Which Parameters Drive Approximation Inaccuracies?

This paper identifies parameters responsible for welfare reversals when the basic New Keynesian model is approximated. In our setting, a reversal occurs when the Ramsey policy under timeless perspective commitment ceases to be dominant against the Taylor rule after approximating the model. We find that the parameters involved are the degree of persistence in the autoregressive shock process and the labor elasticity of real output.Optimal Monetary policy, Approximations, Welfare Analysis, Timeless Perspective

Thermal Error Modelling of a CNC Machine Tool Feed Drive System using FEA Method

Recirculating ball screw systems are commonly used in machine tools and are one of the major heat sources which cause considerable thermal drift in CNC machine tools. Finite Element Analysis (FEA) method has been used successfully in the past to model the thermal characteristics of machine tools with promising results. Since FEA predictions are highly dependent on the efficacy of numerical parameters including the surrounding Boundary Conditions (BC), this study emphasises on an efficient modelling method to obtain optimised numerical parameters for acquiring a qualitative response from the feed drive system model. This study was performed on a medium size Vertical Machining Centre (VMC) feed drive system in which two parameter dentification methods have been employed; the general prediction method based on formulae provided by OEMs, and the energy balance method. The parameters obtained from both methods were applied to the FEA model of the machine feed drive system and validated against experimental results. Correlation with which was increased from 70 % to 80 % using the energy balance method

Simultaneous maximum-likelihood calibration of odometry and sensor parameters

For a differential-drive mobile robot equipped with an on-board range sensor, there are six parameters to calibrate: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot frame. This paper describes a method for calibrating all six parameters at the same time, without the need for external sensors or devices. Moreover, it is not necessary to drive the robot along particular trajectories. The available data are the measures of the angular velocities of the wheels and the range sensor readings. The maximum-likelihood calibration solution is found in a closed form

Drive Cycle Optimisation for Pollution Reduction

Green house gas emissions have abraded environmental quality for human existence. Automobile exhaust is a significant contributor globally to green house gases, among other contributors. This research investigates how vehicle fuel consumption can be tabulated from laboratory tests and road tests. The laboratory tests are used to establish mathematical relationships to predict fuel consumption as a function of such drive-cycle parameters as vehicle speed,acceleration and throttle position. Then, these relationships are applied to calculate fuel consumption during real-life road tests. In the future, the drive-cycle parameters contributing to vehicle fuel consumption could be optimized to lower automobile exhaust’s impact on environmental degradation

Which parameters drive approximation inaccuracies?

This paper identifies parameters responsible for welfare reversals when the basic New Keynesian model is approximated. In our setting, a reversal occurs when the Ramsey policy under timeless perspective commitment ceases to be dominant against the Taylor rule after approximating the model. We find that the parameters involved are the degree of persistence in the autoregressive shock process and the labor elasticity of real output

Driven Widom-Rowlinson lattice gas

In the Widom-Rowlinson lattice gas, two particle species (A, B) diffuse freely via particle-hole exchange, subject to both on-site exclusion and prohibition of A-B nearest-neighbor pairs. As an athermal system, the overall densities are the only control parameters. As the densities increase, an entropically driven phase transition occurs, leading to ordered states with A- and B-rich domains separated by hole-rich interfaces. Using Monte Carlo simulations, we analyze the effect of imposing a drive on this system, biasing particle moves along one direction. Our study parallels that for a driven Ising lattice gas -- the Katz-Lebowitz-Spohn (KLS) model, which displays atypical collective behavior, e.g., structure factors with discontinuity singularities and ordered states with domains only parallel to the drive. Here, other novel features emerge, including structure factors with kink singularities (best fitted to |q|), maxima at non-vanishing wavevector values, oscillating correlation functions, and ordering into multiple striped domains perpendicular to the drive, with a preferred wavelength depending on density and drive intensity. Moreover, the (hole-rich) interfaces between the domains are statistically rough (whether driven or not), in sharp contrast with those in the KLS model, in which the drive suppresses interfacial roughness. Defining a novel order parameter (to account for the emergence of multistripe states), we map out the phase diagram in the density-drive plane and present preliminary evidence for a critical phase in this driven lattice gas.Comment: 39 pages, 18 figure

Evaluation of Functional Condition of Respiratory Muscles of Patients with a Complicated Bronchial Asthma Pathology and Chronic Obstructive Pulmonary Diseases

The aim of the research was to study the functional state of respiratory muscles and neuro-respiratory drive in patients with a combined pathology of bronchial asthma and chronic obstructive pulmonary disease.The functional condition of the respiratory muscles and the tone of the respiratory centre were determined with the help of a device for occlusion spirometry. Also, the patient was observed with a spirometry, a general plethysmography of the body.Materials and methods.140 patients with combined broncho-obstructive pathology, 34 patients with asthma and 17 patients with COPD were examined. Spirometry, general plethysmography of the body and occlusion spirometry were provided for all patients.Results show a decrease in muscle strength of breath in all categories of patients with broncho-obstructive diseases, especially expressed in patients with bronchial asthma and asthma-COPD intersection. The muscle strength of breath was maintained with a significant increase in COPD patients compared with those with bronchial asthma. With increasing broncho-obstruction in patients with asthma-COPD intersection, there was a progressive and reliable decrease in muscle strength for breath and expiration, as well as a tendency to increase neuron respiratory drive. In patients with asthma-COPD intersection with more expressed symptoms revealed a significant and reliable weakening of muscle strength for breath and increased neuro-respiratory drive. During the work were obtained reliable links of the parameters of respiratory muscle strength not only with the parameters of pulmonary volume and bronchial patency, but also with the degree of neutrophilic inflammation in this category of patients.Conclusions The obtained data on failure of the functional state of the respiratory muscles and the neuro-respiratory drive can be used in the development of rehabilitation programs for the management of patients with combined broncho-obstructive pathology

Estimating bayesian decision problems with heterogeneous priors

In many areas of economics there is a growing interest in how expertise and preferences drive individual and group decision making under uncertainty. Increasingly, we wish to estimate such models to quantify which of these drive decision making. In this paper we propose a new channel through which we can empirically identify expertise and preference parameters by using variation in decisions over heterogeneous priors. Relative to existing estimation approaches, our \PriorBased Identi cation" extends the possible environments which can be estimated, and also substantially improves the accuracy and precision of estimates in those environments which can be estimated using existing methods