Nanocrystalline TiO(2) preparation by microwave route and nature of anatase-rutile phase transition in nano TiO(2)

Nanopowders of TiO(2) has been prepared using a microwave irradiation-assisted route, starting from a metalorganic precursor, bis(ethyl-3-oxo-butanoato)oxotitanium (IV), [TiO(etob)(2)](2). Polyvinylpyrrolidone (PVP) was used as a capping agent. The as-prepared amorphous powders crystallize into anatase phase, when calcined. At higher calcination temperature, the rutile phase is observed to form in increasing quantities as the calcination temperature is raised. The structural and physicochemical properties were measured using XRD, FT-IR, SEM, TEM and thermal analyses. The mechanisms of formation of nano-TiO(2) from the metal-organic precursor and the irreversible phase transformation of nano TiO(2) from anatase to rutile structure at higher temperatures have been discussed. It is suggested that a unique step of initiation of transformation takes place in Ti(1/2)O layers in anatase which propagates. This mechanism rationalizes several key observations associated with the anatase rutile transformation.

NMR methods for fast data acquisition

NMR spectroscopy has witnessed tremendous advancements in recent years with the development of new methodologies for structure determination and availability of high-field strength spectrometers equipped with cryogenic probes. Supported by these advancements, a new dimension in NMR research has emerged which aims to increase the speed with data is collected and analyzed. Several novel methodologies have been proposed in this direction. This review focuses on the principles on which these different approaches are based with an emphasis on G-matrix Fourier transform NMR spectroscopy.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Preparation of a thermally sensitive ammonium perchlorate

The effect of ultrasound on the thermal decomposition behaviour of ammonium perchlorate (AP) has been investigated. It was observed that significant changes in the thermal behaviour of A-P, followed using differential thermal analysis and thermogravimetry, was observed when AP was subjected to power ultrasound in water saturated with oxygen-nitrogen mixture. The decomposition temperature of AP was found to have been lowered by nearly 25degreesC. A similar thermal sensitization was observed in AP when subjected to sonication in the presence of transition metal oxides. Kinetic parameters were calculated for AP, modified AP and catalyzed AP decomposition using non-isothermal kinetics. The activation energy for the decomposition of the sonicated AP samples were found to be lower than normal AP.

A simple and fast scheme for code compression for VLIW processors

Summary form only given. A scheme for code compression that has a fast decompression algorithm, which can be implemented using simple hardware, is proposed. The effectiveness of the scheme on the TMS320C62x architecture that includes the overheads of a line address table (LAT) is evaluated and obtained compression rates ranging from 70% to 80%. Two schemes for decompression are proposed. The basic idea underlying the scheme is a simple clustering algorithm that partially maps a block of instructions into a set of clusters. The clustering algorithm is a greedy algorithm based on the frequency of occurrence of various instructions.

Fast algorithms for frequent episode discovery in event sequences

In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

An Opportunistic, Fast, and Distributed Subchannel and User-Pairing Algorithm for OFDMA

Channel-aware assignment of subchannels to users in the downlink of an OFDMA system requires extensive feedback of channel state information (CSI) to the base station. Since bandwidth is scarce, schemes that limit feedback are necessary. We develop a novel, low feedback, distributed splitting-based algorithm called SplitSelect to opportunistically assign each subchannel to its most suitable user. SplitSelect explicitly handles multiple access control aspects associated with CSI feedback, and scales well with the number of users. In it, according to a scheduling criterion, each user locally maintains a scheduling metric for each subchannel. The goal is to select, for each subchannel, the user with the highest scheduling metric. At any time, each user contends for the subchannel for which it has the largest scheduling metric among the unallocated subchannels. A tractable asymptotic analysis of a system with many users is central to SplitSelect's simple design. Extensive simulation results demonstrate the speed with which subchannels and users are paired. The net data throughput, when the time overhead of selection is accounted for, is shown to be substantially better than several schemes proposed in the literature. We also show how fairness and user prioritization can be ensured by suitably defining the scheduling metric.

Mutual inhibition and capacity sharing during parallel preparation of serial eye movements

Many common activities, like reading, scanning scenes, or searching for an inconspicuous item in a cluttered environment, entail serial movements of the eyes that shift the gaze from one object to another. Previous studies have shown that the primate brain is capable of programming sequential saccadic eye movements in parallel. Given that the onset of saccades directed to a target are unpredictable in individual trials, what prevents a saccade during parallel programming from being executed in the direction of the second target before execution of another saccade in the direction of the first target remains unclear. Using a computational model, here we demonstrate that sequential saccades inhibit each other and share the brain's limited processing resources (capacity) so that the planning of a saccade in the direction of the first target always finishes first. In this framework, the latency of a saccade increases linearly with the fraction of capacity allocated to the other saccade in the sequence, and exponentially with the duration of capacity sharing. Our study establishes a link between the dual-task paradigm and the ramp-to-threshold model of response time to identify a physiologically viable mechanism that preserves the serial order of saccades without compromising the speed of performance.

Human action recognition using a fast learning fully complex-valued classifier

In this paper, we use optical flow based complex-valued features extracted from video sequences to recognize human actions. The optical flow features between two image planes can be appropriately represented in the Complex plane. Therefore, we argue that motion information that is used to model the human actions should be represented as complex-valued features and propose a fast learning fully complex-valued neural classifier to solve the action recognition task. The classifier, termed as, ``fast learning fully complex-valued neural (FLFCN) classifier'' is a single hidden layer fully complex-valued neural network. The neurons in the hidden layer employ the fully complex-valued activation function of the type of a hyperbolic secant function. The parameters of the hidden layer are chosen randomly and the output weights are estimated as the minimum norm least square solution to a set of linear equations. The results indicate the superior performance of FLFCN classifier in recognizing the actions compared to real-valued support vector machines and other existing results in the literature. Complex valued representation of 2D motion and orthogonal decision boundaries boost the classification performance of FLFCN classifier. (c) 2012 Elsevier B.V. All rights reserved.

Coexistence of fast photodarkening and slow photobleaching in Ge19As21Se60 thin films

We experimentally demonstrate the coexistence of two opposite photo-effects, viz. fast photodarkening (PD) and slow photobleaching (PB) in Ge19As21Se60 thin films, when illuminated with a laser of wavelength 671 nm. PD appears to begin instantaneously upon light illumination and saturates in tens of seconds. By comparison, PB is a slower process that starts only after PD has saturated. Both PD and PB follow stretched exponetial dependence on time. Modeling of overall change as a linear sum of two contributions suggests that the changes in As and Ge parts of glass network respond to light effectively indepndent of each other. (C) 2012 Optical Society of America

Electroless Ni-W-P Coating and Its Nano-WS2 Composite: Preparation and Properties

The ternary alloy Ni-W-P and its WS2 nanocomposite coatings were successfully obtained on low-carbon steel using the electroless plating technique. The sodium tungstate (Na2WO4) concentration in the bath was varied to obtain Ni-W-P deposits containing various Ni and P contents. WS2 composite was obtained with a suitable concentration of Na2WO4 in Ni-P coating. These deposits were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray analysis (EDX) studies. The corrosion behavior was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) studies in 3.5 wt % NaCl solutions, and the corrosion rates of the coatings for Ni-P, Ni-W-P, and Ni-W-P-WS2 were found to be 2.571 x 10(-5), 8.219 x 10(-7), and 7.986 x 10(-7) g/h, respectively. An increase in the codeposition of alloying metal tungsten (W) enhanced the corrosion resistance and microhardness and changed the structure and morphology of the deposits. Incorporation of WS2 nanoparticles to Ni-W-P alloy coating reduced the coefficient of friction from 0.16 to 0.11 and also helped in improving the corrosion resistance of the coating further.

AIWIN - A fast and jigless inspection technique for machined parts

Precision inspection of manufactured components having multiple complex surfaces and variable tolerance definition is an involved, complex and time-consuming function. In routine practice, a jig is used to present the part in a known reference frame to carry out the inspection process. Jigs involve both time and cost in their development, manufacture and use. This paper describes 'as is where is inspection' (AIWIN), a new automated inspection technique that accelerates the inspection process by carrying out a fast registration procedure and establishing a quick correspondence between the part to inspect and its CAD geometry. The main challenge in doing away with a jig is that the inspection reference frame could be far removed from the CAD frame. Traditional techniques based on iterative closest point (ICP) or Newton methods require either a large number of iterations for convergence or fail in such a situation. A two-step coarse registration process is proposed to provide a good initial guess for a modified ICP algorithm developed earlier (Ravishankar et al., Int J Adv Manuf Technol 46(1-4):227-236, 2010). The first step uses a calibrated sphere for local hard registration and fixing the translation error. This transformation locates the centre for the sphere in the CAD frame. In the second step, the inverse transformation (involving pure rotation about multiple axes) required to align the inspection points measured on the manufactured part with the CAD point dataset of the model is determined and enforced. This completes the coarse registration enabling fast convergence of the modified ICP algorithm. The new technique has been implemented on complex freeform machined components and the inspection results clearly show that the process is precise and reliable with rapid convergence. © 2011 Springer-Verlag London Limited.