Experimental investigation on corrosion and hardness of ion implanted AISI 316L stainless steel

The AISI 316L stainless steel has been widely used both in artificial knee and hip joints in bio-medical applications. In the present study AISI 316L SS was implanted with two different ions: nitrogen and helium at 100 keV with a dose of 1 × 10¹⁷ ions/cm² at room temperature. The crystallographic orientation and surface morphology were studied using X-ray diffraction (XRD) and scanning electron microscope (SEM). The effects of ion implantation on the corrosion performance of AISI 316L stainless steel was evaluated in 0.9% NaCl solution using electro chemical test both on the virgin and implanted samples. The subsequent Tafel analysis shows that the ion implanted specimens were more corrosion resistant when compared to the bare specimens. Microhardness was also measured by Vickers method by varying the loads. The results of the studies indicated that there was a significant improvement in both corrosion resistance and hardness of implanted samples.     

Nitrogen-incorporated carbon nanotube derived from polystyrene and polypyrrole as hydrogen storage material

“Synthesis of nitrogen-doped carbon nanotubes from polymeric precursors (polystyrene and polypyrrole) by poly-condensation followed by carbonization under an inert atmosphere is reported. Three different carbonization temperatures (500 °C, 700 °C and 900 °C) were employed to synthesize three different carbon nanostructures with different morphologies. These were designated as NCNR-500 (nitrogen-doped carbon nanorods), NCBCT-700 (nitrogen-doped fused bead carbon nanotubes), and NCNT-900 (nitrogen-doped carbon nanotubes) according to morphology and carbonization temperature. Microstructure, morphology, porosity, and nitrogen content were characterized by several different techniques. The effects of carbonization temperature and the role of functional groups were also investigated. Total and excess hydrogen storage capacities of 2.0 wt% and 1.8 wt%, respectively, were measured at 298 K and 100 bar for the NCNT-900 material. This is higher than the capacities of the NCNR-500 and NCBCT-700 materials. NCNT-900 exhibited a porous structure with high specific surface area and total pore volume of 870 m/g and 0.62 cm³/g, respectively.     

Image motion estimation from motion smear-a new computational model

Motion smear is an important visual cue for motion perception by the human vision system (HVS). However, in image analysis research, exploiting motion smear has been largely ignored. Rather, motion smear is usually considered as a degradation of images that needs to be removed. In this paper, the authors establish a computational model that estimates image motion from motion smear information-“motion from smear”. In many real situations, the shutter of the sensing camera must be kept open long enough to produce images of adequate signal-to-noise ratio (SNR), resulting in significant motion smear in images. The authors present a new motion blur model and an algorithm that enables unique estimation of image motion. A prototype sensor system that exploits the new motion blur model has been built to acquire data for “motion-from-smear”. Experimental results on images with both simulated smear and real smear, using the authors' “motion-from-smear” algorithm as well as a conventional motion estimation technique, are provided. The authors also show that temporal aliasing does not affect “motion-from-smear” to the same degree as it does algorithms that use displacement as a cue. “Motion-from-smear” provides an additional tool for motion estimation and effectively complements the existing techniques when apparent motion smear is present     

Integrated analysis of thermal and visual images for sceneinterpretation

An approach for computer perception of outdoor scenes is presented. The approach is based on integrating information extracted from thermal images and visual images, which provides information not available by processing either type of image alone. The thermal image is analyzed to provide estimates of surface temperature. The visual image provides surface absorptivity and relative orientation. These parameters are used together to provide estimates of heat fluxes at the surfaces of viewed objects. The thermal behavior of scene objects is described in terms of surface heat fluxes. Features based on estimated values of surface heat fluxes are shown to be more meaningful and specific in distinguishing scene components     

Spatiotemporal approach for time-varying global image motionestimation

Image motion estimation using the spatiotemporal approach has largely relied on the constant velocity assumption, and thus becomes inappropriate when the velocity of the imaged scene or the camera changes during the data acquisition time. Using a polynomial or a trigonometric polynomial model for the time variation of the image motion, spatiotemporal algorithms are developed in this paper to handle time-varying (but space-invariant) motion. Under these models, it is shown that time-varying image motion estimation is equivalent to parameter estimation of one-dimensional (1-D) polynomial phase or phase-modulated signals, which allows one to exploit well-established results in radar signal processing. When compared with alternative approaches, the resulting motion estimation algorithms produce more accurate estimates. Simulation results are provided to demonstrate the proposed schemes.     

DSSCs: a facile and low-cost MgSnO3-based transparent conductive oxides via nebulized spray pyrolysis technique

Journal of Materials Science: Materials in Electronics - The primary focus of this investigation was constructing worthwhile and cost-effective TCO substrate to make low-cost dye-sensitized solar...     

The artificial intelligence approach to pattern recognition—a perspective and an overview

The present paper reviews the techniques for automated extraction of information from signals. The techniques may be classified broadly into two categories—the conventional pattern recognition approach and the artificial intelligence (AI) based approach. The conventional approach comprises two methodologies—statistical and structural. The paper reviews salient issues in the application of conventional techniques for extraction of information. The systems that use the artificial intelligence approach are characterized with respect to three key properties. The basic differences between the approaches and the computational aspects are reviewed. Current trends in the use of the AI approach are indicated. Some key ideas in current literature are reviewed.