Local laser heat treatment in dual-phase steels

This research deals with processes leading to local strengthening effects in hot-rolled dual-phase (DP) steels. For this purpose, a method was investigated to achieve local strengthening, namely, local laser heat treatment (LHT). DP sheet steels were globally and homogenously deformed with different degrees of prestrains by cold rolling and subsequently locally heat treated by laser. Following this treatment with selected parameters, the microstructure of the surface and cross section of the heat-treated area as well as the mechanical properties were evaluated by light optical microscopy (LOM), scanning electron microscopy (SEM), as well as transmission electron microscopy (TEM), hardness measurement, and tensile testing. It can be stated that with partial heat treatment, local high strengthening can be produced. At lower heat treating temperatures, this effect could be attributed to bake hardening (BH). Increasing the prestrain as well as temperature results in improving the local properties. With increased heat treating temperature, the initial microstructure near the surface is affected. Partial strengthening of DP steels by laser can open up new fields of application for locally using the strengthening effect to only influence relevant areas of interest, thus providing the potential for saving energy and designed the component's behavior.

New methods for objective evaluation of fabric pilling by frequency domain image processing

Fabric pilling is a serious problem for the apparel industry. Resistance to pilling is normally tested by simulated accelerated wear and manual assessment of degree of pilling based on a visual comparison of the sample to a set of test images. A number of automated systems based on image analysis have been developed. The authors propose new methods of image analysis based on the two-dimensional wavelet transform to objectively measure the pilling intensity in sample images. Initial work employed the detail coefficients of the two-dimensional discrete wavelet transform (2DDWT) as a measure of the pilling intensity of woven/knitted fabrics.

This method is shown to be robust to image translation and brightness variation. Using the approximation coefficients of the 2DDWT, the method is extended to non-woven pilling image sets. Wavelet texture analysis (WTA) combined with principal components analysis are shown to produce a richer texture description of pilling for analysis and classification. Finally, employing the two-dimensional dual-tree complex wavelet transform as the basis for the WTA feature vector is shown to produce good automated classification on a range of standard pilling image sets.

Familiarity-based word-frequency effects in recognition memory and implicit priming

Provides evidence that familiarity as well as recollection contributes to the recognition advantage for low-frequency words. The importance for explanations of the low-frequency word advantage to account for the influence of both explicit and implicit memory processes is discussed with emphasis given to developing the dual-process model.

Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum

Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination changes, IR data introduces specific challenges of its own, most notably sensitivity to factors which affect facial heat emission patterns, e.g. emotional state, ambient temperature, and alcohol intake. In addition, facial expression and pose changes are more difficult to correct in IR images because they are less rich in high frequency detail which is an important cue for fitting any deformable model. In this paper we describe a novel method which addresses these major challenges. Specifically, when comparing two thermal IR images of faces, we mutually normalize their poses and facial expressions by using an active appearance model (AAM) to generate synthetic images of the two faces with a neutral facial expression and in the same view (the average of the two input views). This is achieved by piecewise affine warping which follows AAM fitting. A major contribution of our work is the use of an AAM ensemble in which each AAM is specialized to a particular range of poses and a particular region of the thermal IR face space. Combined with the contributions from our previous work which addressed the problem of reliable AAM fitting in the thermal IR spectrum, and the development of a person-specific representation robust to transient changes in the pattern of facial temperature emissions, the proposed ensemble framework accurately matches faces across the full range of yaw from frontal to profile, even in the presence of scale variation (e.g. due to the varying distance of a subject from the camera). The effectiveness of the proposed approach is demonstrated on the largest public database of thermal IR images of faces and a newly acquired data set of thermal IR motion videos. Our approach achieved perfect recognition performance on both data sets, significantly outperforming the current state of the art methods even when they are trained with multiple images spanning a range of head views.

Implementation of dual stack technique for reducing leakage and dynamic power

This paper deals with proposal of a new dual stack approach for reducing both leakage and dynamic powers. The development of digital integrated circuits is challenged by higher power consumption. Thecombination of higher clock speeds, greater functional integration, and smaller process geometries has contributed to significant growth in power density. Scaling improves transistor density and functionality ona chip. Scaling helps to increase speed and frequency of operation and hence higher performance. As voltages scale downward with the geometries threshold voltages must also decrease to gain the performance advantages of the new technology but leakage current increases exponentially. Today leakage power has become anincreasingly important issue in processor hardware and software design. It can be used in various applications like digital VLSI clocking system, buffers, registers, microprocessors etc. The leakage power increases astechnology is scaled down. In this paper, we propose a new dual stack approach for reducing both leakage and dynamic powers. Moreover, the novel dual stack approach shows the least speed power product whencompared to the existing methods. All well known approach is “Sleep” in this method we reduce leakage power. The proposed Dual Stack approach we reduce more power leakage. Dual Stack approach uses theadvantage of using the two extra pull-up and two extra pull-down transistors in sleep mode either in OFF state or in ON state. Since the Dual Stack portion can be made common to all logic circuitry, less number of transistors is needed to apply a certain logic circuit.The dual stack approach shows the least speed power product among all methods. The Dual Stack technique provides new ways to designers who require ultra-low leakage power consumption with much less speedpower product.

Study of direct laser fabricated high entropy alloys

This work analysed the microstructure-property correlations and solidification behavior of high entropy alloys (based on 5 principal elements: Al,Co, Cr, Fe, Ni). The novel outcome of the work is the effect of dislocation activities, texture and phase distribution on the tension-compression asymmetry of FCC, BCC and dual phase high entropy alloys.