Managing groups of files in a rule oriented data management system (iRODS)

The iRODS system, created by the San Diego Supercomputing Centre, is a rule oriented data management system that allows the user to create sets of rules to define how the data is to be managed. Each rule corresponds to a particular action or operation (such as checksumming a file) and the system is flexible enough to allow the user to create new rules for new types of operations. The iRODS system can interface to any storage system (provided an iRODS driver is built for that system) and relies on its’ metadata catalogue to provide a virtual file-system that can handle files of any size and type. However, some storage systems (such as tape systems) do not handle small files efficiently and prefer small files to be packaged up (or “bundled”) into larger units. We have developed a system that can bundle small data files of any type into larger units - mounted collections. The system can create collection families and contains its’ own extensible metadata, including metadata on which family the collection belongs to. The mounted collection system can work standalone and is being incorporated into the iRODS system to enhance the systems flexibility to handle small files. In this paper we describe the motivation for creating a mounted collection system, its’ architecture and how it has been incorporated into the iRODS system. We describe different technologies used to create the mounted collection system and provide some performance numbers.

The effect of class size on student achievement: evidence from Bangladesh

This study examines the effect of class size on student achievement in Bangladesh using national secondary school survey data. A Ministry of Education rule regarding allocation of teachers to secondary grades is exploited to construct an instrument for class size. This rule causes a discontinuity between grade enrolment and class size thereby generating exogenous variation in the latter. It is found that OLS and IV estimates of class size effects have perverse signs: both yield a positive coefficient on the class size variable. The results suggest that reduction in class size in secondary grades is not efficient in a developing country like Bangladesh. Last, as by-product, some evidence is found suggesting that greater competition among schools improve student achievement.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

Categorization and construction of rule based systems

Expert systems have been increasingly popular for commercial importance. A rule based system is a special type of an expert system, which consists of a set of ‘if-then‘ rules and can be applied as a decision support system in many areas such as healthcare, transportation and security. Rule based systems can be constructed based on both expert knowledge and data. This paper aims to introduce the theory of rule based systems especially on categorization and construction of such systems from a conceptual point of view. This paper also introduces rule based systems for classification tasks in detail.

Clinical evaluation and COL2A1 gene analysis in 21 Brazilian families with Stickler syndrome: Identification of novel mutations, further genotype/phenotype correlation, and its implications for the diagnosis

We present clinical and molecular evaluation from a large cohort of patients with Stickler syndrome: 78 individuals from 21 unrelated Brazilian families. The patients were selected in a Hospital with a craniofacial dysmorphology assistance service and clinical diagnosis was based on the presence of cleft palate associated to facial and ocular anomalies of Stickler syndrome. Analysis of COL2A1 gene revealed 9 novel and 4 previously described pathogenic mutations. Except for the mutation c.556G>T (p.Gly186X), all the others were located in the triple helical domain. We did not find genotype/phenotype correlation in relation to type and position of the mutation in the triple helical domain. However, a significantly higher proportion of myopia in patients with mutations located in this domain was observed in relation to those with the mutation in the non-tripe helical domain (c.556G>T; P < 0.04). A trend towards a higher prevalence of glaucoma, although not statistically significant, was observed in the presence of the mutation c.556G>T. It is possible. that this mutation alters the splicing of the mRNA instead of only creating a premature stop codon and therefore it can lead to protein products of different ocular effects. One novel DNA variation (c.1266+7G>C) occurs near a splice site and it was observed to co-segregate with the phenotype in one of the two families with this DNA variation. As in silico analysis predicted that the c.1266+7G>C DNA variation can affect the efficiency of the splicing, we still cannot rule it out as non-pathogenic. Our study also showed that ascertainment through cleft palate associated to other craniofacial signs can be very efficient for identification of Stickler syndrome patients. Still, high frequency of familial cases and high frequency of underdevelopment of distal lateral tibial epiphyses observed in our patients suggested that the inclusion of this information can improve the clinical diagnosis of Stickler syndrome. (C) 2008 Elsevier Masson SAS. All rights reserved.

The degree of polydispersity in micellar dispersions: A sum rule approach

Statistical properties of a two-dimensional ideal dispersion of polydisperse micelles are derived by analyzing the convergence properties of a sum rule set by mass conservation. Internal micellar degrees of freedom are accounted for by a microscopic model describing small displacements of the constituting amphiphiles with respect to their equilibrium positions. The transfer matrix (TM) method is employed to compute internal micelle partition function. We show that the conditions under which the sum rule is saturated by the largest eigenvalue of the TM determine the value of amphiphile concentration above which the dispersion becomes highly polydisperse and micelle sizes approach a Schultz distribution. (C) 2011 Elsevier B.V. All rights reserved.

Shubnikov de Haas oscillations in double wells with opposite signs of the electronic g-factor

We report on the measurements of the Shubnikov de Haas oscillations (SdH) in symmetrically doped AlxGa1-xAs double wells with different Al compositions in wells, which lead to the opposite signs of the electronic g-factor in each layer. Surprisingly, the spin splitting appears and collapses several times with increase in the magnetic field, We attribute such behaviour to the oscillations of the exchange-correlation term with Landau filling factor. (C) 2007 Elsevier B.V. All rights reserved.

A Contour-based Separation of VerticallyAttached Traffic Signs

This report presents an algorithm for locating the cut points for and separatingvertically attached traffic signs in Sweden. This algorithm provides severaladvanced digital image processing features: binary image which representsvisual object and its complex rectangle background with number one and zerorespectively, improved cross correlation which shows the similarity of 2Dobjects and filters traffic sign candidates, simplified shape decompositionwhich smoothes contour of visual object iteratively in order to reduce whitenoises, flipping point detection which locates black noises candidates, chasmfilling algorithm which eliminates black noises, determines the final cut pointsand separates originally attached traffic signs into individual ones. At each step,the mediate results as well as the efficiency in practice would be presented toshow the advantages and disadvantages of the developed algorithm. Thisreport concentrates on contour-based recognition of Swedish traffic signs. Thegeneral shapes cover upward triangle, downward triangle, circle, rectangle andoctagon. At last, a demonstration program would be presented to show howthe algorithm works in real-time environment.

Evaluation of Red Colour Segmentation Algorithms in Traffic Signs Detection

Colour segmentation is the most commonly used method in road signs detection. Road sign contains several basic colours such as red, yellow, blue and white which depends on countries.The objective of this thesis is to do an evaluation of the four colour segmentation algorithms. Dynamic Threshold Algorithm, A Modification of de la Escalera’s Algorithm, the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm. The processing time and segmentation success rate as criteria are used to compare the performance of the four algorithms. And red colour is selected as the target colour to complete the comparison. All the testing images are selected from the Traffic Signs Database of Dalarna University [1] randomly according to the category. These road sign images are taken from a digital camera mounted in a moving car in Sweden.Experiments show that the Fuzzy Colour Segmentation Algorithm and Shadow and Highlight Invariant Algorithm are more accurate and stable to detect red colour of road signs. And the method could also be used in other colours analysis research. The yellow colour which is chosen to evaluate the performance of the four algorithms can reference Master Thesis of Yumei Liu.