Imperfect Matching Research Articles

Deep Search for a Scattered Light Dust Halo Around Vega with the Hubble Space Telescope

We present a provisory scattered-light detection of the Vega debris disk using deep Hubble Space Telescope (HST) coronagraphy (PID 16666). At only 7.7 pc, Vega is immensely important in debris disk studies both for its prominence and also because it allows the highest physical resolution among all debris systems relative to temperature zones around the star. We employ the STIS coronagraph’s widest wedge position and classical reference differential imaging to achieve among the lowest surface-brightness sensitivities to date ( ∼4μJyarcsec−2 ) at wide separations using 32 orbits in Cycle 29. We detect a halo extending from the inner edge of our effective inner working angle at 10.″5 out to the photon noise floor at 30″ (80–230 au). The face-on orientation of the system and the lack of a perfectly color-matched point-spread function star have posed significant challenges to the reductions, particularly regarding artifacts from the imperfect color matching. However, we find that a halo of small dust grains provides the best explanation for the observed signal. Unlike Fomalhaut (a close twin to Vega in luminosity, distance, and age), there is no clear distinction in scattered light between the parent planetesimal belt observed with the Atacama Large Millimeter/submillimeter Array and the extended dust halo. These HST observations complement JWST GTO Cycle 1 observations of the system with NIRCam and MIRI.

Estimation of the domain of attraction for continuous-time saturated positive polynomial fuzzy systems based on novel analysis and convexification strategies

In this paper, the domain of attraction (DOA) of the continuous-time positive polynomial fuzzy systems subject to input saturation is estimated by using the level set of the linear copositive Lyapunov function. To relax the estimation of DOA, the restriction on the level set is removed by embedding the expression of the level set into the stability conditions and positivity conditions. Referring to the nonconvex terms caused by above novel analysis strategy, some polynomial inequality lemmas are proposed to handle them; the nonconvex terms caused by imperfect premise matching (IPM) nonlinear membership functions are dealt with by sector nonlinear methods and advanced Chebyshev membership-function-dependent (MFD) methods. In this advanced MFD method, the state space segmentation and polynomial order selection of the Chebyshev approximation method are improved based on breakpoints of the first derivative and curvature, respectively, which is helpful to reduce the conservatism and computational burden of the result. Thus, this advanced Chebyshev MFD method not only optimizes the convexification strategy, but also can further be extended to estimate the DOA when it is used to introduce the membership functions information for convex stability and positivity conditions. Finally, a numerical example and the lipoprotein metabolism and potassium ion transfer nonlinear model are presented to validate the effectiveness and feasibility of the aforementioned analysis and convexification strategies in the expansion of DOA estimation.

Short-time self-diffusion in binary colloidal suspensions

The Brownian dynamics of a colloidal particle is consistently modified by the presence in the solvent of other particles of comparable size, whose effects on the particle diffusion coefficient cannot be attributed to a change of the effective solvent viscosity. So far, despite their impact on subjects ranging from microrheology to phoretic transport in crowded environments, a detailed experimental survey of these effects is still lacking. By exploiting the peculiar properties of fluorinated colloidal particle, we have performed an extensive dynamic light scattering (DLS) investigation of short-time self-diffusion in binary colloidal mixtures, focusing on systems where one of the two species (the “tracer” particles) is very diluted compared to the other one (the “host” particles). From the dependence on the host concentration of the DLS correlation function, we have obtained the first-order correction hs1s to the tracer single-particle diffusion coefficient, varying the tracer-to-host size ratio q in the range 0.2 ≤ q ≤ 2. Our results support the functional relation of hs1s on q proposed to account for the theoretical and numerical results for hard-sphere mixtures. However, hs1s seems to have a weaker dependence on the size ratio than theoretically predicted, possibly because of an imperfect matching of the suspensions we used for an ideal hard-sphere mixture. This may be due to the presence of a stabilizing surfactant layer on the particle surface that, although very thin, has significant effects on hydrodynamic lubrication forces.

Integrated Fault-Tolerant Control Design With Sampled-Output Measurements for Interval Type-2 Takagi-Sugeno Fuzzy Systems.

This article is concerned with the integrated design of fault estimation (FE) and fault-tolerant control (FTC) for uncertain nonlinear systems suffering from actuator faults and external disturbance. The uncertain nonlinear systems are characterized as the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, and IT2 membership functions are employed to effectively handle uncertainties. A fuzzy observer, utilizing only sampled-output measurements, is applied to simultaneously estimate actuator faults and system states. Based on the estimation, the fault-tolerant controller is designed to ensure the system stability under a predefined H∞ performance. The sampling behavior complicates the system dynamics and makes the integrated FTC design more challenging. To confront this issue, the discontinuous Lyapunov functional technique is exploited to enhance stability results by considering the sampling characteristic, upon which FE and FTC units are co-designed in the linear matrix inequality (LMI) framework. To further relax stability criteria, the analysis process incorporates the bound information of membership functions through the membership-function-dependent (MFD) method. Additionally, the relationship of mismatched premise variables resulting from the sampling scheme is also taken into account. Moreover, considering the imperfect premise matching (IPM) framework, the proposed fault-tolerant controller provides greater flexibility in selecting the shapes of membership functions and number of fuzzy rules that can vary from the counterpart of the fuzzy system. Finally, the efficacy of the proposed FTC technique is validated through a detailed numerical example.

Imperfect refractive index matching in scanning laser optical tomography and a method for digital correction.

Scanning laser optical tomography (SLOT) is a volumetric multi-modal imaging technique that is comparable to optical projection tomography and computer tomography. Image quality is crucially dependent on matching the refractive indexes (RIs) of the sample and surrounding medium, but RI matching often requires some effort and is never perfect. Reducing the burden of RI matching between the immersion medium and sample in biomedical imaging is a challenging and interesting task. We aim at implementing a post processing strategy for correcting SLOT measurements that have errors caused by RI mismatch. To better understand the problems with poorly matched Ris, simulated SLOT measurements with imperfect RI matching of the sample and medium are performed and presented here. A method to correct distorted measurements was developed and is presented and evaluated. This method is then applied to a sample containing fluorescent polystyrene beads and a sample made of olydimethylsiloxane with embedded fluorescent nanoparticles. From the simulations, it is evident that measurements with an RI mismatch larger than 0.02 and no correction yield considerably worse results compared to perfectly matched measurements. RI mismatches larger than 0.05 make it almost impossible to resolve finer details and structures. By contrast, the simulations imply that a measurement with an RI mismatch of up to 0.1 can still yield reasonable results if the presented correction method is applied. The experiments validate the simulated results for an RI mismatch of about 0.09. The method significantly improves the SLOT image quality for samples with imperfectly matched Ris. Although the absolutely best imaging quality will be achieved with perfect RI matching, these results pave the way for imaging in SLOT with RI mismatches while maintaining high image quality.

Stability analysis of interval type-2 sampled-data polynomial fuzzy-model-based control system with a switching control scheme

The stability of an interval type-2 (IT2) sampled-data (SD) polynomial fuzzy-model-based control system with a switching control scheme is studied in this paper. The uncertain nonlinear plant is depicted via an IT2 polynomial fuzzy model. To realize control, a switching IT2SD polynomial fuzzy controller is generated. This paper adopts a switching control scheme with a variable sampling period. The modeling domain consists of several sub-domains, and each sub-domain corresponds to a local IT2SD polynomial fuzzy controller. These local IT2SD polynomial fuzzy controllers form the switching IT2SD polynomial fuzzy controller. To aid in the stability analysis, this paper adopts a looped-functional-based technique. The imperfect premise matching concept is brought in to solve the mismatch dilemma caused by the SD control strategy and uncertainties. For decreasing the conservativeness, this paper takes into account the state information as well as the information of IT2 membership functions. The stability analysis is performed for each sub-domain, providing the potential for further relaxation. As polynomials exist in the stability conditions, this paper employs the sum-of-squares method for the stability investigation. The simulation outcomes confirm the efficacy of the proposed method.

Imperfect premise matching finite-time filter design for continuous-time Takagi–Sugeno fuzzy systems

An input–output finite-time filtering design problem for a class of delayed Takagi–Sugeno fuzzy systems with external disturbance input is discussed in this paper. Specifically, the filter design uses the imperfect premise matching scheme that relaxes the requirement that the filter and system membership functions be the same. This method can improve the flexibility of the filter design by incorporating membership function information into the input–output finite-time stability analysis. Using the system and filter states, an augmented filtering system is obtained. The required stability criteria are then derived using the Lyapunov–Krasovskii stability theorem and a few recent inequality approaches. Following that, the desired filter gain matrices are determined. The developed filtering design method is validated through some demonstrative examples.

Adaptive Neural Sliding-Mode Control for Fuzzy Singularly Perturbed Systems: Sojourn-Probability-Based Stochastic Communication Protocol.

This article addresses an adaptive neural network (NN) sliding-mode control (SMC) strategy for fuzzy singularly perturbed systems against unrestricted deception attacks and stochastic communication protocol (SCP). Instead of relying on the traditional transition probability, a sojourn-probability-based SCP is efficiently established to characterize the stochastic nature more precisely. In response to unrestricted deception attacks, an NN-based technique is deployed to estimate and counteract their detrimental impacts on system performance. Moreover, the design of the sliding-mode controller integrates the singular perturbation parameter and fuzzy rules, addressing the challenge of imperfect premise matching. The proposed controller guarantees exponential ultimate boundedness in the mean square sense and ensures the reachability of the specified sliding surface for the closed-loop system. Finally, the efficacy of the proposed theoretical framework is validated through two illustrative examples, confirming its practical applicability and robustness.

Asynchronous Control for Interval Type-2 Fuzzy Nonhomogeneous Markov Jump Systems Against Successive DoS Attacks.

This article is concerned with the problem of asynchronous control for Interval Type-2 (IT2) fuzzy nonhomogeneous Markov jump systems against successive denial-of-service (DoS) attacks. The system and the controller are assumed to be connected through a communication channel subject to malicious attacks. The maximum number and probability distribution of successive attacks are considered. Under the imperfect premise matching, a fuzzy asynchronous controller is constructed by the hidden Markov model. By means of the introduced transmission delay, a delay closed-loop system is constructed, where the stochastic description of the delay depends on the statistical characteristic of successive attacks. Then stability criteria together are derived in the form of linear matrix inequalities by the Lyapunov functional approach, as well as the condition on the existence of the fuzzy controller. Finally, the feasibility and effectiveness of the presented control scheme are demonstrated by simulation results.

Nonepitaxial Wafer-Scale Single-Crystal 2D Materials on Insulators.

Next-generation nanodevices require 2D material synthesis on insulating substrates. However, growing high-quality 2D-layered materials, such as hexagonal boron nitride (hBN) and graphene, on insulators is challenging owing to the lack of suitable metal catalysts, imperfect lattice matching with substrates, and other factors. Therefore, developing a generally applicable approach for realizing high-quality 2D layers on insulators remains crucial, despite numerous strategies being explored. Herein, a universal strategy is introduced for the nonepitaxial synthesis of wafer-scale single-crystal 2D materials on arbitrary insulating substrates. The metal foil in a nonadhered metal-insulator substrate system is almost melted by a brief high-temperature treatment, thereby pressing the as-grown 2D layers to well attach onto the insulators. High-quality, large-area, single-crystal, monolayer hBN and graphene films are synthesized on various insulating substrates. This strategy provides new pathways for synthesizing various 2D materials on arbitrary insulators and offers a universal epitaxial platform for future single-crystal film production.

Cost-effectiveness of HerzMobil Tirol, a multidimensional post-discharge disease management program for heart failure patients Economic evaluation along a one-year observation period

Abstract Methods We conducted a cost-effectiveness analysis along a retrospective cohort study of the routine DMP in the province of Tyrol, Austria (HerzMobil Tirol, DMP-HMT) with a propensity score matched cohort of 257 individuals in the usual care (UC) and 251 in the DMP group and a one-year follow up (2016-2019). We determined the effectiveness (hospital-free life expectancy, event-free life years and life years gained, and number of avoided rehospitalizations), costs (DMP, rehospitalizations) and the incremental cost-effectiveness ratio (ICER) of DMP-HMT vs. UC. Data preparation included two steps, missing value imputation and adjustment for remaining confounding due to imperfect matching. We performed a nonparametric sensitivity analysis with bootstrap sampling (n=5,000 replications), sensitivity analyses on costs of HF-rehospitalizations after events that are highly irrelevant for the stated research question and on costs per disease-related diagnosis (DRG) score for rehospitalizations. Results The base-case analysis showed that, on average, DMP-HMT results in 42 additional hospital-free life days, 0.54 event-free days to the next cardiovascular event, 40 additional life days, and 0.12 avoided hospitalizations per person compared to UC. The average DPM costs are EUR 1,916 per person. Mean rehospitalization costs are EUR 5,551 in HMT and EUR 6,943 in UC. The ICER of DMP-HMT compared to UC is EUR 4,773 per life-year gained outside the hospital. In a sensitivity analysis, DMP-HMT was also cost saving when "high irrelevant costs" related to the DMP were replaced with average costs. The ICER decreases with increasing costs per DRG score. Conclusions Our economic evaluation along the cohort study showed that the DMP HerzMobil Tirol is cost-effective compared to UC based on the one-year time follow up horizon. The DMP was cost-saving in a sensitivity analysis correcting for "high irrelevant costs". Our findings promote widespread adoption of telemedicine assisted DMP for HF. Further research is needed on the long-term assessment of benefits and costs beyond the study period using a decision-analytic model and considering upcoming real-world evidence.

Optimization for Interval Type-2 Polynomial Fuzzy Systems: A Deep Reinforcement Learning Approach

It is known that the interval type-2 (IT2) fuzzy controllers are superior compared to their type-1 counterparts in terms of robustness, flexibility, etc. However, how to conduct the type reduction optimally with the consideration of system stability under the fuzzy-model-based (FMB) control framework is still an open problem. To address this issue, we present a new approach through the membership-function-dependent (MFD) and deep reinforcement learning (DRL) approaches. In the proposed approach, the reduction of IT2 membership functions of the fuzzy controller is completing during optimizing the control performance. Another fundamental issue is that the stability conditions must hold subject to different type-reduction methods. It is tedious and impractical to resolve the stability conditions according to different type-reduction methods, which could lead to infinite possibility. It is more practical to guarantee the holding of stability conditions during type-reduction rather than resolving the stability conditions, the MFD approach is proposed with the imperfect premise matching (IPM) concept. Thanks to the unique merit of the MFD approach, the stability conditions according to all the different embedded type-1 membership functions within the footprint of uncertainty (FOU) are guaranteed to be valid. During the control processes, the state transitions associated with properly engineered cost/reward function can be used to approximately calculate the deterministic policy gradient to optimize the acting policy and then to improve the control performance through determining the grade of IT2 membership functions of the fuzzy controller. The detailed simulation example is provided to verify the merits of the proposed approach.

Estimating complex dielectric permittivity of materials by the frequency dependences of reflection and transmission coefficient magnitudes in the microwave range

Electromagnetic waves of the microwave range are an effective tool for solving problems of non-destructive testing and diagnostics as applied to dielectric, semiconductor, and composite materials, ferrite products. An algorithm is suggested for estimating the complex permittivity of non-magnetic materials by the frequency dependences of reflection and transmission coefficient magnitudes during the interaction of electromagnetic waves in the microwave range with a sample in the form of a plate located in the cross section of a closed rectangular waveguide. Statistical analysis methods are applied to evaluating the errors arising during the application of this algorithm due to imperfect matching of the waveguide measurement path with the receivers and generator of the scalar circuit analyzer. It is shown that the proposed algorithm using the results of measuring reflection and transmission coefficients in a wide frequency range can significantly reduce the influence of frequency-dependent measurement errors on the accuracy of complex permittivity estimation. An additional advantage of the algorithm is that its implementation does not require vector network analyzers, which are very expensive.

Sliding-Mode Control for Interval Type-2 Fuzzy Systems: Event-Triggering WTOD Scheme.

This article investigates the sliding-mode control issue for interval type-2 (IT2) T-S fuzzy systems under limited communication resources. An event-triggering weight try-once-discard (ET-WTOD) protocol is formulated via two thresholds to determine the transmission of the state signal. The proposed ET-WTOD protocol can dynamically adjust the transmitted nodes and permits only partial components with larger error to be sent at each triggering instant, which is just the key distinction from the existing protocols. Under the imperfect premise matching framework, the controller's membership functions are reconstructed via the received state and the known upper and lower bounds, and then, a new scheduling signal set is established to design the scheduling-signal-dependent fuzzy sliding-mode controller. With the aid of the membership-function-dependent approach, the mismatching premise variables of the fuzzy model and the controller are effectively handled by introducing some slack matrices, while the relaxed stability conditions are derived to ensure the stability of the closed-loop system and the reachability of the specified sliding surface. Moreover, an optimized sliding domain is further obtained via the genetic algorithm (GA). Finally, the proposed control strategy is verified via the mass-spring-damper system.

Observer-Based Non-PDC Control Design for PMSG-Based Wind Energy Conversion Systems

In this study, the nonparallel distribution compensation (PDC) control is proposed for permanent magnet synchronous generator (PMSG)-based wind energy conversion systems (WECS). To do this, the nonlinear PMSG-based WECS is expressed by Takagi-Sugeno (T-S) fuzzy systems. Based on the imperfect premise matching, the T-S fuzzy observer is delineated for estimating the unmeasurable states of the proposed WECS. Unlike the traditional PDC control, a general non-PDC control strategy is designed via the T-S fuzzy observer. The designed control scheme indicates that it is not required to share the same membership functions as the observer and system. By constructing the Lyapunov functional with available information on the fuzzy membership function and introducing the slack variables, sufficient conditions are obtained to assure the asymptotic stability of error dynamic for the PMSG-based T-S fuzzy system and its observer. Finally, the feasibility and applicability of the derived theoretical results are validated through the numerical example.

Positivity and separation principle for observer-based output-feedback disturbance attenuation of uncertain discrete-time fuzzy models with immeasurable premise variables

We propose a robust observer-based output-feedback (OBOF) controller design method for the positive stabilization of discrete-time Takagi–Sugeno (T–S) fuzzy models subject to immeasurable premise variables, parametric uncertainties, and l∞ disturbances. The results of this paper are as follows. First, a new fuzzy OBOF controller structure is used to improve the possibility that the uncertain closed-loop system is positive. Second, the separation principle is demonstrated for the l∞–l∞ disturbance attenuation. Finally, the stability, positivity, and disturbance attenuation of T–S fuzzy closed-loop models are analyzed in the presence of the perturbation caused by the imperfect premise matching by the immeasurable premise variable.

A Resilient Adaptive Event-triggered H\(\infty\) Tracking Control of T-S Fuzzy Systems with Markovian Jump Parameters under DOS Attacks

In this paper, the problem of H\(\infty\) output-tracking control for T-S fuzzy markov jump systems(MJSs) with imperfect premise matching is investigated. The conditional probability information between the system and the controller is imperfectly known. Firstly, due to the in influence of network-induce delay, the system mode information can not be transmitted to the controller synchronously, thus, a discrete-time hidden markov model(HMM) is established to describe the asynchronous phenomenon between the system and the controller; Secondly, form the prospectively of practical applications, packet loss in two channels is taken into consideration, which is caused by denial-of-service(DOS) attacks; Thirdly, in order to improve the data transmission efficiency and save network bandwidth resources, a novel resilient adaptive event-triggered(AET) mechanism is proposed, in which the event-based threshold parameter is dynamically regulated over the processing. Additionally, resorted the compensation principle and the lyapunov-krasovski(L-K) functions methods, some sufficient conditions in form of liner matrix inequality(LMI) are achieved to co-guarantee the stability and H\(\infty\) tracking property of the closed-loop system; Finally, two examples are given to verify the effectiveness of our design mentality.

Scorpionfish rapidly change colour in response to their background

BackgroundTo facilitate background matching in heterogenous environments, some animals rapidly change body colouration. Marine predatory fishes might use this ability to hide from predators and prey. Here, we focus on scorpionfishes (Scorpaenidae), well-camouflaged, bottom-dwelling sit-and-wait predators. We tested whether Scorpaena maderensis and Scorpaena porcus adjust body luminance and hue in response to three artificial backgrounds and thereby achieve background matching. Both scorpionfish species are also red fluorescent, which could contribute to background matching at depth. Therefore, we tested whether red fluorescence is also regulated in response to different backgrounds. The darkest and the lightest backgrounds were grey, while the third background was orange of intermediate luminance. Scorpionfish were placed on all three backgrounds in a randomised repeated measures design. We documented changes in scorpionfish luminance and hue with image analysis and calculated contrast to the backgrounds. Changes were quantified from the visual perspective of two potential prey fishes, the triplefin Tripterygion delaisi and the goby Pomatoschistus flavescens. Additionally, we measured changes in the area of scorpionfish red fluorescence. Because scorpionfish changed quicker than initially expected, we measured luminance change at a higher temporal resolution in a second experiment.ResultsBoth scorpionfish species rapidly adjusted luminance and hue in response to a change of background. From prey visual perspective, scorpionfishes’ body achromatic and chromatic contrasts against the background were high, indicating imperfect background matching. Chromatic contrasts differed considerably between the two observer species, highlighting the importance of choosing natural observers with care when studying camouflage. Scorpionfish displayed larger areas of red fluorescence with increasing luminance of the background. With the second experiment, we showed that about 50% of the total luminance change observed after one minute is achieved very rapidly, in five to ten seconds.ConclusionBoth scorpionfish species change body luminance and hue in response to different backgrounds within seconds. While the achieved background matching was suboptimal for the artificial backgrounds, we propose that the observed changes were intended to reduce detectability, and are an essential strategy to camouflage in the natural environment.

Investigating an Alternative for Estimation from a Nonprobability Sample: Matching plus Calibration

Abstract Matching a nonprobability sample to a probability sample is one strategy both for selecting the nonprobability units and for weighting them. This approach has been employed in the past to select subsamples of persons from a large panel of volunteers. One method of weighting, introduced here, is to assign a unit in the nonprobability sample the weight from its matched case in the probability sample. The properties of resulting estimators depend on whether the probability sample weights are inverses of selection probabilities or are calibrated. In addition, imperfect matching can cause estimates from the matched sample to be biased so that its weights need to be adjusted, especially when the size of the volunteer panel is small. Calibration weighting combined with matching is one approach to correct bias and reduce variances. We explore the theoretical properties of the matched and matched, calibrated estimators with respect to a quasirandomization distribution that is assumed to describe how units in the nonprobability sample are observed, a superpopulation model for analysis variables collected in the nonprobability sample, and the randomization distribution for the probability sample. Numerical studies using simulated and real data from the 2015 US Behavioral Risk Factor Surveillance Survey are conducted to examine the performance of the alternative estimators.

New Relaxed Static Output Feedback Stabilization of T–S Fuzzy Systems with Time-Varying Delays

This paper investigates the imperfect premise matching-based (IPMB) static output feedback (SOF) controller for T–S fuzzy systems with time-varying delays. Firstly, by employing integral inequality techniques, the membership-function-independent fuzzy SOF design methods in terms of LMIs are presented based on imperfect premise matching (IPM) strategy. The obtained stabilization conditions do not contain equality constraints, and the output matrices do not have rank constraints. Secondly, some suitable relaxation variables are employed, and more relaxed membership-function-dependent (MFD) stabilization conditions are obtained by considering the local boundary information of membership functions (MFs). Finally, two simulation examples are given to show the progressiveness of the proposed methods in this paper.