973 resultados para Empirical Comparison


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In this paper, numerical modelling of fracture in concrete using two-dimensional lattice model is presented and also a few issues related to lattice modelling technique applicable to concrete fracture are reviewed. A comparison is made with acoustic emission (AE) events with the number of fractured elements. To implement the heterogeneity of the plain concrete, two methods namely, by generating grain structure of the concrete using Fuller's distribution and the concrete material properties are randomly distributed following Gaussian distribution are used. In the first method, the modelling of the concrete at meso level is carried out following the existing methods available in literature. The shape of the aggregates present in the concrete are assumed as perfect spheres and shape of the same in two-dimensional lattice network is circular. A three-point bend (TPB) specimen is tested in the experiment under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/sec and the fracture process in the same TPB specimen is modelled using regular triangular 2D lattice network. Load versus crack mouth opening isplacement (CMOD) plots thus obtained by using both the methods are compared with experimental results. It was observed that the number of fractured elements increases near the peak load and beyond the peak load. That is once the crack starts to propagate. AE hits also increase rapidly beyond the peak load. It is compulsory here to mention that although the lattice modelling of concrete fracture used in this present study is very similar to those already available in literature, the present work brings out certain finer details which are not available explicitly in the earlier works.

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The effect of solvent on chemical reactivity has generally been explained on the basis of the dielectric constant and viscosity. However a number of spectroscopic studies, including UV-VIS, IR and Raman, has led to numerous empirical parameters to define solvent effect based on either solvating ability or polarity scale. These parameters include solvent polarizability, dipolarity, Lewis acidity and Lewis basicity, E-T(30), pi*, alpha, beta etc. However, from a structural point of view, we can separate solvation as static and dynamic processes. The static solvation basically relates to stabilization of the molecular structure by the solvent to attain the equilibrium structure, both in the intermediate and ground state. Dynamic solvation relates to solvent reorganization-induced dynamics prior to the structural reorganization to reach the equilibrium state. In this paper, we present (a) structural distortions induced by the solvent due to preferential solvation of the triplet excited state, and (b) the importance of dynamic solvation induced by vibronic coupling (pseudo-Jahn-Teller coupling). The examples include the effect of solvent on structure and reactivity of excited states of 2,2,2-trifluoroacetophenone (TFA). Based on the comparison of time resolved resonance Raman (TR3) data of TFA and other substituted acetophenone systems, it was found that change in solvent polarity indeed results in electronic state switching and structural changes in the excited state, which explains the trend in reactivity. Further, a TR3 study of fluoranil (FA) in the triplet excited state in solvents of varying polarities indicates that the structure of FA in the triplet excited state is determined by vibronic coupling effects and thus distorted structure. These experimental results have been well supported by density functional theoretical computational studies.

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Tribology of small inorganic nanoparticles in suspension in a liquid lubricant is often impaired because these particles agglomerate even when organic dispersants are used. In this paper we use lateral force microscopy to study the deformation mechanism and dissipation under traction of two extreme configurations (1) a large MoS2 particle (similar to 20 mu m width) of about 1 mu m height and (2) an agglomerate (similar to 20 mu m width), constituting 50 nm MoS2 crystallites, of about 1 mu m height. The agglomerate records a friction coefficient which is about 5-7 times that of monolithic particle. The paper examines the mechanisms of material removal for both the particles using continuum modeling and microscopy and infers that while the agglomerate response to traction can be accounted for by the bulk mechanical properties of the material, intralayer and interlayer basal planar slips determine the friction and wear of monolithic particles. The results provide a rationale for selection of layered particles, for suspension in liquid lubricants.

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MEG directly measures the neuronal events and has greater temporal resolution than fMRI, which has limited temporal resolution mainly due to the larger timescale of the hemodynamic response. On the other hand fMRI has advantages in spatial resolution, while the localization results with MEG can be ambiguous due to the non-uniqueness of the electromagnetic inverse problem. Thus, these methods could provide complementary information and could be used to create both spatially and temporally accurate models of brain function. We investigated the degree of overlap, revealed by the two imaging methods, in areas involved in sensory or motor processing in healthy subjects and neurosurgical patients. Furthermore, we used the spatial information from fMRI to construct a spatiotemporal model of the MEG data in order to investigate the sensorimotor system and to create a spatiotemporal model of its function. We compared the localization results from the MEG and fMRI with invasive electrophysiological cortical mapping. We used a recently introduced method, contextual clustering, for hypothesis testing of fMRI data and assessed the the effect of neighbourhood information use on the reproducibility of fMRI results. Using MEG, we identified the ipsilateral primary sensorimotor cortex (SMI) as a novel source area contributing to the somatosensory evoked fields (SEF) to median nerve stimulation. Using combined MEG and fMRI measurements we found that two separate areas in the lateral fissure may be the generators for the SEF responses from the secondary somatosensory cortex region. The two imaging methods indicated activation in corresponding locations. By using complementary information from MEG and fMRI we established a spatiotemporal model of somatosensory cortical processing. This spatiotemporal model of cerebral activity was in good agreement with results from several studies using invasive electrophysiological measurements and with anatomical studies in monkey and man concerning the connections between somatosensory areas. In neurosurgical patients, the MEG dipole model turned out to be more reliable than fMRI in the identification of the central sulcus. This was due to prominent activation in non-primary areas in fMRI, which in some cases led to erroneous or ambiguous localization of the central sulcus.

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Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

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Boron Nitride Nanotubes (BNNTs) have alternating boron and nitrogen atoms in graphite like network and are strongly polar in nature due to a large charge on boron and nitrogen atoms. Hence electrostatic interactions are expected to play an important role in determining the elastic properties of BNNTs. In the absence of specific partial atomic charge information for boron and nitrogen, we have studied the elastic properties BNNTs varying the partial atomic charges on boron and nitrogen. We have computed Young modulus (Y) and Shear modulus (G) of BNNT as a function of the tube radius and number of walls using molecular mechanics calculation. Our calculation shows that Young modulus of BNNTs increases with increase in magnitude of the partial atomic charge on B and N and can be larger than the Young modulus of CNTs of same radius. This is in contrast to the earlier finding that CNTs has the largest tensile strength (PRL, 80, 4502, 1998). Shear modulus, on the other hand depends weakly on the magnitude of partial atomic charge and is less than the shear modulus of the CNT. The values obtained for Young modulus and Shear modulus are in excellent agreement with the available experimental results.

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The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country’s Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

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Conjugated polymers are promising materials for electrochromic device technology. Aqueous dispersions of poly(3,4-ethylenedioxythiophene)-(PEDOT) were spin coated onto transparent conducting oxide (TCO) coated glass substrates. A seven-layer electrochromic device was fabricated with the following configuration: glass/transparent conducting oxide (TCO)/PEDOT (main electrochromic layer)/gel electrolyte/prussian blue (counter electrode)/TCO/glass. The device fabricated with counter electrode (Prussian blue) showed a contrast of 18% and without counter electrode showed visible contrast of 5% at 632 nm at a voltage of 1.9 V. The comparison of the device is done in terms of the colouration efficiency of the devices with and without counter electrode.

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In this paper, we study the thermoelectric power under strong magnetic field (TPSM) in quantum dots (QDs) of nonlinear optical, III-V, II-VI, GaP, Ge, Te, Graphite, PtSb2, zerogap, Lead Germanium Telluride, GaSb, stressed materials, Bismuth, IV-VI, II-V, Zinc and Cadmium diphosphides, Bi2Te3 and Antimony respectively. The TPSM in III-V, II-VI, IV-VI, HgTe/CdTe quantum well superlattices with graded interfaces and effective mass superlattices of the same materials together with the quantum dots of aforementioned superlattices have also been investigated in this context on the basis of respective carrier dispersion laws. It has been found that the TPSM for the said quantum dots oscillates with increasing thickness and decreases with increasing electron concentration in various manners and oscillates with film thickness, inverse quantizing magnetic field and impurity concentration for all types of superlattices with two entirely different signatures of quantization as appropriate in respective cases of the aforementioned quantized structures. The well known expression of the TPSM for wide-gap materials has been obtained as special case for our generalized analysis under certain limiting condition, and this compatibility is an indirect test of our generalized formalism. Besides, we have suggested the experimental method of determining the carrier contribution to elastic constants for nanostructured materials having arbitrary dispersion laws.

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EEG recordings are often contaminated with ocular artifacts such as eye blinks and eye movements. These artifacts may obscure underlying brain activity in the electroencephalogram (EEG) data and make the analysis of the data difficult. In this paper, we explore the use of empirical mode decomposition (EMD) based filtering technique to correct the eye blinks and eye movementartifacts in single channel EEG data. In this method, the single channel EEG data containing ocular artifact is segmented such that the artifact in each of the segment is considered as some type of slowly varying trend in the dataand the EMD is used to remove the trend. The filtering is done using partial reconstruction from components of the decomposition. The method is completely data dependent and hence adaptive and nonlinear. Experimental results are provided to check the applicability of the method on real EEG data and the results are quantified using power spectral density (PSD) as a measure. The method has given fairlygood results and does not make use of any preknowledge of artifacts or the EEG data used.

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Inventory management (IM) has a decisive role in the enhancement of manufacturing industry's competitiveness. Therefore, major manufacturing industries are following IM practices with the intention of improving their performance. However, the effort to introduce IM in SMEs is very limited due to lack of initiation, expertise, and financial constraints. This paper aims to provide a guideline for entrepreneurs in enhancing their IM performance, as it presents the results of a survey based study carried out for machine tool Small and Medium Enterprises (SMEs) in Bangalore. Having established the significance of inventory as an input, we probed the relationship between IM performance and economic performance of these SMEs. To the extent possible all the factors of production and performance indicators were deliberately considered in pure economic terms. All economic performance indicators adopted seem to have a positive and significant association with IM performance in SMEs. On the whole, we found that SMEs which are IM efficient are likely to perform better on the economic front also and experience higher returns to scale.

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Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

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Imbalance is not only a direct major cause of downtime in wind turbines, but also accelerates the degradation of neighbouring and downstream components (e.g. main bearing, generator). Along with detection, the imbalance quantification is also essential as some residual imbalance always exist even in a healthy turbine. Three different commonly used sensor technologies (vibration, acoustic emission and electrical measurements) are investigated in this work to verify their sensitivity to different imbalance grades. This study is based on data obtained by experimental tests performed on a small scale wind turbine drive train test-rig for different shaft speeds and imbalance levels. According to the analysis results, electrical measurements seem to be the most suitable for tracking the development of imbalance.