881 resultados para N-based linear spacers


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This report describes a new approach to the problem of scheduling highway construction type projects. The technique can accurately model linear activities and identify the controlling activity path on a linear schedule. Current scheduling practices are unable to accomplish these two tasks with any accuracy for linear activities, leaving planners and manager suspicious of the information they provide. Basic linear scheduling is not a new technique, and many attempts have been made to apply it to various types of work in the past. However, the technique has never been widely used because of the lack of an analytical approach to activity relationships and development of an analytical approach to determining controlling activities. The Linear Scheduling Model (LSM) developed in this report, completes the linear scheduling technique by adding to linear scheduling all of the analytical capabilities, including computer applications, present in CPM scheduling today. The LSM has tremendous potential, and will likely have a significant impact on the way linear construction is scheduled in the future.

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During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

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This paper proposes a three-shot improvement scheme for the hard-decision based method (HDM), an implementation solution for linear decorrelating detector (LDD) in asynchronous DS/CDMA systems. By taking advantage of the preceding (already reconstructed) bit and the matched filter output for the following two bits, the coupling between temporally adjacent bits (TABs), which always exists for asynchronous systems, is greatly suppressed and the performance of the original HDM is substantially improved. This new scheme requires no signaling overhead yet offers nearly the same performance as those more complicated methods. Also, it can easily accommodate the change in the number of active users in the channel, as no symbol/bit grouping is involved. Finally, the influence of synchronisation errors is investigated.

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The synthesis and thermal behavior of the new [Pd(fum)(bipy)] (n) center dot 2nH(2)O (1), [Pd(fum)(bpe)] (n) center dot nH(2)O (2) and [Pd(fum)(pz)] (n) center dot 3nH(2)O (3) {bipy = 4,4'-bipyridine, bpe = 1,2-bis(4-pyridyl)ethene and pz = pyrazine} fumarate complexes are described in this work as well their characterization by IR and (13)C CPMAS NMR spectroscopies. TG curves showed that the compounds released organic ligands and lattice water molecules in the temperature range of 46-491 A degrees C. In all the cases, metallic palladium was identified as the final residue.

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This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

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This paper presents several new families of cumulant-based linear equations with respect to the inverse filter coefficients for deconvolution (equalisation) and identification of nonminimum phase systems. Based on noncausal autoregressive (AR) modeling of the output signals and three theorems, these equations are derived for the cases of 2nd-, 3rd and 4th-order cumulants, respectively, and can be expressed as identical or similar forms. The algorithms constructed from these equations are simpler in form, but can offer more accurate results than the existing methods. Since the inverse filter coefficients are simply the solution of a set of linear equations, their uniqueness can normally be guaranteed. Simulations are presented for the cases of skewed series, unskewed continuous series and unskewed discrete series. The results of these simulations confirm the feasibility and efficiency of the algorithms.

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A bit-level processing (BLP) based linear CDMA detector is derived following the principle of minimum variance distortionless response (MVDR). The combining taps for the MVDR detector are determined from (1) the covariance matrix of the matched filter output, and (2) the corresponding row (or column) of the user correlation matrix. Due to the interference suppression capability of MVDR and the fact that no inversion of the user correlation matrix is involved, the influence of the synchronisation errors is greatly reduced. The detector performance is demonstrated via computer simulations (both synchronisation errors and intercell interference are considered).

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We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways.

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BACKGROUND AND PURPOSE: Functional brain variability has been scarcely investigated in cognitively healthy elderly subjects, and it is currently debated whether previous findings of regional metabolic variability are artifacts associated with brain atrophy. The primary purpose of this study was to test whether there is regional cerebral age-related hypometabolism specifically in later stages of life. MATERIALS AND METHODS: MR imaging and FDG-PET data were acquired from 55 cognitively healthy elderly subjects, and voxel-based linear correlations between age and GM volume or regional cerebral metabolism were conducted by using SPM5 in images with and without correction for PVE. To investigate sex-specific differences in the pattern of brain aging, we repeated the above voxelwise calculations after dividing our sample by sex. RESULTS: Our analysis revealed 2 large clusters of age-related metabolic decrease in the overall sample, 1 in the left orbitofrontal cortex and the other in the right temporolimbic region, encompassing the hippocampus, the parahippocampal gyrus, and the amygdala. The division of our sample by sex revealed significant sex-specific age-related metabolic decrease in the left temporolimbic region of men and in the left dorsolateral frontal cortex of women. When we applied atrophy correction to our PET data, none of the above-mentioned correlations remained significant. CONCLUSIONS: Our findings suggest that age-related functional brain variability in cognitively healthy elderly individuals is largely secondary to the degree of regional brain atrophy, and the findings provide support to the notion that appropriate PVE correction is a key tool in neuroimaging investigations.

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Objective. The purpose of this research was to provide further evidence to demonstrate the precision and accuracy of maxillofacial linear and angular measurements obtained by cone-beam computed tomography (CBCT) images. Study design. The study population consisted of 15 dry human skulls that were submitted to CBCT, and 3-dimensional (3D) images were generated. Linear and angular measurements based on conventional craniometric anatomical landmarks, and were identified in 3D-CBCT images by 2 radiologists twice each independently. Subsequently, physical measurements were made by a third examiner using a digital caliper and a digital goniometer. Results. The results demonstrated no statistically significant difference between inter-and intra-examiner analysis. Regarding accuracy test, no statistically significant differences were found of the comparison between the physical and CBCT-based linear and angular measurements for both examiners (P = .968 and .915, P = .844 and .700, respectively). Conclusions. 3D-CBCT images can be used to obtain dimensionally accurate linear and angular measurements from bony maxillofacial structures and landmarks. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2009; 108: 430-436)

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The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

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Dielectric Elastomers (DE) are incompressible dielectrics which can experience deviatoric (isochoric) finite deformations in response to applied large electric fields. Thanks to the strong electro-mechanical coupling, DE intrinsically offer great potentialities for conceiving novel solid-state mechatronic devices, in particular linear actuators, which are more integrated, lightweight, economic, silent, resilient and disposable than equivalent devices based on traditional technologies. Such systems may have a huge impact in applications where the traditional technology does not allow coping with the limits of weight or encumbrance, and with problems involving interaction with humans or unknown environments. Fields such as medicine, domotic, entertainment, aerospace and transportation may profit. For actuation usage, DE are typically shaped in thin films coated with compliant electrodes on both sides and piled one on the other to form a multilayered DE. DE-based Linear Actuators (DELA) are entirely constituted by polymeric materials and their overall performance is highly influenced by several interacting factors; firstly by the electromechanical properties of the film, secondly by the mechanical properties and geometry of the polymeric frame designed to support the film, and finally by the driving circuits and activation strategies. In the last decade, much effort has been focused in the devolvement of analytical and numerical models that could explain and predict the hyperelastic behavior of different types of DE materials. Nevertheless, at present, the use of DELA is limited. The main reasons are 1) the lack of quantitative and qualitative models of the actuator as a whole system 2) the lack of a simple and reliable design methodology. In this thesis, a new point of view in the study of DELA is presented which takes into account the interaction between the DE film and the film supporting frame. Hyperelastic models of the DE film are reported which are capable of modeling the DE and the compliant electrodes. The supporting frames are analyzed and designed as compliant mechanisms using pseudo-rigid body models and subsequent finite element analysis. A new design methodology is reported which optimize the actuator performances allowing to specifically choose its inherent stiffness. As a particular case, the methodology focuses on the design of constant force actuators. This class of actuators are an example of how the force control could be highly simplified. Three new DE actuator concepts are proposed which highlight the goodness of the proposed method.

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This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

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Two-part tariffs, when used at the retail level, increase efficiency by lowering the price of marginal units. The same potential for higher efficiency exists for two-part tariffs at wholesale level for a given market structure, but the fixed part of the wholesale tariff can negatively affect the latter. In a simulated competition model of next-generation telecommunications access networks that has been calibrated with engineering cost data, we show that the latter effects strongly outweigh the former. That is, substituting a cost-based linear wholesale access tariff with revenue-equivalent two-part tariffs reduces the number of access seekers and therefore leads to higher prices and lower welfare and consumer surplus.

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The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.