turning of hardened steels using a single point cutting tool has replaced the cylindrical grinding now as it offers attractive benefits in terms of lower equipment costs, shorter set up time, fewer process setups, higher material removal rate, better surface quality and elimination of cutting fluids compared to cylindrical grinding. in order to obtain desired surface quality by machining, prope...

We study the sample complexity of learning neural networks, by providing new bounds on their Rademacher complexity assuming norm constraints on the parameter matrix of each layer. Compared to previous work, these complexity bounds have improved dependence on the network depth, and under some additional assumptions, are fully independent of the network size (both depth and width). These results ...

The n-tree approximation scheme, introduced in the context of random directed polymers, is here applied to the computation of the maximum Lya-punov exponent in a coupled map lattice. We discuss both an exact implementation for small tree-depth n and a numerical implementation for larger ns. We find that the phase-transition predicted by the mean field approach shifts towards larger values of th...

The process of laser beam transformation hardening is principally controlled by two independent parameters, the absorbed laser power on a given area and the interaction time. These parameters can be transformed into two functional parameters: the maximum surface temperature and the hardening depth. It has been proved that with a constant hardening depth the results (hardness. residual stress. e...

A computable complexity measure analogous to computational depth is developed using the Lempel-Ziv compression algorithm. This complexity measure, which we call compression depth, is then applied to the computational output of cellular automata. We nd that compression depth captures the complexity found in Wolfram Class III celluar automata, and is in good agreement with his classi cation schem...

The object reconstruction from synthesized and noisy photothermal signals was carried out by deconvoluting contrast scans by means of photothermal point spread function. The unknown defect depth parameter was estimated by minimizing the "imaginary content" of the deconvoluted real valued defect distribution. The algorithm shows remarkable accuracy even in the presence of 10%-noise in finding th...

A MAP-MRF based scheme is proposed for simultaneous recovery of the depth and the focused image of a scene from two defocused images. The space-variant blur parameter and the focused image of the scene are both modeled as MRFs and their MAP estimates are obtained using simulated annealing. The performance of the proposed scheme is tested on synthetic as well as real data and the estimates of th...

Breadth-first search (BFS) and depth-first search (DFS) are the two most fundamental search algorithms. We derive approximations of their expected runtimes in complete trees, as a function of tree depth and probabilistic goal distribution. We also demonstrate that the analytical approximations are close to the empirical averages for most parameter settings, and that the results can be used to p...

A computable complexity measure analogous to computational depth is developed using the Lempel-Ziv compression algorithm. This complexity measure, which we call compression depth, is then applied to the computational output of cellular automata. We nd that compression depth captures the complexity found in Wolfram Class III celluar automata, and is in good agreement with his classi cation schem...

We present a novel model for the true vertical depth (TVD) positioning error in horizontal wells. The model utilizes a non-stationary Gaussian process known as the integrated Ornstein-Uhlenbeck process. This process is continuous and exhibits the known systematic accumulation of vertical errors with increasing measured depth. The well corrections produced are smooth and maintain the underlying ...