996 resultados para variable interest entity
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Background: There has been growing interest in integrative taxonomy that uses data from multiple disciplines for species delimitation. Typically, in such studies, monophyly is taken as a proxy for taxonomic distinctiveness and these units are treated as potential species. However, monophyly could arise due to stochastic processes. Thus here, we have employed a recently developed tool based on coalescent approach to ascertain the taxonomic distinctiveness of various monophyletic units. Subsequently, the species status of these taxonomic units was further tested using corroborative evidence from morphology and ecology. This inter-disciplinary approach was implemented on endemic centipedes of the genus Digitipes (Attems 1930) from the Western Ghats (WG) biodiversity hotspot of India. The species of the genus Digitipes are morphologically conserved, despite their ancient late Cretaceous origin. Principal Findings: Our coalescent analysis based on mitochondrial dataset indicated the presence of nine putative species. The integrative approach, which includes nuclear, morphology, and climate datasets supported distinctiveness of eight putative species, of which three represent described species and five were new species. Among the five new species, three were morphologically cryptic species, emphasizing the effectiveness of this approach in discovering cryptic diversity in less explored areas of the tropics like the WG. In addition, species pairs showed variable divergence along the molecular, morphological and climate axes. Conclusions: A multidisciplinary approach illustrated here is successful in discovering cryptic diversity with an indication that the current estimates of invertebrate species richness for the WG might have been underestimated. Additionally, the importance of measuring multiple secondary properties of species while defining species boundaries was highlighted given variable divergence of each species pair across the disciplines.
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Context-aware computing is useful in providing individualized services focusing mainly on acquiring surrounding context of user. By comparison, only very little research has been completed in integrating context from different environments, despite of its usefulness in diverse applications such as healthcare, M-commerce and tourist guide applications. In particular, one of the most important criteria in providing personalized service in a highly dynamic environment and constantly changing user environment, is to develop a context model which aggregates context from different domains to infer context of an entity at the more abstract level. Hence, the purpose of this paper is to propose a context model based on cognitive aspects to relate contextual information that better captures the observation of certain worlds of interest for a more sophisticated context-aware service. We developed a C-IOB (Context-Information, Observation, Belief) conceptual model to analyze the context data from physical, system, application, and social domains to infer context at the more abstract level. The beliefs developed about an entity (person, place, things) are primitive in most theories of decision making so that applications can use these beliefs in addition to history of transaction for providing intelligent service. We enhance our proposed context model by further classifying context information into three categories: a well-defined, a qualitative and credible context information to make the system more realistic towards real world implementation. The proposed model is deployed to assist a M-commerce application. The simulation results show that the service selection and service delivery of the system are high compared to traditional system.
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Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.
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Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.
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In this brief, variable structure systems theory based guidance laws, to intercept maneuvering targets at a desired impact angle, are presented. Choosing the missile's lateral acceleration (latax) to enforce sliding mode, which is the principal operating mode of variable structure systems, on a switching surface defined by the line-of-sight angle leads to a guidance law that allows the achievement of the desired terminal impact angle. As will be shown, this law does not ensure interception for all states of the missile and the target during the engagement. Hence, additional switching surfaces are designed and a switching logic is developed that allows the latax to switch between enforcing sliding mode on one of these surfaces so that the target can be intercepted at the desired impact angle. The guidance laws are designed using nonlinear engagement dynamics for the general case of a maneuvering target.
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Variable speed operation of microhydro power plants is gaining popularity due to the benefits that accrue from their use and the development of suitable generator control systems. This paper highlights the benefits of variable speed systems over conventional systems and also proposes a simple emulator for hydraulic turbines that operate in variable speed fixed flow rate mode. The emulator consists of an uncontrolled separately excited DC motor with additional resistors and has performance characteristics similar to that of the hydraulic turbine.
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This paper presents a technique to vary the electric field within a cylindrical ion trap (CIT) mass spectrometer while it is in operation. In this technique, the electrodes of the CIT are split into number of mini-electrodes and different voltages are applied to these split-electrodes to achieve the desired field. In our study we have investigated two geometries of the split-electrode CIT. In the first, we retain the flat endcap electrodes of the CIT but split the ring electrode into five mini-rings. In the second configuration, we split the ring electrode of the CIT into three mini-rings and also divide the endcaps into two mini-discs. By applying different potentials to the mini-rings and mini-discs of these geometries we have shown that the field within the trap can be optimized to desired values. In our study, two different types of fields were targeted. In the first, potentials were adjusted to obtain a linear electric field and, in the second, a controlled higher order even multipole field was obtained by adjusting the potential. We have shown that the different potentials required can be derived from a single RF generator by connecting appropriate capacitor terminations to split electrodes. The field within the trap can be modified by changing the values of the external capacitors. (C) 2013 Elsevier B.V. All rights reserved.
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Voltage Source Inverter (VSI) fed induction motors are widely used in variable speed applications. For inverters using fixed switching frequency PWM, the output harmonic spectra are located at a few discrete frequencies. The ac motordrives powered by these inverters cause acoustic noise. This paper proposes a new variable switching frequency pwm technique and compares its performance with constant switching frequency pwm technique. It is shown that the proposed technique leads to spread spectra of voltages and currents. Also this technique ensures that no lower order harmonics are present and the current THD is comparable to that of fixed switching frequency PWM and is even better for higher modulation indices.
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This article describes the determination of the internal structure of heterogeneous nanoparticle systems including inverted core-shell (CdS core and CdSe shell) and alloyed (CdSeS) quantum dots using depth-resolved, variable-energy X-ray photoelectron spectroscopy (XPS). A unique feature of this work is the combination of photoelectron spectroscopy performed at lower X-ray energies (400-700 eV), to achieve surface sensitivity, with bulk sensitive measurements at high photon energies (>2000 eV), thereby providing detailed information about the whole nanoparticle structure with a great accuracy. The use of high photon energies furthermore allows us to investigate nanoparticles much larger than those studied thus far. This capability is a consequence of the much-increased mean free path of the photoelectron achieved at high excitation energies. Our results show that the actual structures of the synthesized nanoparticles are considerably different from the nominal, targeted structures, which can be post facto rationalized in terms of the reactivity of different constituents.
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Regions in video streams attracting human interest contribute significantly to human understanding of the video. Being able to predict salient and informative Regions of Interest (ROIs) through a sequence of eye movements is a challenging problem. Applications such as content-aware retargeting of videos to different aspect ratios while preserving informative regions and smart insertion of dialog (closed-caption text) into the video stream can significantly be improved using the predicted ROIs. We propose an interactive human-in-the-loop framework to model eye movements and predict visual saliency into yet-unseen frames. Eye tracking and video content are used to model visual attention in a manner that accounts for important eye-gaze characteristics such as temporal discontinuities due to sudden eye movements, noise, and behavioral artifacts. A novel statistical-and algorithm-based method gaze buffering is proposed for eye-gaze analysis and its fusion with content-based features. Our robust saliency prediction is instantiated for two challenging and exciting applications. The first application alters video aspect ratios on-the-fly using content-aware video retargeting, thus making them suitable for a variety of display sizes. The second application dynamically localizes active speakers and places dialog captions on-the-fly in the video stream. Our method ensures that dialogs are faithful to active speaker locations and do not interfere with salient content in the video stream. Our framework naturally accommodates personalisation of the application to suit biases and preferences of individual users.
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Composite laminates are prone to delamination. Implementation of delamination in the Carrera Unified Formulation frame work using nine noded quadrilateral MITC9 element is discussed in this article. MITC9 element is devoid of shear locking and membrane locking. Delaminated as well as healthy structure is analyzed for free mode vibration. The results from the present work are compared with the available experimental or/and research article or/and the three dimensional finite element simulations. The effect of different kinds and different percentages of area of delamination on the first three natural frequencies of the structure is discussed. The presence of open-mode delamination mode shape for large delaminations within the first three natural frequencies is discussed. Also, the switching of places between the second bending mode, with that of the first torsional mode frequency is discussed. Results obtained from different ordered theories are compared in the presence of delamination. Advantage of layerwise theories as compared to equivalent single layer theories for very large delaminations is stated. The effect of different kinds of delamination and their effect on the second bending and first torsional mode shape is discussed. (C) 2014 Elsevier Ltd. All rights reserved.
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Optical emission from emitters strongly interacting among themselves and also with other polarizable matter in close proximity has been approximated by emission from independent emitters. This is primarily due to our inability to evaluate the self-energy matrices and radiative properties of the collective eigenstates of emitters in heterogeneous ensembles. A method to evaluate self-energy matrices that is not limited by the geometry and material composition is presented to understand and exploit such collective excitations. Numerical evaluations using this method are used to highlight the significant differences between independent and the collective modes of emission in nanoscale heterostructures. A set of N Lorentz emitters and other polarizable entities is used to represent the coupled system of a generalized geometry in a volume integral approach. Closed form relations between the Green tensors of entity pairs in free space and their correspondents in a heterostructure are derived concisely. This is made possible for general geometries because the global matrices consisting of all free-space Green dyads are subject to conservation laws. The self-energy matrix can then be assembled using the evaluated Green tensors of the heterostructure, but a decomposition of its components into their radiative and nonradiative decay contributions is nontrivial. The relations to compute the observables of the eigenstates (such as quantum efficiency, power/energy of emission, radiative and nonradiative decay rates) are presented. A note on extension of this method to collective excitations, which also includes strong interactions with a surface in the near-field, is added. (C) 2014 Optical Society of America
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A new generator topology for microhydel power plants, capable of unsupervised operation, is proposed. While conventional microhydel plants operate at constant speed with switched ballast loads, the proposed generator, based on the wound rotor induction machine, operates at variable speed and does away with the need for ballast loads. This increases reliability and substantially decreases system costs and setup times. The proposed generator has a simplified decoupled control structure with stator-referenced voltage control similar to a conventional synchronous generator, and rotor-side frequency control that is facilitated by rotating electronics mounted on the rotor. While this paper describes an isolated plant, the topology can also be tailored for distributed generation enabling conversion of the available hydraulic power into useful electrical power when the grid is present, and supplying local loads in the event of grid outage.
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Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.
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Lead tin telluride is one of the well-established thermoelectric materials in the temperature range 350-750 K. In the present study, Pb0.75-xMnxSn0.25Te1.00 alloys with variable manganese (Mn) content were prepared by solid state synthesis and the thermoelectric properties were studied. X-ray diffraction, (XRD) showed that the samples followed Vegard's law, indicating solid solution formation and substitution of Mn at the Pb site. Scanning Electron Microscopy (SEM) showed that the grain sizes varied from <1 mu m to more than 10 mu m and MnTe rich phase was present for higher Mn content. Seebeck coefficient, electrical resistivity and thermal conductivity were measured from room temperature to 720 K. At 300 K, large Seebeck values were obtained, possibly due to increased effective mass on Mn substitution and low carrier concentration of the samples. At higher temperatures, transition from n-type to p-type indicated the presence of thermally generated carriers. Temperature dependent electrical resistivity showed the transition from degenerate to non-degenerate behavior. For thermal conductivity, low values (similar to 1 W/m-K at 300 K) were obtained. At higher temperatures bipolar conduction was observed, in agreement with the Seebeck and resistivity data. Due to low power factor, the maximum thermoelectric figure of merit (zT) was limited to 0.23 at 329 K for the sample with lowest Mn content (x=0.03). (C) 2015 Elsevier Ltd. All rights reserved.