Attention Based Detection and Recognition of Hand Postures Against Complex Backgrounds

A system for the detection, segmentation and recognition of multi-class hand postures against complex natural backgrounds is presented. Visual attention, which is the cognitive process of selectively concentrating on a region of interest in the visual field, helps human to recognize objects in cluttered natural scenes. The proposed system utilizes a Bayesian model of visual attention to generate a saliency map, and to detect and identify the hand region. Feature based visual attention is implemented using a combination of high level (shape, texture) and low level (color) image features. The shape and texture features are extracted from a skin similarity map, using a computational model of the ventral stream of visual cortex. The skin similarity map, which represents the similarity of each pixel to the human skin color in HSI color space, enhanced the edges and shapes within the skin colored regions. The color features used are the discretized chrominance components in HSI, YCbCr color spaces, and the similarity to skin map. The hand postures are classified using the shape and texture features, with a support vector machines classifier. A new 10 class complex background hand posture dataset namely NUS hand posture dataset-II is developed for testing the proposed algorithm (40 subjects, different ethnicities, various hand sizes, 2750 hand postures and 2000 background images). The algorithm is tested for hand detection and hand posture recognition using 10 fold cross-validation. The experimental results show that the algorithm has a person independent performance, and is reliable against variations in hand sizes and complex backgrounds. The algorithm provided a recognition rate of 94.36 %. A comparison of the proposed algorithm with other existing methods evidences its better performance.     

Long Range Self‐Assembly of Polythiophene Breath Figures: Optical and Morphological Characterization

Large‐area, device relevant sized microporous thin films are formed with commercially available polythiophenes by the breath figure technique, a water‐assisted micropatterning method, with such semitransparent thin films exhibiting periodicity and uniformity dictated by the length of the polymer side chain. Compared to drop‐casted thin films, the microporous thin films exhibit increased crystallinity due to stronger packing of the polymer inside the honeycomb frame.     

Interacting MCMC particle filter for tracking maneuvering target

In this paper, a new method, named interacting MCMC particle filter, is proposed to track maneuvering target. The particles are sampled from the target posterior distribution via direct interacting MCMC sampling method, which avoids sample impoverishment and increases the robustness of the algorithm. Moreover, the interacting MCMC particle filter algorithm accelerates the MCMC convergence rate via propagating each particle based on both its history information and the information from other particles.     

Near cathode optical emission spectroscopy in N2-H2 glow discharge plasma

Optical emission spectroscopy (OES) is a non-intrusive diagnostic technique, widely used to study different kinds of plasmas. In the present work, a locally resolved OES technique was used to obtain near cathode (substrate) emission spectra for N₂-H₂ glow discharges. It was observed that, along with N₂⁺ and N₂ lines, the characteristic atomic nitrogen lines at 742.3 nm (3p ⁴S⁰_3/2 → 3s ⁴P_1/2), 744.2 nm (3p ⁴S⁰_3/2 → 3s ⁴P_3/2), 746.8 nm (3p ⁴S⁰_3/2 → 3s ⁴P_5/2) and H_α (656.3 nm) were the main emissions coming from the sheath region that shrouded the cathode. A qualitative analysis of the spectral lines near the cathode has been done in order to understand the mechanism of plasma nitriding and the role played by the hydrogen in the nitriding process. The decrease in local intensity of these atomic lines with hydrogen composition suggests that the effect of hydrogen is to enhance the sticking/adsorption of N on the cathode surface.     

Numerical solutions for boundary layers beneath a potential vortex

Two implicit finite-difference schemes, one iterative and one non-iterative, have been used to obtain improved solutions for the laminar boundary layer on a finite disc beneath a potential-flow vortex.

Results obtained by the two schemes are in close agreement to within 0.02 of the disc radius and differ substantially from earlier calculations in values of normal velocity close to the axis.

The iterative scheme has also been applied to the calculation of turbulent boundary layer development using eddy-viscosity and mixing-length models.     

SAD-IoT: Security Analysis of DDoS Attacks in IoT Networks

Wireless Personal Communications - Internet of Things is one of the most versatile technologies in existence today. It has taken over our day to day activities and thus has many applications that...