18 research outputs found

    Advances in Hydraulics and Hydroinformatics Volume 2

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    This Special Issue reports on recent research trends in hydraulics, hydrodynamics, and hydroinformatics, and their novel applications in practical engineering. The Issue covers a wide range of topics, including open channel flows, sediment transport dynamics, two-phase flows, flow-induced vibration and water quality. The collected papers provide insight into new developments in physical, mathematical, and numerical modelling of important problems in hydraulics and hydroinformatics, and include demonstrations of the application of such models in water resources engineering

    Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstracts

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    Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstract

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Biosensors

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    A biosensor is defined as a detecting device that combines a transducer with a biologically sensitive and selective component. When a specific target molecule interacts with the biological component, a signal is produced, at transducer level, proportional to the concentration of the substance. Therefore biosensors can measure compounds present in the environment, chemical processes, food and human body at low cost if compared with traditional analytical techniques. This book covers a wide range of aspects and issues related to biosensor technology, bringing together researchers from 11 different countries. The book consists of 16 chapters written by 53 authors. The first four chapters describe several aspects of nanotechnology applied to biosensors. The subsequent section, including three chapters, is devoted to biosensor applications in the fields of drug discovery, diagnostics and bacteria detection. The principles behind optical biosensors and some of their application are discussed in chapters from 8 to 11. The last five chapters treat of microelectronics, interfacing circuits, signal transmission, biotelemetry and algorithms applied to biosensing

    Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstracts

    Get PDF
    Seventh International Workshop on Simulation, 21-25 May, 2013, Department of Statistical Sciences, Unit of Rimini, University of Bologna, Italy. Book of Abstract

    The evaluation of Corona and Ikonos satellite imagery for archaeological applications in a semi-arid environment

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    Archaeologists have been aware of the potential of satellite imagery as a tool almost since the first Earth remote sensing satellite. Initially sensors such as Landsat had a ground resolution which was too coarse for thorough archaeological prospection although the imagery was used for geo-archaeological and enviro-archaeological analyses. In the intervening years the spatial and spectral resolution of these sensing devices has improved. In recent years two important occurrences enhanced the archaeological applicability of imagery from satellite platforms: The declassification of high resolution photography by the American and Russian governments and the deregulation of commercial remote sensing systems allowing the collection of sub metre resolution imagery. This thesis aims to evaluate the archaeological application of three potentially important resources; Corona space photography and Ikonos panchromatic and multispectral imager). These resources are evaluated in conjunction with Landsat Thematic Mapper (TM) imagery over a 600 square km study area in the semi-arid environment around Homs, Syria. The archaeological resource in this area is poorly understood, mapped and documented. The images are evaluated for their ability to create thematic layers and to locate archaeological residues in different environmental zones. Further consideration is given to the physical factors that allow archaeological residues to be identified and how satellite imagery and modern technology may impact on Cultural Resource Management. This research demonstrates that modern high resolution and historic satellite imagery can be important tools for archaeologists studying in semi-arid environments. The imagery has allowed a representative range of archaeological features and landscape themes to be identified. The research shows that the use of satellite imagery can have significant impact on the design of the archaeological survey in the middle-east and perhaps in other environments

    Shrinkage in Quickest Change Detection, Multichannel Profile Monitoring, and Uncertainty Quantification

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    In the information age, many real-world applications such as biosurveillance, manufacturing systems, physical and computer experiments often involve data that are massive, high-dimension or have complicated structures. In some cases it is cheap to collect large-scale data, while in other cases it may be costly or time-consuming to collect them. In either case, it is often non-trivial to extract information from these types of data to make useful decisions. This dissertation makes methodology contributions to three important subfields of statistics: (i) Large-scale multi-stream quickest change detection, (ii) multichannel profile monitoring and (iii) global optimization of expensive functions. A common feature of the thesis work is the use of shrinkage to the respective subfields to address the challenges of high-dimensional or complicated data. However, since different subfields and applications have different features and challenges, details of the shrinkage techniques vary with the subfield. This dissertation consists of three chapters. In Chapter 1, we study the problem of online monitoring large-scale data streams, which has many important applications from biosurveillance and quality control to finance and security in modern information age. While many classical quickest change detection methods can be extended from one-dimensional to any K-dimensional, their performances are rather poor when monitoring large K of data streams. This motives us to investigate the effects of dimensionality on the performance of quickest change detection methods. We found out through theoretical analysis that the classical quickest change detection methods often over-emphasize the first-order term of the detection delays and overlook the second-order terms of the detection delays, where the latter often increases linearly as a function of the dimension K. When K is large (e.g., hundreds), the second-order term of the detection delay will likely be comparable to the first-order term, which implies that the nice first-order asymptotic optimality properties have little practical meaning for large K. We propose a novel approach to lessen the dimensionality effects by introducing some shrinkage estimators of the unknown post-change parameters. In addition, we also illustrate the challenge of Monte Carlo simulation of the average run length to false alarm in the context of online monitoring large-scale data streams. In Chapter 2, we consider the problem of monitoring multichannel profiles that has important applications in manufacturing systems improvement. A concrete motivating example of this work is from a forging process, in which multichannel load profiles measure exerted forces in each column of the forging machine. While various methods have been developed for univariate profile monitoring, they often cannot easily be extended to multichannel profiles. There are two main challenges when monitoring multichannel profiles. The first one is that profiles are high-dimensional functional data with intrinsic inner- and inter-channel correlations, and the second, probably more fundamental, challenge is that the functional structure of multi-channel profiles might change over time, and thus the dimension reduction method should be capable of taking into account the potential unknown change. We develop a novel thresholded multivariate principal component analysis (PCA) method for multi-channel profile monitoring. Our proposed method consists of two steps of dimension reduction: It first applies the functional PCA to extract a reasonable large number of features under the in-control state, and then uses the shrinkage techniques to functional PCAs to further select significant features capturing profile information in the out-of-control state. The choice of tuning parameter for soft-thresholding is provided based on asymptotic analysis, and extensive simulation studies are conducted to illustrate the efficacy of our proposed methodology. In Chapter 3, we study the problem of global optimization of expensive functions. In modern physical and computer experiments, one often deals with expensive functions in the sense that it may take days or months to evaluate their values at a single input setting. An important problem is how to choose an appropriate setting of the input variables so as to optimize the output. To tackle this question, our proposed method involves two main components: one is the construction of a surrogate model to approximate the true function with much cheaper computation, and the other is the determination of a new input setting for function evaluation based on the surrogate model. After iteratively updating these two components, we optimize the latest surrogate model, which yields the approximation to the optima of the original expensive function. To be specific, we propose an adaptive Radial Basis Function (RBF) based global optimization framework via uncertainty quantification. For the surrogate model, we construct an adaptive RBF-based normal mixture Bayesian surrogate model, where the parameters in the RBFs can be adaptively updated each time a new point is explored. It is crucial to employ the normal mixture Bayesian structure which leads to a more stable surrogate model and avoid over-fitting. Its use can be regarded as a ridge-type regression estimate of model coefficients. For the selection of input setting, we propose a novel criterion to assess the input setting based on the surrogate model, and we choose the inputs that maximize the criterion. Our criterion incorporates the expected improvement (EI) of the function prediction to effectively identify promising areas for the global optima, and its uncertainties to efficiently explore the unknown regions. We conduct numerical studies with standard test functions to understand and compare the empirical performance of our proposed method with a prominent existing method.Ph.D

    INTER-ENG 2020

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    These proceedings contain research papers that were accepted for presentation at the 14th International Conference Inter-Eng 2020 ,Interdisciplinarity in Engineering, which was held on 8–9 October 2020, in Târgu Mureș, Romania. It is a leading international professional and scientific forum for engineers and scientists to present research works, contributions, and recent developments, as well as current practices in engineering, which is falling into a tradition of important scientific events occurring at Faculty of Engineering and Information Technology in the George Emil Palade University of Medicine, Pharmacy Science, and Technology of Târgu Mures, Romania. The Inter-Eng conference started from the observation that in the 21st century, the era of high technology, without new approaches in research, we cannot speak of a harmonious society. The theme of the conference, proposing a new approach related to Industry 4.0, was the development of a new generation of smart factories based on the manufacturing and assembly process digitalization, related to advanced manufacturing technology, lean manufacturing, sustainable manufacturing, additive manufacturing, and manufacturing tools and equipment. The conference slogan was “Europe’s future is digital: a broad vision of the Industry 4.0 concept beyond direct manufacturing in the company”

    Aeronautical engineering: A continuing bibliography with indexes (supplement 322)

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    This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in Oct. 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics
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