EIT image reconstruction is an ill-posed problem, the spatial resolution of the estimated conductivity distribution is usually poor and the external voltage measurements are subject to variable noise. Therefore, EIT conductivity estimation cannot be used in the raw form to correctly estimate the shape and size of complex shaped regional anomalies. An efficient algorithm employing a shape based ...

We present a scalable and robust Bayesian inference method for linear state space models. The method is applied to demand forecasting in the context of a large e-commerce platform, paying special attention to intermittent and bursty target statistics. Inference is approximated by the Newton-Raphson algorithm, reduced to linear-time Kalman smoothing, which allows us to operate on several orders ...

The objectives of this study were to provide new parameters to better understand labor curves, and to provide a model to predict the time to full cervical dilation (CD). We studied labor curves using the retrospective records of 594 nulliparas, including at term, spontaneous labor onset, and singleton vertex deliveries of normal birth weight infants. We redefined the parameters of Friedman's la...

The significant increase in planned offshore wind parks and the tendency towards large parks in considerable distances offshore, make the well established HVDC technology a favorable solution for the connection of these large & distant offshore wind parks to the main power grid onshore. It is therefore necessary to adequately model the HVDC transmission links and integrate them in the load flow...

This paper reports on an FPGA implementation of sparse LU decomposition. The resulting special purpose hardware is geared towards power system problems load flow computation which are typically solved iteratively using Newton Raphson. The key step in this process, which takes approximately 85% of the computation time, is the solution of sparse linear systems arising from the Jacobian matrices t...

A hybrid particle swarm optimization algorithm which includes two alternative gradient-based methods for handling constraints has been proposed to solve process synthesis and design problems which involve continuous and binary variables and equality and inequality constraints (a mixed integer non-linear programming problem, MINLP). The first method for handling constraints uses the Newton-Raphs...

This paper focuses on using the Newton-Raphson method to solve power-flow problems. Since most computationally demanding part of is linear equations at each iteration, this study investigates different approaches both central processing unit (CPU) and graphical (GPU). Six have been developed evaluated in paper: two these run entirely CPU while other GPU, remaining are hybrid that GPU. All six d...