Search for optimum labeling schemes in qubit systems for Quantum Information processing by NMR

Optimal labeling schemes lead to efficient experimental protocols for quantum information processing by nuclear magnetic resonance (NMR). A systematic approach of finding optimal labeling schemes for a given computation is described here. The scheme is described for both quadrupolar systems and spin-1/2 systems. Finally, one of the optimal labeling scheme has been used to experimentally implement a quantum full-adder in a 4-qubit system by NMR, using the technique of transition selective pulses.Comment: 24 pages, 6 figure

Conditioning Covert Geo-Location (CGL) Detection on Semantic Class Information

The primary goal of artificial intelligence is to mimic humans. Therefore, to advance toward this goal, the AI community attempts to imitate qualities/skills possessed by humans and imbibes them into machines with the help of datasets/tasks. Earlier, many tasks which require knowledge about the objects present in an image are satisfactorily solved by vision models. Recently, with the aim to incorporate knowledge about non-object image regions (hideouts, turns, and other obscured regions), a task for identification of potential hideouts termed Covert Geo-Location (CGL) detection was proposed by Saha et al. It involves identification of image regions which have the potential to either cause an imminent threat or appear as target zones to be accessed for further investigation to identify any occluded objects. Only certain occluding items belonging to certain semantic classes can give rise to CGLs. This fact was overlooked by Saha et al. and no attempts were made to utilize semantic class information, which is crucial for CGL detection. In this paper, we propose a multitask-learning-based approach to achieve 2 goals - i) extraction of features having semantic class information; ii) robust training of the common encoder, exploiting large standard annotated datasets as training set for the auxiliary task (semantic segmentation). To explicitly incorporate class information in the features extracted by the encoder, we have further employed attention mechanism in a novel manner. We have also proposed a better evaluation metric for CGL detection that gives more weightage to recognition rather than precise localization. Experimental evaluations performed on the CGL dataset, demonstrate a significant increase in performance of about 3% to 14% mIoU and 3% to 16% DaR on split 1, and 1% mIoU and 1% to 2% DaR on split 2 over SOTA, serving as a testimony to the superiority of our approach

SnakeCut : an Integrated Approach Based on Active Contour and GrabCut for Automatic Foreground Object Segmentation

Interactive techniques for extracting the foreground object from an image have been the interest of research in computer vision for a long time. This paper addresses the problem of an efficient, semi-interactive extraction of a foreground object from an image. Snake (also known as Active contour) and GrabCut are two popular techniques, extensively used for this task. Active contour is a deformable contour, which segments the object using boundary discontinuities by minimizing the energy function associated with the contour. GrabCut provides a convenient way to encode color features as segmentation cues to obtain foreground segmentation from local pixel similarities using modified iterated graph-cuts. This paper first presents a comparative study of these two segmentation techniques, and illustrates conditions under which either or both of them fail. We then propose a novel formulation for integrating these two complimentary techniques to obtain an automatic foreground object segmentation. We call our proposed integrated approach as "SnakeCut", which is based on a probabilistic framework. To validate our approach, we show results both on simulated and natural images

Quantization error in stereo imaging systems

In this paper a stochastic analysis of the quantization error in a stereo imaging system has been presented. Further the probability density function of the range estimation error and the expected value of the range error magnitude are derived in terms of various design parameters. Further the relative range error is proposed

Reconstruction of quadratic curves in 3-D from two or more perspective views

The issues involved in the reconstruction of a quadratic curve in 3-D space from arbitrary perspective projections are described in this paper. Correspondence between the projections of the curve on the image planes is assumed to be established. Equations for reconstruction of the 3-D curve, which give the parameters of the 3-D quadratic curve are determined. Uniqueness of the solution in the process of reconstruction is addressed and solved using additional constraints. As practical examples, reconstruction of circles, parabolas and pair of straight lines in 3-D space are demonstrated

A Clue to Understand Environmental Influence on Friction and Wear of Diamond-Like Nanocomposite Thin Film

The wear and friction of diamond-like nanocomposite (DLN) film have been investigated in air with different relative humidity (RH), under deionized (DI) water and saline solution. The structure of the film has been characterized by Fourier transform infrared (FTIR), Raman spectroscopy, and scanning electron microscope (SEM). The result shows two interpenetrating network structure: a–C:H and a–Si:O, and they are interpenetrated by Si–C bonding. The tribological performance has been measured using ball-on-disc tribometer with tungsten carbide ball as counterbody at 10 N normal load. Results show that with increasing relative humidity (RH) from 35% to 80%, the coefficient of friction (COF) increases gradually from 0.005 to 0.074, whereas with increasing RH the wear factor decreases from 9.8×10−8 mm3/Nm and attains a minimum value of 2.7×10−8 mm3/Nm at 50% RH. With further increase of RH the wear factor increases again. Moreover, in DI water and especially in saline solution, both the COF and wear factor have been found to be significantly low. A clue has been interpreted to understand environmental dependency, considering the effect of surface dangling bonds, charge transfer, and chemical interactions

Deposition and characterization of diamond-like nanocomposite coatings grown by plasma enhanced chemical vapour deposition over different substrate materials

Diamond-like nanocomposite (DLN) coatings have been deposited over different substrates used for biomedical applications by plasma-enhanced chemical vapour deposition (PECVD). DLN has an interconnecting network of amorphous hydrogenated carbon and quartz-like oxygenated silicon. Raman spectroscopy, Fourier transform-infra red (FT-IR) spectroscopy, transmission electron microscopy (TEM) and X-ray diffraction (XRD) have been used for structural characterization. Typical DLN growth rate is about 1 m/h, measured by stylus profilometer. Due to the presence of quartz-like Si:O in the structure, it is found to have very good adhesive property with all the substrates. The adhesion strength found to be as high as 0 center dot 6 N on SS 316 L steel substrates by scratch testing method. The Young's modulus and hardness have found to be 132 GPa and 14 center dot 4 GPa, respectively. DLN coatings have wear factor in the order of 1 x 10 (-aEuro parts per thousand 7) mm (3) /N-m. This coating has found to be compatible with all important biomedical substrate materials and has successfully been deposited over Co-Cr alloy based knee implant of complex shape