Haptic Feedback for Injecting Biological Cells using Miniature Compliant Mechanisms

We present a real-time haptics-aided injection technique for biological cells using miniature compliant mechanisms. Our system consists of a haptic robot operated by a human hand, an XYZ stage for micro-positioning, a camera for image capture, and a polydimethylsiloxane (PDMS) miniature compliant device that serves the dual purpose of an injecting tool and a force-sensor. In contrast to existing haptics-based micromanipulation techniques where an external force sensor is used, we use visually captured displacements of the compliant mechanism to compute the applied and reaction forces. The human hand can feel the magnified manipulation force through the haptic device in real-time while the motion of the human hand is replicated on the mechanism side. The images are captured using a camera at the rate of 30 frames per second for extracting the displacement data. This is used to compute the forces at the rate of 30 Hz. The force computed in this manner is sent at the rate of 1000 Hz to ensure stable haptic interaction. The haptic cell-manipulation system was tested by injecting into a zebrafish egg cell after validating the technique at a size larger than that of the cell.

A DCT Based Filtering of Biomedical Images

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a-priori knowledge about the type of noise corrupting the image and image features. This makes the standard filters to be application and image specific. The most popular filters such as average, Gaussian and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design filters based on discrete cosine transform (DCT) is proposed in this study for optimal medical image filtering. This algorithm exploits the better energy compaction property of DCT and re-arrange these coefficients in a wavelet manner to get the better energy clustering at desired spatial locations. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions.

Total Factor Productivity in Indian Electronic Sector after Liberalisation: Sources and Outcomes

This paper analyses the efficiency and productivity growth of the Electronic Sector of India in the liberalization era since 1991. The study gives an insight into the process of the growth of one of the most upcoming sector of this decade. This sector has experienced a vast structural change along with the changing economic structures in India after liberalisation. With the opening up of this sector to foreign market and incoming of multinational companies, the environment has become highly competitive. The law that operates is that of Darwin’s ‘Survival of the fittest’. Existing industries experience a continuous threat of exit due to entrance of new potential entrants. Thus, it becomes inevitable for the existing industries in this sector to improve productivity growth for their survival. It is thus important to analyze how the industries in this sector have performed over the years and what are the factors that have contributed to the overall output growth.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Andaman Postseismic Deformation Observations: Still Slipping after All These Years?

More than six years after the great (M-w 9.2) Sumatra-Andaman earthquake, postevent processes responsible for relaxation of the coseismic stress change remain controversial. Modeling of Andaman Islands Global Positioning System (GPS) displacements indicated early near-field motions were dominated by slip down-dip of the rupture, but various researchers ascribe elements of relaxation to dominantly poroelastic, dominantly viscoelastic, and dominantly fault slip processes, depending primarily on their measurement sampling and modeling tools used. After subtracting a pre-2004 interseismic velocity, significant transient motion during the 2008.5-2010.5 epoch confirms that postseismic relaxation processes continue in Andaman. Modeling three-component velocities as viscoelastic flow yields a weighted root-mean-square (wrms) misfit that always exceeds the wrms of the measured signal (26.3 mm/yr). The best-fitting models are those that yield negligible deformation, indicating the model parameters have no real physical meaning. GPS velocities are well fit (wrms 4.0 mm/yr) by combining a viscoelastic flow model that best fits the horizontal velocities with similar to 50 cm/yr thrust slip down-dip of the coseismic rupture. Both deep slip and flow respond to stress changes, and each can significantly change stress in the realm of the other; it therefore is reasonable to expect that both transient deep slip and viscoelastic flow will influence surface deformation long after a great earthquake.

Residual strength of hot pressed zirconium diboride (ZrB2) after exposure to high temperatures

ZrB2 with different amounts of B4C additive (0-5 wt.%) has been hot pressed at 2000 degrees C and 25 MPa for 1 h. By addition of B4C, density as well as micro-hardness increased. For lower B4C content (0.5 and 1 wt.%), hot pressed ZrB2 shows considerable improvement in flexural strength after exposure in air at 1000 C for 5 h, while higher B4C content (3 and 5 wt.%) leads to marginal or no improvement. For any content of B4C, flexural strength after exposure in air at 1500 degrees C for 5 h is lower than as-hot pressed ZrB2. (C) 2011 Elsevier B.V. All rights reserved.

Hierarchical Clustering Algorithm for Land Cover Mapping Using Satellite Images

This paper presents hierarchical clustering algorithms for land cover mapping problem using multi-spectral satellite images. In unsupervised techniques, the automatic generation of number of clusters and its centers for a huge database is not exploited to their full potential. Hence, a hierarchical clustering algorithm that uses splitting and merging techniques is proposed. Initially, the splitting method is used to search for the best possible number of clusters and its centers using Mean Shift Clustering (MSC), Niche Particle Swarm Optimization (NPSO) and Glowworm Swarm Optimization (GSO). Using these clusters and its centers, the merging method is used to group the data points based on a parametric method (k-means algorithm). A performance comparison of the proposed hierarchical clustering algorithms (MSC, NPSO and GSO) is presented using two typical multi-spectral satellite images - Landsat 7 thematic mapper and QuickBird. From the results obtained, we conclude that the proposed GSO based hierarchical clustering algorithm is more accurate and robust.