965 resultados para ITS applications


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A model for the crystallography and morphology of diffusion-controlled phase transformations - edge-to-edge matching - has been used to predict the orientation relationships (OR) and habit planes of precipitates Mg17Al12 in Mg-Al alloy, Mg24Y5 in Mg-Y alloy and alpha-Mn in Mg-Mn alloy. Based on the crystal structures and lattice parameters only, the model predicts that the possible ORs between Mg17Al12 and Mg matrix are the near Burgers OR, the Potter OR, the Gjonnes-Ostmoe OR and the Crawley OR. In the Mg-Y alloy, the OR between Mg24Y5 precipitates and the Mg matrix is predicted to be the Burgers OR only. The model also predicts that there are no reproducible ORs between alpha-Mn and Mg in the Mg-Mn alloy. Combining the edge-to-edge matching model and W. Zhang's Deltag approach, the habit plane and side facets of the precipitate for each OR can be determined. All the predicted ORs and the corresponding habit planes in Mg-Al and Mg-Y alloys agree very well with the experimental results. (C) 2004 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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Due to its wide applicability and ease of use, the analytic hierarchy process (AHP) has been studied extensively for the last 20 years. Recently, it is observed that the focus has been confined to the applications of the integrated AHPs rather than the stand-alone AHP. The five tools that commonly combined with the AHP include mathematical programming, quality function deployment (QFD), meta-heuristics, SWOT analysis, and data envelopment analysis (DEA). This paper reviews the literature of the applications of the integrated AHPs. Related articles appearing in the international journals from 1997 to 2006 are gathered and analyzed so that the following three questions can be answered: (i) which type of the integrated AHPs was paid most attention to? (ii) which area the integrated AHPs were prevalently applied to? (iii) is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the integrated AHPs are better than the stand-alone AHP, but also aids the researchers and decision makers in applying the integrated AHPs effectively.

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This thesis describes an investigation into methods for controlling the mode distribution in multimode optical fibres. The major contributions presented in this thesis are summarised below. Emerging standards for Gigabit Ethernet transmission over multimode optical fibre have led to a resurgence of interest in the precise control, and specification, of modal launch conditions. In particular, commercial LED and OTDR test equipment does not, in general, comply with these standards. There is therefore a need for mode control devices, which can ensure compliance with the standards. A novel device consisting of a point-load mode-scrambler in tandem with a mode-filter is described in this thesis. The device, which has been patented, may be tuned to achieve a wide range of mode distributions and has been implemented in a ruggedised package for field use. Various other techniques for mode control have been described in this work, including the use of Long Period Gratings and air-gap mode-filters. Some of the methods have been applied to other applications, such as speckle suppression and in sensor technology. A novel, self-referencing, sensor comprising two modal groups in the Mode Power Distribution has been designed and tested. The feasibility of a two-channel Mode Group Diversity Multiplexed system has been demonstrated over 985m. A test apparatus for measuring mode distribution has been designed and constructed. The apparatus consists of a purpose-built video microscope, and comprehensive control and analysis software written in Visual Basic. The system may be fitted with a Silicon camera or an InGaAs camera, for measurement in the 850nm and 130nm transmission windows respectively. A limitation of the measurement method, when applied to well-filled fibres, has been identified and an improvement to the method has been proposed, based on modelled Laguerre Gauss field solutions.

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Radio Frequency Identification (RFID) has been identified as a crucial technology for the modern 21st century knowledge-based economy. Some businesses have realised benefits of RFID adoption through improvements in operational efficiency, additional cost savings, and opportunities for higher revenues. RFID research in warehousing operations has been less prominent than in other application domains. To investigate how RFID technology has had an impact in warehousing, a comprehensive analysis of research findings available from articles through leading scientific article databases has been conducted. Articles from years 1995 to 2010 have been reviewed and analysed with respect to warehouse operations, RFID application domains, benefits achieved and obstacles encountered. Four discussion topics are presented covering RFID in warehousing focusing on its applications, perceived benefits, obstacles to its adoption and future trends. This is aimed at elucidating the current state of RFID in the warehouse and providing insights for researchers to establish new research agendas and for practitioners to consider and assess the adoption of RFID in warehousing functions. © 2013 Elsevier B.V.

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This chapter provides the theoretical foundation and background on Data Envelopment Analysis (DEA) method and some variants of basic DEA models and applications to various sectors. Some illustrative examples, helpful resources on DEA, including DEA software package, are also presented in this chapter. DEA is useful for measuring relative efficiency for variety of institutions and has its own merits and limitations. This chapter concludes that DEA results should be interpreted with much caution to avoid giving wrong signals and providing inappropriate recommendations.

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ACM Computing Classification System (1998): E.4.

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2002 Mathematics Subject Classification: 35L05, 34L15, 35D05, 35Q53

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MSC 2010: 35R11, 44A10, 44A20, 26A33, 33C45

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The objectives of this research are to analyze and develop a modified Principal Component Analysis (PCA) and to develop a two-dimensional PCA with applications in image processing. PCA is a classical multivariate technique where its mathematical treatment is purely based on the eigensystem of positive-definite symmetric matrices. Its main function is to statistically transform a set of correlated variables to a new set of uncorrelated variables over $\IR\sp{n}$ by retaining most of the variations present in the original variables.^ The variances of the Principal Components (PCs) obtained from the modified PCA form a correlation matrix of the original variables. The decomposition of this correlation matrix into a diagonal matrix produces a set of orthonormal basis that can be used to linearly transform the given PCs. It is this linear transformation that reproduces the original variables. The two-dimensional PCA can be devised as a two successive of one-dimensional PCA. It can be shown that, for an $m\times n$ matrix, the PCs obtained from the two-dimensional PCA are the singular values of that matrix.^ In this research, several applications for image analysis based on PCA are developed, i.e., edge detection, feature extraction, and multi-resolution PCA decomposition and reconstruction. ^

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The investigations of human mitochondrial DNA (mtDNA) have considerably contributed to human evolution and migration. The Middle East is considered to be an essential geographic area for human migrations out of Africa since it is located at the crossroads of Africa, and the rest of the world. United Arab Emirates (UAE) population inhabits the eastern part of Arabian Peninsula and was investigated in this study. Published data of 18 populations were included in the statistical analysis. The diversity indices showed (1) high genetic distance among African populations and (2) high genetic distance between African populations and non-African populations. Asian populations clustered together in the NJ tree between the African and European populations. MtDNA haplotypes database of the UAE population was generated. By incorporating UAE mtDNA dataset into the existing worldwide mtDNA database, UAE Forensic Laboratories will be able to analyze future mtDNA evidence in a more significant and consistent manner. ^

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The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

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Digital Image Processing is a rapidly evolving eld with growing applications in Science and Engineering. It involves changing the nature of an image in order to either improve its pictorial information for human interpretation or render it more suitable for autonomous machine perception. One of the major areas of image processing for human vision applications is image enhancement. The principal goal of image enhancement is to improve visual quality of an image, typically by taking advantage of the response of human visual system. Image enhancement methods are carried out usually in the pixel domain. Transform domain methods can often provide another way to interpret and understand image contents. A suitable transform, thus selected, should have less computational complexity. Sequency ordered arrangement of unique MRT (Mapped Real Transform) coe cients can give rise to an integer-to-integer transform, named Sequency based unique MRT (SMRT), suitable for image processing applications. The development of the SMRT from UMRT (Unique MRT), forward & inverse SMRT algorithms and the basis functions are introduced. A few properties of the SMRT are explored and its scope in lossless text compression is presented.

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Background. Tremendous advances in biomaterials science and nanotechnologies, together with thorough research on stem cells, have recently promoted an intriguing development of regenerative medicine/tissue engineering. The nanotechnology represents a wide interdisciplinary field that implies the manipulation of different materials at nanometer level to achieve the creation of constructs that mimic the nanoscale-based architecture of native tissues. Aim. The purpose of this article is to highlight the significant new knowledges regarding this matter. Emerging acquisitions. To widen the range of scaffold materials resort has been carried out to either recombinant DNA technology-generated materials, such as a collagen-like protein, or the incorporation of bioactive molecules, such as RDG (arginine-glycine-aspartic acid), into synthetic products. Both the bottom-up and the top-down fabrication approaches may be properly used to respectively obtain sopramolecular architectures or, instead, micro-/nanostructures to incorporate them within a preexisting complex scaffold construct. Computer-aided design/manufacturing (CAD/CAM) scaffold technique allows to achieve patient-tailored organs. Stem cells, because of their peculiar properties - ability to proliferate, self-renew and specific cell-lineage differentiate under appropriate conditions - represent an attractive source for intriguing tissue engineering/regenerative medicine applications. Future research activities. New developments in the realization of different organs tissue engineering will depend on further progress of both the science of nanoscale-based materials and the knowledge of stem cell biology. Moreover the in vivo tissue engineering appears to be the logical step of the current research.

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Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

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Compressed covariance sensing using quadratic samplers is gaining increasing interest in recent literature. Covariance matrix often plays the role of a sufficient statistic in many signal and information processing tasks. However, owing to the large dimension of the data, it may become necessary to obtain a compressed sketch of the high dimensional covariance matrix to reduce the associated storage and communication costs. Nested sampling has been proposed in the past as an efficient sub-Nyquist sampling strategy that enables perfect reconstruction of the autocorrelation sequence of Wide-Sense Stationary (WSS) signals, as though it was sampled at the Nyquist rate. The key idea behind nested sampling is to exploit properties of the difference set that naturally arises in quadratic measurement model associated with covariance compression. In this thesis, we will focus on developing novel versions of nested sampling for low rank Toeplitz covariance estimation, and phase retrieval, where the latter problem finds many applications in high resolution optical imaging, X-ray crystallography and molecular imaging. The problem of low rank compressive Toeplitz covariance estimation is first shown to be fundamentally related to that of line spectrum recovery. In absence if noise, this connection can be exploited to develop a particular kind of sampler called the Generalized Nested Sampler (GNS), that can achieve optimal compression rates. In presence of bounded noise, we develop a regularization-free algorithm that provably leads to stable recovery of the high dimensional Toeplitz matrix from its order-wise minimal sketch acquired using a GNS. Contrary to existing TV-norm and nuclear norm based reconstruction algorithms, our technique does not use any tuning parameters, which can be of great practical value. The idea of nested sampling idea also finds a surprising use in the problem of phase retrieval, which has been of great interest in recent times for its convex formulation via PhaseLift, By using another modified version of nested sampling, namely the Partial Nested Fourier Sampler (PNFS), we show that with probability one, it is possible to achieve a certain conjectured lower bound on the necessary measurement size. Moreover, for sparse data, an l1 minimization based algorithm is proposed that can lead to stable phase retrieval using order-wise minimal number of measurements.