300 research outputs found
Subnational Determinants of Foreign Direct Investments in the Russian Federation
No full textOur purpose is to examine the determinants of subnational distribution of Foreign Direct Investments (FDI) in the key fifteen regions of Russia over the period of 2005-2011 using panel data. Within the most important economic regions of the country we found market seeking is still the main purpose of foreign inward investments. As a result, the size of the Russian consumer market presents a significant influence on the foreign economic activities alongside trade openness and government economic incentives. Our results from regression analysis indicate that gross regional product per capita, trade openness and the existence of special economic zones have significant positive impact on the regional distribution of FDI in the Russian Federation
Provenance-based trust for grid computing: Position Paper
No full textCurrent evolutions of Internet technology such as Web Services, ebXML, peer-to-peer and Grid computing all point to the development of large-scale open networks of diverse computing systems interacting with one another to perform tasks. Grid systems (and Web Services) are exemplary in this respect and are perhaps some of the first large-scale open computing systems to see widespread use - making them an important testing ground for problems in trust management which are likely to arise. From this perspective, today's grid architectures suffer from limitations, such as lack of a mechanism to trace results and lack of infrastructure to build up trust networks. These are important concerns in open grids, in which "community resources" are owned and managed by multiple stakeholders, and are dynamically organised in virtual organisations. Provenance enables users to trace how a particular result has been arrived at by identifying the individual services and the aggregation of services that produced such a particular output. Against this background, we present a research agenda to design, conceive and implement an industrial-strength open provenance architecture for grid systems. We motivate its use with three complex grid applications, namely aerospace engineering, organ transplant management and bioinformatics. Industrial-strength provenance support includes a scalable and secure architecture, an open proposal for standardising the protocols and data structures, a set of tools for configuring and using the provenance architecture, an open source reference implementation, and a deployment and validation in industrial context. The provision of such facilities will enrich grid capabilities by including new functionalities required for solving complex problems such as provenance data to provide complete audit trails of process execution and third-party analysis and auditing. As a result, we anticipate that a larger uptake of grid technology is likely to occur, since unprecedented possibilities will be offered to users and will give them a competitive edge
ASME 3rd International Conference on Microchannels and Minichannels, Parts A and B
No full textAndres Carrano (with James B. Taylor and Satish G. Kandlikar) is a contributing author, Characterization of the Effect of Surface Roughness and Texture on Fluid Flow: Past, Present, and Future (Keynote), pp. 11-18.
Proceedings of ASME 3rd International Conference on Nanochannels, Microchannels and Minichannels.https://digitalcommons.fairfield.edu/engineering-books/1053/thumbnail.jp
A quantitative data representation framework for structural and functional MR Imaging with application to prostate cancer detection
No full textProstate cancer (CaP) is currently the second leading cause of cancer-related deaths in the United States among men, but there is a paucity of non-invasive image-based information for CaP detection and staging in vivo. Studies have shown the utility of multi-protocol magnetic resonance imaging (MRI) to improve CaP detection accuracy by using both T2-weighted (T2w), dynamic contrast enhanced (DCE), and diffusion weighted (DWI) MRI information. In this thesis, we present methods for quantitative representation of structural and functional imaging data with the objective of building automated classifiers to improve CaP detection accuracy in vivo. In vivo disease presence was quantified via extraction of textural signatures from T2w MRI. Evaluation of these signatures showed that CaP appearance within each of the two dominant prostate regions (central gland, peripheral zone) is significantly different. A classifier trained on zone-specific features also yielded a higher detection accuracy compared to a simpler, monolithic combination of all the texture features. While a number of automated classifiers are available, classifier choice must account for limitations in dataset size and annotation (such as with in vivo prostate MRI). A comprehensive evaluation of different classifier schemes was undertaken for the specific problem of automated CaP detection via T2w MRI on a zonewise basis. It was found that simple classifiers yielded significantly improved CaP detection accuracies compared to complex classifiers. Fundamental differences must be overcome when constructing a unified quantitative representation of structural (T2w) and functional (DCE, DWI) MRI. We present a novel technique, referred to as consensus embedding, which constructs a lower dimensional representation (embedding) from a high dimensional feature space such that information (class-based or otherwise) is optimally preserved. Consensus embedding is shown to result in an improved representation of the data compared to alternative DR-based strategies in a variety of experimental domains. A unified quantitative representation of T2w, DCE, and DWI prostate MRI was constructed via the consensus embedding framework. This yielded an integrated classifier which was more accurate for CaP detection in vivo as compared to using structural and functional information individually, or using a naive combination of such differing types of information.Ph. D.Includes bibliographical referencesIncludes vitaby Satish Easwar Viswanat
Fault Diagnosis of Semiconductor Random Access Memories
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Reason: Restricted to UIUC communityOpen Restriction set for Item 100821 on 2019-11-15T17:33:23Z with date null by [email protected] Services Electronics Program / DAAB-07-72-C-0259OpenCoordinated Science Laboratory was formerly known as Control Systems Laboratory"Author name appears as ""Satish Munkund Thatte"" in front matter
Job evaluation and incentives - its effects on wages unions and industrial relations, with particular reference to its impact on the socio-economic life of workers in general, 1961
No full textDynamic Prediction of Delays in Software Projects using Delay Patterns and Bayesian Modeling
No full textModern agile software projects are subject to constant change, making it essential to re-asses overall delay risk throughout the project life cycle. Existing effort estimation models are static and not able to incorporate changes occurring during project execution. In this paper, we propose a dynamic model for continuously predicting overall delay using delay patterns and Bayesian modeling. The model incorporates the context of the project phase and learns from changes in team performance over time. We apply the approach to real-world data from 4,040 epics and 270 teams at ING. An empirical evaluation of our approach and comparison to the state-of-the-art demonstrate significant improvements in predictive accuracy. The dynamic model consistently outperforms static approaches and the state-of-the-art, even during early project phases.Software EngineeringSoftware Technolog
Shelf life extension of Indian traditional sweet based holige
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Social Indicators Research: A Retrospective Using Bibliometric Analysis
No full textSocial Indicators Research (SIR) publishes novel and groundbreaking research focusing on
social indicators related to quality of life and sustainability. Using bibliometrics, this study
aims to offer a retrospective of the major trends (e.g., publication, citation, and top contributing
authors, institutions, and countries) and intellectual structure of SIR. The retrospective
indicates that SIR, which has grown substantially in productivity and impact, attracts
contributions worldwide, notably from the USA, with 11 major themes revealed between
1974 and 2019. Using a zero-inflated negative binomial regression, this study also reveals
the factors that influence the citation count of SIR publications, namely article age, number
of author keywords, title novelty, title length, USA affiliation, and number of authors.
Noteworthily, this study, which represents the inaugural review of SIR, should be useful for
readers to gain rich insights into the state of research on social indicators related to quality
of life and sustainability
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