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This paper aims to present a special transformation that is applied to univariable polynomials of an arbitrary order, resulting in the generation of the proposed offset eliminated polynomial. This transform-based approach is used in the analysis and synthesis of temporal arc functions, which are time domain polynomial functions possessing two or more values simultaneously. Using the proposed transform, the submerged values of temporal arcs can also be extracted in measurements.

The methodology involves a two-step mathematical procedure in which the proposed transform of the weighted modified derivative of the polynomial is generated, followed by multiplication with a linear or ramp function. The transform introduces a stretching in the temporal or spatial domain depending on the type of variable under consideration, resulting in modifications for parameters such as time derivative and relative velocity.

Detailed analysis of various parameters in this modified time domain is performed and results are presented. Additionally, using the proposed methodology, the submerged value of any temporal arc function can also be extracted in measurements, thereby unraveling the temporal arc.

A typical implementation study with results is also presented for an operational amplifier-based temporal arc-producing square rooting circuit for the extraction of the submerged value of the function.

The proposed transform-based approach has major applications in extracting the values of temporal arc functions that are submerged in conventional experimental measurements, thereby providing a novel method in unraveling that class of special functions.

This article examines the macroeconomic impact of a consumption‐based value‐added tax (VAT) using simulations of a large‐scale model. The VAT is imposed as a structural reform of the tax code rather than as a revenue‐raising device, i.e., the revenues from the VAT are offset by compensatory reductions elsewhere. Three basic scenarios are examined, in which 1) the VAT is offset by individual rate reductions, 2) abolition of the corporate profits tax in conjunction with a small individual rate cut, and 3) an investment tax credit with the balance of the revenues offset by a personal rate cut. Additionally, this paper examines the effects of the microeconomic incidence of the VAT, i.e., whether it is fully passed through to output prices or shifted back onto profits. The finding is that the VAT in general raises the long‐term level of output, but at the cost of initial output losses, which are in evidence even when the associated rise in the price level is accommodated by a corresponding shift in monetary policy. In addition to changes in the intertemporal distribution of growth, there are significant changes in the composition of GNP, which shifts away from consumption, toward business fixed investment and net exports. These changes are particularly pronounced when the VAT is fully passed through. When the tax is partially shifted back, the gains in investment and trade are less marked, while business profits are reduced, and the long‐term increase in output is smaller.

This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

The purpose of this paper is to evaluate three categories of four-degrees of freedom (4-DOFs) upper limb rehabilitation exoskeleton mechanisms from the perspective of relative movement offsets between the upper limb and the exoskeleton, so as to provide reference for the selection of exoskeleton mechanism configurations.

According to the configuration synthesis and optimum principles of 4-DOFs upper limb exoskeleton mechanisms, three categories of exoskeletons compatible with upper limb were proposed. From the perspective of human exoskeleton closed chain, through reasonable decomposition and kinematic characteristics analysis of passive connective joints, the kinematic equations of three categories exoskeletons were established and inverse position solution method were addressed. Subsequently, three indexes, which can represent the relative movement offsets of human–exoskeleton were defined.

Based on the presented position solution and evaluation indexes, the joint displacements and relative movement offsets of the three exoskeletons during eating movement were compared, on which the kinematic characteristics were investigated. The results indicated that the second category of exoskeleton was more suitable for upper limb rehabilitation than the other two categories.

This paper has a certain reference value for the selection of the 4-DOFs upper extremity rehabilitation exoskeleton mechanism configurations. The selected exoskeleton can ensure the safety and comfort of stroke patients with upper limb dyskinesia during rehabilitation training.

This paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.

Robot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.

Laguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.

The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.

The purpose of this paper is to demonstrate the simplicity and versatility of micro‐cantilever based sensors and to present the influence of added mass and stress on the frequency response of the sensor in order to determine the most suitable sensing domain for a given application.

The frequency response of micro‐cantilevers depends not only on the applied mass and surface stress, but also on the mass position. An interpretation of the theoretical frequency results of the 1st and 2nd natural frequencies, for added mass, identifies a nodal point for the 2nd natural frequency which demonstrates mass invariance. Hence, at this nodal point, the frequency response remains constant regardless of mass and may be used for identifying purely induced surface stress influences on the micro‐cantilever's dynamic response. The Rayleigh‐Ritz energy method is used for the theoretical analysis. Theoretical results are compared with experimental results.

A graph of the 2nd natural frequency of micro‐cantilevers with added mass demonstrates the variability of the frequency with mass position on the micro‐cantilever. Of particular interest is the nodal point at which mass independence is revealed. This nodal point may be exploited to investigate purely stress‐related influences on the dynamic characteristics of micro‐cantilever sensors, thereby eliminating such effects as reactant evaporation from the micro‐cantilever sensor surface. In this regard, the nodal point of the 2nd natural frequency response is used to decouple mass‐stress influences.

Owing to the micro‐scale size of the micro‐cantilevers, it may not be possible to apply mass or stress directly at the nodal point and to concentrate its influence there. Hence, a certain amount of influence due to mass‐stress coupling may remain in the frequency responses observed.

Silicon micro‐cantilevers can be easily shaped and sensitized to a variety of influences. These qualities are highly regarded for sensor applications. The work presented herein, contributes to the optimization of micro‐cantilever sensors' dynamic response as a function of mass and surface stress influences. The main criterion for choosing one or the other is based on the time for the surface reaction to take place between the sensing material and the target material. The results presented contribute to the performance optimization of micro‐cantilever based medical and bio‐sensors.

Surface stress effects are generally of much smaller magnitude than mass influences; hence, through an investigation of the stress effects at the nodal point of the 2nd natural frequency it is possible to eliminate the mass influence completely. At this position mass and stress influences are decoupled and the sensor response can be uniquely quantified as a function of the applied stress. This is important for bio‐medical and health monitoring applications in which changes to the applied mass or surface stress on a micro‐cantilever sensor, may be readily observed through changes to the natural frequency response of the micro‐cantilever.

A novel rapid prototyping technology incorporating a curved layer building style was developed. The new process, based on laminated object manufacturing (LOM), was designed for efficient fabrication of curved layer structures made from ceramics and fiber reinforced composites. A new LOM machine was created, referred to as curved layer LOM. This new machine uses ceramic tapes and fiber prepregs as feedstocks and fabricates curved structures on a curved‐layer by curved‐layer basis. The output of the process is a three‐dimensional “green” ceramic that is capable of being processed to a seamless, fully dense ceramic using traditional techniques. A detailed description is made of the necessary software and hardware for this new process. Also reviewed is the development of ceramic preforms and accompanying process technology for net shape ceramic fabrication. Monolithic ceramic (SiC) and ceramic matrix composite (SiC/SiC) articles were fabricated using both the flat layer and curved layer LOM processes. For making curved layer objects, the curved process afforded the advantages of eliminated stair step effect, increased build speed, reduced waste, reduced need for decubing, and maintenance of continuous fibers in the direction of curvature.

The purpose of this paper is to study the implementation of GNSS technique in aviation for recovery of aircraft’s position using Precise Point Positioning (PPP) method.

The aircraft’s coordinates in ellipsoidal frame were obtained based on GPS code and phase observations for PPP method. The numerical computations were executed in post-processing mode in the CSRS-PPP and magicPPP online services. The mathematical scheme of PPP method was development using indifference equations of Ionosphere-Free linear combination. In the experiment, airborne test using Cessna 172 aircraft on June 01, 2010 in the military airport in Deblin was realized. The aircraft’s position was determined using data from GNSS receiver (Topcon HiperPro with interval of 1 s).

In this paper, the accuracy of aircraft’s position is better than 0.07 m for CSRS-PPP service and better than 0.27 m for magicPPP service. In case of the Mean Radial Spherical Error parameter, the average value for CSRS-PPP service equals to 0.01 m, whereas for magicPPP, it is about 0.38 m. The values of vertical coordinate of Cessna 172 aircraft were also checked with results of Real Time Kinematic–On The Fly technique.

In this paper, the analysis of aircraft positioning is focused on the application of the PPP method in post-processing mode. In near real time, the PPP method still has limitations, especially in the area of ambiguity resolution and also instrumental biases (e.g. Narrow Lane Hardware Delays).

The PPP method can be applied in aviation in post-processing mode for verification of true aircraft coordinates and elimination of blunder errors from adjustment processing of GNSS observations. The Zenith Wet Delay term as a product of troposphere delay and receiver clock bias as a product of precise time transfer can be obtained in the PPP method.

The paper presents that the PPP method is an alternative solution for the recovery of aircraft’s position in aviation, and this method can be also applied in the positioning of aircraft based on GLONASS or GPS/GLONASS data.

Drawing on the signaling theory and the relational exchange theory, this study investigates how buyer–supplier trust is influenced through the congruence and incongruence between blockchain and norm of solidarity. The moderating role of technology uncertainty is further examined.

Using a survey data of 110 Chinese firms, this study empirically tests not only the combined effect of blockchain and norm of solidarity on trust, but also how this combined effect is moderated by technology uncertainty. The proposed hypotheses are tested using the polynomial regression analysis and the response surface methodology.

The results suggest that trust increases along with an increasing congruence between blockchain and norm or solidarity, but in a diminishing rate (i.e. an inverted U-shaped relationship). Simultaneously, incongruence between blockchain and norm of solidarity can also guarantee sufficient trust (i.e. a U-shaped relationship). Moreover, technology uncertainty overturns the inverted U-shaped relationship between blockchain and norm of solidarity congruence on trust into a U-shaped relationship and nullifies the U-shaped relationship between blockchain and norm of solidarity incongruence on trust.

This study enriches supply chain governance literature by introducing the emerging blockchain governance and examining the blockchain governance's interplay with a conventional relational norm. The study emphasizes that the combined effects of these two are quite complex. Blockchain and norm of solidarity can offset each other’s limitations when both are at low to moderate levels. But simultaneous pursuit of both high blockchain and norm has only limited marginal benefits. Furthermore, the study also highlights the importance of technology uncertainty under which the combined effects between the two governance mechanisms vary. Collectively, the results provide nuanced insights into the design of supply chain governance portfolios in the digital era.

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In this chapter, we apply an RKD approach to study the effect of unemployment benefits on the duration of joblessness in Austria, and discuss implementation issues that may arise in similar settings, including the use of bandwidth selection algorithms and bias-correction procedures. Although recent developments in nonparametric estimation (Calonico, Cattaneo, & Farrell, 2014; Imbens & Kalyanaraman, 2012) are sometimes interpreted by practitioners as pointing to a default estimation procedure, we show that in any given application different procedures may perform better or worse. In particular, Monte Carlo simulations based on data-generating processes that closely resemble the data from our application show that some asymptotically dominant procedures may actually perform worse than “sub-optimal” alternatives in a given empirical application.