955 resultados para visual pop-out


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The primary role of substituted side chains in organic semiconductors is to increase their solubility in common organic solvents. In the recent past, many literature reports have suggested that the side chains play a critical role in molecular packing and strongly impact the charge transport properties of conjugated polymers. In this work, we have investigated the influence of side-chains on the charge transport behavior of a novel class of diketopyrrolopyrrole (DPP) based alternating copolymers. To investigate the role of side-chains, we prepared four diketopyrrolopyrrole-diketopyrrolopyrrole (DPP-DPP) conjugated polymers with varied side-chains and carried out a systematic study of thin film microstructure and charge transport properties in polymer thin-film transistors (PTFTs). Combining results obtained from grazing incidence X-ray diffraction (GIXD) and charge transport properties in PTFTs, we conclude side-chains have a strong influence on molecular packing, thin film microstructure, and the charge carrier mobility of DPP-DPP copolymers. However, the influence of side-chains on optical properties was moderate. The preferential ``edge-on'' packing and dominant n-channel behavior with exceptionally high field-effect electron mobility values of >1 cm(2) V-1 s(-1) were observed by incorporating hydrophilic (triethylene glycol) and hydrophobic side-chains of alternate DPP units. In contrast moderate electron and hole mobilities were observed by incorporation of branched hydrophobic side-chains. This work clearly demonstrates that the subtle balance between hydrophobicity and hydrophilicity induced by side-chains is a powerful strategy to alter the molecular packing and improve the ambipolar charge transport properties in DPP-DPP based conjugated polymers. Theoretical analysis supports the conclusion that the side-chains influence polymer properties through morphology changes, as there is no effect on the electronic properties in the gas phase. The exceptional electron mobility is at least partially a result of the strong intramolecular conjugation of the donor and acceptor as evidenced by the unusually wide conduction band of the polymer.

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This paper presents the shaking table studies to investigate the factors that influence the liquefaction resistance of sand. A uniaxial shaking table with a perspex model container was used for the model tests, and saturated sand beds were prepared using wet pluviation method. The models were subjected to horizontal base shaking, and the variation of pore water pressure was measured. Three series of tests varying the acceleration and frequency of base shaking and density of the soil were carried out on sand beds simulating free field condition. Liquefaction was visualized in some model tests, which was also established through pore water pressure ratios. Effective stress was calculated at the point of pore water pressure measurement, and the number of cycles required to liquefy the sand bed were estimated and matched with visual observations. It was observed that there was a gradual variation in pore water pressure with change in base acceleration at a given frequency of shaking. The variation in pore water pressure is not significant for the range of frequency used in the tests. The frequency of base shaking at which the sand starts to liquefy when the sand bed is subjected to any specific base acceleration depends on the density of sand, and it was observed that the sand does not liquefy at any other frequency less than this. A substantial improvement in liquefaction resistance of the sand was observed with the increase in soil density, inferring that soil densification is a simple technique that can be applied to increase the liquefaction resistance.

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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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Designing a robust algorithm for visual object tracking has been a challenging task since many years. There are trackers in the literature that are reasonably accurate for many tracking scenarios but most of them are computationally expensive. This narrows down their applicability as many tracking applications demand real time response. In this paper, we present a tracker based on random ferns. Tracking is posed as a classification problem and classification is done using ferns. We used ferns as they rely on binary features and are extremely fast at both training and classification as compared to other classification algorithms. Our experiments show that the proposed tracker performs well on some of the most challenging tracking datasets and executes much faster than one of the state-of-the-art trackers, without much difference in tracking accuracy.

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Results from interface shear tests on sand-geosynthetic interfaces are examined in light of surface roughness of the interacting geosynthetic material. Three different types of interface shear tests carried out in the frame of direct shear-test setup are compared to understand the effect of parameters like box fixity and symmetry on the interface shear characteristics. Formation of shear bands close to the interface is visualized in the tests and the bands are analyzed using image-segmentation techniques in MATLAB. A woven geotextile with moderate roughness and a geomembrane with minimal roughness are used in the tests. The effect of surface roughness of the geosynthetic material on the formation of shear bands, movement of sand particles, and interface shear parameters are studied and compared through visual observations, image analyses, and image-segmentation techniques.

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Objective: The aim of this study is to validate the applicability of the PolyVinyliDene Fluoride (PVDF) nasal sensor to assess the nasal airflow, in healthy subjects and patients with nasal obstruction and to correlate the results with the score of Visual Analogue Scale (VAS). Methods: PVDF nasal sensor and VAS measurements were carried out in 50 subjects (25-healthy subjects and 25 patients). The VAS score of nasal obstruction and peak-to-peak amplitude (Vp-p) of nasal cycle measured by PVDF nasal sensors were analyzed for right nostril (RN) and left nostril (LN) in both the groups. Spearman's rho correlation was calculated. The relationship between PVDF nasal sensor measurements and severity of nasal obstruction (VAS score) were assessed by ANOVA. Results: In healthy group, the measurement of nasal airflow by PVDF nasal sensor for RN and LN were found to be 51.14 +/- 5.87% and 48.85 +/- 5.87%, respectively. In patient group, PVDF nasal sensor indicated lesser nasal airflow in the blocked nostrils (RN: 23.33 +/- 10.54% and LN: 32.24 +/- 11.54%). Moderate correlation was observed in healthy group (r = 0.710, p < 0.001 for RN and r = 0.651, p < 0.001 for LN), and moderate to strong correlation in patient group (r = 0.751, p < 0.01 for RN and r = 0.885, p < 0.0001 for LN). Conclusion: PVDF nasal sensor method is a newly developed technique for measuring the nasal airflow. Moderate to strong correlation was observed between PVDF nasal sensor data and VAS scores for nasal obstruction. In our present study, PVDF nasal sensor technique successfully differentiated between healthy subjects and patients with nasal obstruction. Additionally, it can also assess severity of nasal obstruction in comparison with VAS. Thus, we propose that the PVDF nasal sensor technique could be used as a new diagnostic method to evaluate nasal obstruction in routine clinical practice. (C) 2015 Elsevier Inc. All rights reserved.

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The room-temperature synthesis of mono-dispersed gold nanoparticles, by the reduction of chlorauric acid (HAuCl4) with tannic acid as the reducing and stabilizing agent, is carried out in a microchannel. The microchannel is fabricated with one soft wall, so that there is a spontaneous transition to turbulence, and thereby enhanced mixing, when the flow Reynolds number increases beyond a critical value. The objective of the study is to examine whether the nanoparticle size and polydispersity can be modified by enhancing the mixing in the microchannel device. The flow rates are varied in order to study nanoparticle formation both in laminar flow and in the chaotic flow after transition, and the molar ratio of the chlorauric acid to tannic acid is also varied to study the effect of molar ratio on nanoparticle size. The formation of gold nanoparticles is examined by UV-visual spectroscopy and the size distribution is determined using scanning electron microscopy. The synthesized nanoparticles size decreases from a parts per thousand yen6 nm to a parts per thousand currency sign4 nm when the molar ratio of chlorauric acid to tannic acid is increased from 1 to 20. It is found that there is no systematic variation of nanoparticle size with flow velocity, and the nanoparticle size is not altered when the flow changes from laminar to turbulent. However, the standard deviation of the size distribution decreases by about 30% after transition, indicating that the enhanced mixing results in uniformity of particle size.

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The performance of two curved beam finite element models based on coupled polynomial displacement fields is investigated for out-of-plane vibration of arches. These two-noded beam models employ curvilinear strain definitions and have three degrees of freedom per node namely, out-of-plane translation (v), out-of-plane bending rotation (theta(z)) and torsion rotation (theta(s)). The coupled polynomial interpolation fields are derived independently for Timoshenko and Euler-Bernoulli beam elements using the force-moment equilibrium equations. Numerical performance of these elements for constrained and unconstrained arches is compared with the conventional curved beam models which are based on independent polynomial fields. The formulation is shown to be free from any spurious constraints in the limit of `flexureless torsion' and `torsionless flexure' and hence devoid of flexure and torsion locking. The resulting stiffness and consistent mass matrices generated from the coupled displacement models show excellent convergence of natural frequencies in locking regimes. The accuracy of the shear flexibility added to the elements is also demonstrated. The coupled polynomial models are shown to perform consistently over a wide range of flexure-to-shear (EI/GA) and flexure-to-torsion (EI/GJ) stiffness ratios and are inherently devoid of flexure, torsion and shear locking phenomena. (C) 2015 Elsevier B.V. All rights reserved.

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Measurement of out-of-plane linear motion with high precision and bandwidth is indispensable for development of precision motion stages and for dynamic characterization of mechanical structures. This paper presents an optical beam deflection (OBD) based system for measurement of out-of-plane linear motion for fully reflective samples. The system also achieves nearly zero cross-sensitivity to angular motion, and a large working distance. The sensitivities to linear and angular motion are analytically obtained and employed to optimize the system design. The optimal shot-noise limited resolution is shown to be less than one angstrom over a bandwidth in excess of 1 kHz. Subsequently, the system is experimentally realized and the sensitivities to out-of-plane motions are calibrated using a novel strategy. The linear sensitivity is found to be in agreement with theory. The angular sensitivity is shown to be over 7.5-times smaller than that of conventional OBD. Finally, the measurement system is employed to measure the transient response of a piezo-positioner, and, with the aid of an open-loop controller, reduce the settling time by about 90%. It is also employed to operate the positioner in closed-loop and demonstrate significant minimization of hysteresis and positioning error.

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We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes.

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This paper presents a novel coarse-to-fine global localization approach that is inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by SIFT descriptors are used as natural land-marks. These descriptors are indexed into two databases: an inverted index and a location database. The inverted index is built based on a visual vocabulary learned from the feature descriptors. In the location database, each location is directly represented by a set of scale invariant descriptors. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the inverted index is fast but not accurate enough; whereas localization from the location database using voting algorithm is relatively slow but more accurate. The combination of coarse and fine stages makes fast and reliable localization possible. In addition, if necessary, the localization result can be verified by epipolar geometry between the representative view in database and the view to be localized. Experimental results show that our approach is efficient and reliable. ©2005 IEEE.