Robust ego-motion estimation and 3-D model refinement using surface parallax.

We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse depth map using parametric surface parallax models and brightness derivatives extracted from an image pair. Given a coarse depth map acquired by a range-finder or extracted from a digital elevation map (DEM), ego-motion is estimated by combining a global ego-motion constraint and a local brightness constancy constraint. Using the estimated camera motion and the available depth estimate, motion of the three-dimensional (3-D) points is compensated. We utilize the fact that the resulting surface parallax field is an epipolar field, and knowing its direction from the previous motion estimates, estimate its magnitude and use it to refine the depth map estimate. The parallax magnitude is estimated using a constant parallax model (CPM) which assumes a smooth parallax field and a depth based parallax model (DBPM), which models the parallax magnitude using the given depth map. We obtain confidence measures for determining the accuracy of the estimated depth values which are used to remove regions with potentially incorrect depth estimates for robustly estimating ego-motion in subsequent iterations. Experimental results using both synthetic and real data (both indoor and outdoor sequences) illustrate the effectiveness of the proposed algorithm.     

Pseudoelasticity of Metal Nanoparticles Is Caused by Their Ultrahigh Strength

An assembly of hemispherical Ag nanoparticles is prepared by solid‐state dewetting of thin Ag film deposited on the sapphire substrate. The in situ nanomechanical compression testing of the particles with a flat diamond punch inside the scanning electron microscope demonstrates the deformation behavior typical for the nucleation‐controlled plasticity: high elastic deformation followed by an abrupt particles collapse. The latter is associated with the dislocations nucleation in otherwise pristine particle. The average contact pressure in the contact zone at the onset of dislocation‐controlled plasticity is about 8 GPa, and does not depend on particle size. This observation supports the hypothesis that the pseudoelasticity of much smaller Ag nanoparticles is intrinsically related to their ultrahigh strength. A stress‐induced diffusion along the particle–substrate and particle–punch interfaces is identified as a factor controlling the pseudoelastic deformation. The corresponding diffusion model allows estimating the room‐temperature self‐diffusion coefficient of Ag along the Ag–W and Ag–zirconia interfaces, which is quite close to the estimated value of the grain boundary self‐diffusion coefficient in Ag. Based on this finding, the map of pseudoelastic deformation of crystalline materials is proposed.     

An efficient and intelligent routing strategy for vehicular delay tolerant networks

The vehicular delay-tolerant network is the real-life application based area of Delay tolerant network where communication takes place using vehicular nodes and roadside units. The topology used in vehicular networks is highly dynamic by architecture due to the use of moving vehicular nodes. It operates in such a scenario where a direct path between source and destination remains absent on the most piece of the time. In case of non-existence of connected path vehicular delay-tolerant network works opportunistically and uses the same store, carry, and forward paradigm as Delay Tolerant Network. However, the routing protocols designed for vehicular delay-tolerant network faces crucial challenges like inadequate relay node, incomplete data transfer, a large number of packet drop, and uncertain delivery time. In this research paper, we propose a novel routing strategy for the vehicular delay-tolerant network. The proposed routing strategy selects efficient vehicular relay node for complete packet transfer and intelligently reduces the packet drop for timely packet delivery. We implement the proposed routing strategy in the ONE simulator; the ONE simulator provides an opportunistic environment for nodes. We analyze the performance of the proposed strategy under various simulations results using different parameters. The results show that the proposed strategy outperforms standard routing protocols in terms of considered parameters and provide an efficient solution for the problem of disconnection.

     

Design and development of a machine vision system using artificial neural network-based algorithm for automated coal characterization

Coal is heterogeneous in nature,and thus the characterization of coal is essential before its use for a specific purpose.Thus,the current study aims to develop ...     

Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523–1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.

An Efficient Data Delivery Scheme in WBAN to Deal with Shadow Effect due to Postural Mobility

The body movement and change in posture exhibit high mobility in sensor nodes which causes shadowing in the Wireless Body Area Network (WBAN). Due to this, the connectivity between the nodes in WBAN is affected which further causes failure in data delivery. This article presents a MAC protocol in WBAN to deal with the problem of data delivery due to body movement and postural mobility. It uses an Improved Initial Centroid K-means clustering technique for classification of various human body postures followed by back propagation neural network as a classifier to recognize human body posture. This article proposes a posture aware dynamic data delivery (PA-DDD) protocol to deliver data dynamically. The PA-DDD protocol can be used under varying speed walking scenario. The simulation results show that it prolongs the network lifetime and is energy efficient.

     

Pressure Drop Studies on Flow of Viscoelastic Fluid Through a Packed Bed

In the present study, pressure drop-flow rate behavior for the flow of viscoelastic fluid through porous media has been investigated. Aqueous solutions of polyacrylamide (PAM) and water in the concentration range of 0.02 to 0.1% wt/vol were used to elucidate the effect of fluid elasticity on bed pressure drop. Based on the observed data, the existing pore model was extended to predict the bed pressure drop for viscoelastic fluid flowing through a porous media. A statistical comparison between the existing models and the present model was made. The proposed correlation based on modified pore model predicts the data well to within a reasonable accuracy of ±10% with arithmetic relative error (%ARE) and mean relative quadratic error (MRQE) of 8.3% and 0.122, respectively.     

Bone cell–materials interaction on alumina ceramics with different grain sizes

The objective of this work was to study adhesion, proliferation and differentiation of osteoblast cells (OPC1) on alumina ceramic, a bio-inert material. Alumina ceramic with different average grain sizes, 1 μm and 12 μm, respectively, were used in as-prepared condition without any grinding and polishing to understand the influence of grain size on cell–material interactions. Scanning electron microscopy and confocal imaging were used to study attachment, adhesion and differentiation of OPC1 cells. Cells attached, proliferated and differentiated well on both the substrates. Adhesion of cells, as assessed by observing the production of vinculin, was found to be a consistent phenomenon on both the substrates. On day 5 of cell culture, significant cell-attachment was observed and vinculin was detected throughout cytoplasm. MTT assay showed that proliferation of OPC1 cells was consistently higher in the case of 12 μm-alumina. Cells of different morphology, nodular, plate-like as well as elongated, were found to get anchored at grains, grain boundaries as well as pores. On day 16, there were clear signs of mineralization as well. Over all, alumina with average grain size of 12 μm showed better cell-attachment, growth and differentiation compared to 1 μm grain size samples.     

Scalable approach to uncertainty quantification and robust design of interconnected dynamical systems

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks.