matrix and absolute and relative single point energies and in the framework of optimally tuned range-separated hybrid functionals.

DATA-DRIVEN IDENTIFICATION OF HYPERELASTIC MODELS BY MEASURING THE STRAIN ENERGY DENSITY FIELD

ABSTRACT A novel method for accurately identifying the large strain elastic response of elastomeric materials is presented. The method combines the data-driven identification (DDI) algorithm with a unique heterogeneous experiment, deviating from the conventional approach of conducting multiple simple experiments. The primary objective of the method is to decouple the experimental process from the fitting technique, relying instead on a single comprehensive experiment to generate an extensive collection of stress and strain energy fields. This collection is then used in conjunction with a standard fitting technique to determine the parameters of hyperelastic models. Notably, the approach places significant emphasis on the strain energy density field as a critical factor in model identification, as it encompasses the full material response within a single scalar quantity. To demonstrate the effectiveness of the proposed approach, a proof of concept is provided using synthetic data. The results highlight the efficiency of the method and emphasize the importance of incorporating the strain energy density field for precise model identification, surpassing the reliance on stress data alone. In addition, several graphical tools are introduced to evaluate and analyze the quality of both the generated mechanical fields and the identification results. The proposed approach offers a more comprehensive representation of the material behavior and enhances the reliability and prediction capabilities of hyperelastic material models. It holds significant potential for advancing the field of solid mechanics, particularly in accurately characterizing the mechanical responses of elastomeric materials.

Comparison of Rational Krylov and Vector Fitting in Transient Simulation of Transmission Lines and Cables

This paper presents stringent comparisons between Vector Fitting (VFIT), Relaxed Vector Fitting (R-VFIT) and Rational Krylov Fitting (RKFIT) techniques in the fitting of transmission line and cable functions to rational forms while accounting for the frequency dependence of electrical parameters. The fitting procedures encapsulate new solution strategies to improve fitting performance. Various case studies are presented to assess the performance of RKFIT in terms of model order reduction, passivity violation and computing times. In addition, the use of RKFIT in obtaining the frequency dependent cable model (FDCM) is demonstrated for the first time together with a resolved case study that showed unstable behavior with the universal line model (ULM) methodology.

Impact of Source Resistance on Linearity of AlGaN/GaN HEMTs at Ka-Band

The impact of the source resistance (RS) on the linearity of AlGaN/GaN high electron mobility transistors (HEMTs) measured by the two-tone test is investigated in this study. The theoretical analysis of the third-order intermodulation (IM3) and the third-order intercept point (IP3) of the devices was performed based on the equivalent circuit approach and the polynomial curve fitting technique. The results revealed that the suppression of IM3 level and thus the improvement of IP3 were achieved for the device with a larger RS. For the experimental verifications, three types of AlGaN/GaN HEMTs were fabricated with different layout structures and air-bridge architectures corresponding to different RS values, which were then extracted by the cold-FET method. It is concluded that a device with a shorter length of middle source pad (LMS) and a side-type air-bridge architecture tends to have a larger RS value. In this study, the 4 × 50–20 device with LMS of 20 um and a side-type air-bridge architecture demonstrated the best-measured linearity performance at 30 GHz due to the largest RS.