Blind Ptychographic Phase Retrieval via Convergent Alternating Direction Method of Multipliers

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A ptychographyic reconstruction is normally formulated as a blind phase retrieval problem, where both the image (sample) and the probe (illumination) have to be recovered from phaseless measured data. In this article we address a nonlinear least squares model for the blind ptychography problem with constraints on the image and the probe by maximum likelihood estimation of the Poisson noise model. We formulate a variant model that incorporates the information of phaseless measurements of the probe to eliminate possible artifacts. Next, we propose a generalized alternating direction method of multipliers designed for the proposed nonconvex models with convergence guarantee under mild conditions, where their subproblems can be solved by fast element-wise operations. Numerically, the proposed algorithm outperforms state-of-the-art algorithms in both speed and image quality.Comment: 23 page

An alternative methodology to predict aging effects on the mechanical properties of glass fiber reinforced cement (GRC)

The effect of three different aging methods (immersion in hot water, freeze–thaw cycles and wet–dry cycles) on the mechanical properties of GRC were studied and compared. Test results showed that immersion in hot water may be an unreliable method for modified GRC formulations, with it being in probability a very harmful procedure. A new aging method, mixing freeze–thaw cycles and wet–dry cycles, seems to be the most accurate simulation of weather conditions that produce a noticeable change in GRC mechanical properties. Future work should be carried out to find a correlation between real weather and the proposed aging method

Partially Coherent Ptychography by Gradient Decomposition of the Probe

Coherent ptychographic imaging experiments often discard over 99.9 % of the flux from a light source to define the coherence of an illumination. Even when coherent flux is sufficient, the stability required during an exposure is another important limiting factor. Partial coherence analysis can considerably reduce these limitations. A partially coherent illumination can often be written as the superposition of a single coherent illumination convolved with a separable translational kernel. In this paper we propose the Gradient Decomposition of the Probe (GDP), a model that exploits translational kernel separability, coupling the variances of the kernel with the transverse coherence. We describe an efficient first-order splitting algorithm GDP-ADMM to solve the proposed nonlinear optimization problem. Numerical experiments demonstrate the effectiveness of the proposed method with Gaussian and binary kernel functions in fly-scan measurements. Remarkably, GDP-ADMM produces satisfactory results even when the ratio between kernel width and beam size is more than one, or when the distance between successive acquisitions is twice as large as the beam width.Comment: 11 pages, 9 figure

Deep Reinforcement Learning in Recommender Systems

Recommender Systems aim to help customers find content of their interest by presenting them suggestions they are most likely to prefer. Reinforcement Learning, a Machine Learning paradigm where agents learn by interaction which actions to perform in an environment so as to maximize a reward, can be trained to give good recommendations. One of the problems when working with Reinforcement Learning algorithms is the dimensionality explosion, especially in the observation space. On the other hand, Industrial recommender systems deal with extremely large observation spaces. New Deep Reinforcement Learning algorithms can deal with this problem, but they are mainly focused on images. A new technique has been developed able to convert raw data into images, enabling DRL algorithms to be properly applied. This project addresses this line of investigation. The contributions of the project are: (1) defining a generalization of the Markov Decision Process formulation for Recommender Systems, (2) defining a way to express the observation as an image, and (3) demonstrating the use of both concepts by addressing a particular Recommender System case through Reinforcement Learning. Results show how the trained agents offer better recommendations than the arbitrary choice. However, the system does not achieve a great performance mainly due to the lack of interactions in the datase

Failure and impact behavior of facade panels made of glass fiber reinforced cement(GRC)

GRC is a cementitious composite material made up of a cement mortar matrix and chopped glass fibers. Due to its outstanding mechanical properties, GRC has been widely used to produce cladding panels and some civil engineering elements. Impact failure of cladding panels made of GRC may occur during production if some tool falls onto the panel, due to stone or other objects impacting at low velocities or caused by debris projected after a blast. Impact failure of a front panel of a building may have not only an important economic value but also human lives may be at risk if broken pieces of the panel fall from the building to the pavement. Therefore, knowing GRC impact strength is necessary to prevent economic costs and putting human lives at risk. One-stage light gas gun is an impact test machine capable of testing different materials subjected to impact loads. An experimental program was carried out, testing GRC samples of five different formulations, commonly used in building industry. Steel spheres were shot at different velocities on square GRC samples. The residual velocity of the projectiles was obtained both using a high speed camera with multiframe exposure and measuring the projectile’s penetration depth in molding clay blocks. Tests were performed on young and artificially aged GRC samples to compare GRC’s behavior when subjected to high strain rates. Numerical simulations using a hydrocode were made to analyze which parameters are most important during an impact event. GRC impact strength was obtained from test results. Also, GRC’s embrittlement, caused by GRC aging, has no influence on GRC impact behavior due to the small size of the projectile. Also, glass fibers used in GRC production only maintain GRC panels’ integrity but have no influence on GRC’s impact strength. Numerical models have reproduced accurately impact tests