Automated analysis of radar imagery of Venus: handling lack of ground truth

Lack of verifiable ground truth is a common problem in remote sensing image analysis. For example, consider the synthetic aperture radar (SAR) image data of Venus obtained by the Magellan spacecraft. Planetary scientists are interested in automatically cataloging the locations of all the small volcanoes in this data set; however, the problem is very difficult and cannot be performed with perfect reliability even by human experts. Thus, training and evaluating the performance of an automatic algorithm on this data set must be handled carefully. We discuss the use of weighted free-response receiver-operating characteristics (wFROCs) for evaluating detection performance when the “ground truth” is subjective. In particular, we evaluate the relative detection performance of humans and automatic algorithms. Our experimental results indicate that proper assessment of the uncertainty in “ground truth” is essential in applications of this nature

Automating the Hunt for Volcanoes on Venus

Our long-term goal is to develop a trainable tool for locating patterns of interest in large image databases. Toward this goal we have developed a prototype system, based on classical filtering and statistical pattern recognition techniques, for automatically locating volcanoes in the Magellan SAR database of Venus. Training for the specific volcano-detection task is obtained by synthesizing feature templates (via normalization and principal components analysis) from a small number of examples provided by experts. Candidate regions identified by a focus of attention (FOA) algorithm are classified based on correlations with the feature templates. Preliminary tests show performance comparable to trained human observers

Condition monitoring of an advanced gas-cooled nuclear reactor core

A critical component of an advanced gas-cooled reactor station is the graphite core. As a station ages, the graphite bricks that comprise the core can distort and may eventually crack. Since the core cannot be replaced, the core integrity ultimately determines the station life. Monitoring these distortions is usually restricted to the routine outages, which occur every few years, as this is the only time that the reactor core can be accessed by external sensing equipment. This paper presents a monitoring module based on model-based techniques using measurements obtained during the refuelling process. A fault detection and isolation filter based on unknown input observer techniques is developed. The role of this filter is to estimate the friction force produced by the interaction between the wall of the fuel channel and the fuel assembly supporting brushes. This allows an estimate to be made of the shape of the graphite bricks that comprise the core and, therefore, to monitor any distortion on them

Wh Question In-Situ and Movement in Najdi Dialect

Changes in the word’s place and the formation of the structure is a system by which some words move from its place to take another due to some effects of linguistic aspects like morphology and syntax . This movement is not only restricted to the words, but that may take place in phrases as well. These changes involve constrains that governs these changes and the movements process. Syntactic structure is one of the linguistic aspects that are commonly influenced in dialect languages. The structure of the sentence, including all kinds of sentences, is a matter of change in dialect. Much concern is paid to study the notion of interrogatives whether in Arabic dialect or in Gulf Arabic dialect. Since the divers of dialects of Saudi dialects are difficult to be touched, although these dialects are mutually intelligible. One of the two dominant dialects, Hijazi and Najd, can be a good representative of the rest of the sub-dialects. This paper will be a contribution to shed light on the structure of wh- interrogatives in-situ in Najdi Arabic dialect and the movement that takes place in different positions in the sentence

Integrated fracture-based model for the analysis of cracked reinforced concrete beams

This is the accepted manuscript.Due to the rapid advances in the development of techniques for monitoring and retrofitting concrete, there is a need to revisit and generalize classical theories in order to better assess the strength of existing reinforced concrete structures and to encompass strengthening systems. An improved understanding of concrete cracking taking into consideration local phenomena such as tensile and compressive concrete softening as well as the bond between the reinforcement and the concrete is required. In this paper, a fracture-based model is developed to describe the cracking process in reinforced concrete by integrating different local phenomena to more precisely describe the flexural behaviour of reinforced concrete beams. The model results show a good correlation with experimental data obtained by testing small scale concrete beams subjected to three-point bending. The beams exhibited mode I fracture propagation and during testing crack measurements were undertaken using a non-destructive digital image correlation technique. The stability of the cracking process was found to depend on the concrete strength, reinforcement properties and reinforcement ratio.The authors would like to thank the Yousef Jameel Foundation for their financial support of this research

Application of Digital Image Correlation to reinforced concrete fracture

The fracture process in reinforced concrete structures is complicated because it is associated with the development of both micro cracks and major cracks. The fracture behavior is also connected to other phenomena including strain localization and crack bridging and depends on the heterogeneity of concrete, the type of reinforcement, and the concrete and reinforcement properties. The purpose of this study is to investigate the mode I crack propagation in reinforced concrete using Digital Image Correlation (DIC). DIC is a robust, non-contact and precise tool for fracture measurements. Digital images are taken at different loading stages and by comparing the images it is possible to infer the deformation of an object subjected to external loads. In this paper, the relationship between the fracture properties and the properties of the concrete and steel reinforcement is investigated experimentally. Tests were performed on small-scale reinforced concrete specimens in three point bending. By means of the DIC technique the visualization and quantification of the fracture properties of reinforced concrete could be determined. The DIC technique was found to be an effective mean to measure the crack opening displacements.The authors would like to thank Yousef Jameel Foundation for their financial support of this research.This is the final published version, which can also be accessed on the publisher's website at: http://www.sciencedirect.com/science/article/pii/S2211812814002570

Attention focussing and anomaly detection in real-time systems monitoring

In real-time monitoring situations, more information is not necessarily better. When faced with complex emergency situations, operators can experience information overload and a compromising of their ability to react quickly and correctly. We describe an approach to focusing operator attention in real-time systems monitoring based on a set of empirical and model-based measures for determining the relative importance of sensor data

Solving Erosion and Corrosion Problems in Jordanian-Potash Company

The amount of surface material eroded by solid particles in a fluid stream depends on the conditions of fluid flow and on the mechanism of material removal. The paper  first analyses the mechanism of material removal for ductile and brittle materials. For ductile material, it is noted that erosion produced by particles striking the surface at shallow angles (  but the maximum erosion in brittle materials at perpendicular impact at ( . In  this paper ductile materials (steel alloys) are studied, then the paper discussed some aspects of the fluid flow conditions which may lead to erosion. Kind of pipe which connect between pumps and factory in Potash Company-Jordan is a carbon steel pipe. Because of large pressure from pumps (10 bar) and huge mass flow rate (about 700(m3 /hr)), particles (KCl, NaCl, ,MgCl) will strike with inner of pipe, erosion will happen, so a pipe will destroyed after many years. This problem considered costly, where Arab Potash Company is changing this pipe every seven years. Keywords: Erosion, Corrosion, Pipe System, Cracks, Fluid Flow, Steel Alloys, Brittle, Ductile

Using machine learning techniques to automate sky survey catalog generation

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data

A new generation of intelligent trainable tools for analyzing large scientific image databases

The focus of this paper is on the detection of natural, as opposed to human-made, objects. The distinction is important because, in the context of image analysis, natural objects tend to possess much greater variability in appearance than human-made objects. Hence, we shall focus primarily on the use of algorithms that 'learn by example' as the basis for image exploration. The 'learn by example' approach is potentially more generally applicable compared to model-based vision methods since domain scientists find it relatively easier to provide examples of what they are searching for versus describing a model