Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Data Processing Modeling in Decision Support Systems.

Due to the advancement of both, information technology in general, and databases in particular; data storage devices are becoming cheaper and data processing speed is increasing. As result of this, organizations tend to store large volumes of data holding great potential information. Decision Support Systems, DSS try to use the stored data to obtain valuable information for organizations. In this paper, we use both data models and use cases to represent the functionality of data processing in DSS following Software Engineering processes. We propose a methodology to develop DSS in the Analysis phase, respective of data processing modeling. We have used, as a starting point, a data model adapted to the semantics involved in multidimensional databases or data warehouses, DW. Also, we have taken an algorithm that provides us with all the possible ways to automatically cross check multidimensional model data. Using the aforementioned, we propose diagrams and descriptions of use cases, which can be considered as patterns representing the DSS functionality, in regard to DW data processing, DW on which DSS are based. We highlight the reusability and automation benefits that this can be achieved, and we think this study can serve as a guide in the development of DSS.

KATS: A Knowledge Acquisition Tool Based on Electronic Document Processing

This paper describes a particular knowledge acquisition tool for the construction and maintenance of the knowledge model of an intelligent system for emergency management in the field of hydrology. This tool has been developed following an innovative approach directed to end-users non familiarized in computer oriented terminology. According to this approach, the tool is conceived as a document processor specialized in a particular domain (hydrology) in such a way that the whole knowledge model is viewed by the user as an electronic document. The paper first describes the characteristics of the knowledge model of the intelligent system and summarizes the problems that we found during the development and maintenance of such type of model. Then, the paper describes the KATS tool, a software application that we have designed to help in this task to be used by users who are not experts in computer programming. Finally, the paper shows a comparison between KATS and other approaches for knowledge acquisition.

Ste6p Mutants Defective in Exit from the Endoplasmic Reticulum (ER) Reveal Aspects of an ER Quality Control Pathway in Saccharomyces cerevisiae

We are studying the intracellular trafficking of the multispanning membrane protein Ste6p, the a-factor transporter in Saccharomyces cerevisiae and a member of the ATP-binding cassette superfamily of proteins. In the present study, we have used Ste6p as model for studying the process of endoplasmic reticulum (ER) quality control, about which relatively little is known in yeast. We have identified three mutant forms of Ste6p that are aberrantly ER retained, as determined by immunofluorescence and subcellular fractionation. By pulse-chase metabolic labeling, we demonstrate that these mutants define two distinct classes. The single member of Class I, Ste6–166p, is highly unstable. We show that its degradation involves the ubiquitin–proteasome system, as indicated by its in vivo stabilization in certain ubiquitin–proteasome mutants or when cells are treated with the proteasome inhibitor drug MG132. The two Class II mutant proteins, Ste6–13p and Ste6–90p, are hyperstable relative to wild-type Ste6p and accumulate in the ER membrane. This represents the first report of a single protein in yeast for which distinct mutant forms can be channeled to different outcomes by the ER quality control system. We propose that these two classes of ER-retained Ste6p mutants may define distinct checkpoint steps in a linear pathway of ER quality control in yeast. In addition, a screen for high-copy suppressors of the mating defect of one of the ER-retained ste6 mutants has identified a proteasome subunit, Hrd2p/p97, previously implicated in the regulated degradation of wild-type hydroxymethylglutaryl-CoA reductase in the ER membrane.

Quality Control in the Secretory Pathway: The Role of Calreticulin, Calnexin and BiP in the Retention of Glycoproteins with C-Terminal Truncations

Unlike properly folded and assembled proteins, most misfolded and incompletely assembled proteins are retained in the endoplasmic reticulum of mammalian cells and degraded without transport to the Golgi complex. To analyze the mechanisms underlying this unique sorting process and its fidelity, the fate of C-terminally truncated fragments of influenza hemagglutinin was determined. An assortment of different fragments was generated by adding puromycin at low concentrations to influenza virus-infected tissue culture cells. Of the fragments generated, <2% was secreted, indicating that the system for detecting defects in newly synthesized proteins is quite stringent. The majority of secreted species corresponded to folding domains within the viral spike glycoprotein. The retained fragments acquired a partially folded structure with intrachain disulfide bonds and conformation-dependent antigenic epitopes. They associated with two lectin-like endoplasmic reticulum chaperones (calnexin and calreticulin) but not BiP/GRP78. Inhibition of the association with calnexin and calreticulin by the addition of castanospermine significantly increased fragment secretion. However, it also caused association with BiP/GRP78. These results indicated that the association with calnexin and calreticulin was involved in retaining the fragments. They also suggested that BiP/GRP78 could serve as a backup for calnexin and calreticulin in retaining the fragments. In summary, the results showed that the quality control system in the secretory pathway was efficient and sensitive to folding defects, and that it involved multiple interactions with endoplasmic reticulum chaperones.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Online Personal Data Processing and EU Data Protection Reform. CEPS Task Force Report, April 2013

This report sheds light on the fundamental questions and underlying tensions between current policy objectives, compliance strategies and global trends in online personal data processing, assessing the existing and future framework in terms of effective regulation and public policy. Based on the discussions among the members of the CEPS Digital Forum and independent research carried out by the rapporteurs, policy conclusions are derived with the aim of making EU data protection policy more fit for purpose in today’s online technological context. This report constructively engages with the EU data protection framework, but does not provide a textual analysis of the EU data protection reform proposal as such.