The Cornell Electron Storage Ring has been reconfigured as a test accelerator (CesrTA) for damping ring R&D for the International Linear Collider (ILC). As part of the research effort, low emittance tuning techniques are being developed with a goal of achieving a vertical emittance approaching that of the ILC damping rings. These techniques include gain mapping to characterize beam position mon...

Optical imaging studies of orientation and direction preference in visual cortex have typically used vector averaging to obtain angle and magnitude maps. This method has shown half-rotation orientation singularities (pinwheels) located within regions of low orientation vector magnitude. Direction preference is generally orthogonal to orientation preference, but often deviates from this, particu...

The present work is concerned with relay auto tuning of parallel cascade controllers. The method proposed by Srinivasan and Chidambaram [10] to analyze the conventional on-off relay oscillations for a single loop feedback controller is extended to the relay tuning of parallel cascade controllers. Using the ultimate gain and ultimate cross over frequency of the two loops, the inner loop (PI) and...

We present a new analytical method for characterizing the directional tuning of neural data. The method is based on computing parameters associated with the geometric properties of solids, and provides an estimate of preferred direction in the context of non-uniform sampling of directions. Unlike optimization methods based on fitting tuning functions, the plate method is computationally fast, a...

Finding appropriate values for the parameters of an algorithm is a challenging, important, and time consuming task. While typically parameters are tuned by hand, recent studies have shown that automatic tuning procedures can effectively handle this task and often find better parameter settings. F-Race has been proposed specifically for this purpose and it has proven to be very effective in a nu...

This paper presents the development of an on-line self-tuning algorithm for PID Controller to control the Governor using Successive approximation method. The successive approximation method is purely based on computational technique. The conventional PID controller is replaced by self tuning PID controller; to make them more general and to achieve minimum steadystate error, also to improve the ...

In this paper, we developed the parametric estimation and the self-tuning control problem of the nonlinear systems which are described by discrete-time nonlinear mathematical models, with unknown, time-varying parameters, and operative in a stochastic environment. The parametric estimation is realized by using the prediction error method and the recursive least squares techniques. The self-tuni...

In this paper, we propose a novel domain adaptation method named “mixed fine tuning” for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an NMT model on an out-of-domain parallel corpus, and then fine tune it on a parallel corpus which is a mix of the in-domain and out-ofdomain corpora. All corpora are augmented with a...

This article considers deterministic computer experiments with real-valued tuning parameters which determine the accuracy of the numerical algorithm. The aim is to integrate computer outputs with different tuning parameters. Finite element method with mesh density as the tuning parameter is an important case. Novel nonstationary Gaussian process models are proposed to establish a framework cons...

This paper presents an LMI-based method for the design and tuning of robust H2 output feedback controllers, illustrated with two case studies. The conservatism of design is considerably reduced by a proposed scaling procedure, referred to as K-S iteration. The method is applied to the ACC benchmark problem and shown to outperform previously published solutions. The choice of tuning parameters a...