Effect of processing route on phase stability in equiatomic multicomponent Ti20Fe20Ni20Co20Cu20 high entropy alloy

The evolution of microstructure and phase formation in equiatomic Ti20Fe20Ni20Co20Cu20 high entropy alloy synthesised by conventional arc melting followed with suction casting and ball milling with spark plasma sintering route is distinctly different. The cast microstructure exhibits one body centre cubic and two face centre cubic high entropy phases based on titanium, cobalt and copper respectively along with a eutectic containing Ti2Ni type Laves phase. On the contrary, spinodal decomposed microstructure consisting of cobalt and copper solid solution is obtained in the sintered sample. However, long term annealing of cast sample at 950 degrees C reveals a eutectoid transformation with different phases than the cast sample. The aforementioned observations are discussed using CALPHAD thermodynamical approach and available literature.

Processing of EEG Signals for Study of Coupling in Brain Regions for Eyes Open and Eyes Closed Conditions

This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.

A novel in-situ polymer derived nano ceramic MMC by friction stir processing

Fiction stir processing (FSP) is a solid state technique used for material processing. Tool wear and the agglomeration of ceramic particles have been serious issues in FSP of metal matrix composites. In the present study, FSP has been employed to disperse the nanoscale particles of a polymer-derived silicon carbonitride (SiCN) ceramic phase into copper by an in-situ process. SiCN cross linked polymer particles were incorporated using multi-pass ESP into pure copper to form bulk particulate metal matrix composites. The polymer was then converted into ceramic through an in-situ pyrolysis process and dispersed by ESP. Multi-pass processing was carried out to remove porosity from the samples and also for the uniform dispersion of polymer derived ceramic particles. Microstructural observations were carried out using Field Emission Scanning Electron Microscopy (FE-SEM) and Transmission Electron Microscopy (TEM) of the composite. The results indicate a uniform distribution of similar to 100 nm size particles of the ceramic phase in the copper matrix after ESP. The nanocomposite exhibits a five fold increase in microhardness (260HV(100)) which is attributed to the nano scale dispersion of ceramic particles. A mechanism has been proposed for the fracturing of PDC particles during multi pass FSP. (C) 2015 Elsevier Ltd. All rights reserved

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.

Ancilla-assisted measurements on quantum ensembles: general protocols and applications in NMR quantum information processing

Quantum ensembles form easily accessible architectures for studying various phenomena in quantum physics, quantum information science and spectroscopy. Here we review some recent protocols for measurements in quantum ensembles by utilizing ancillary systems. We also illustrate these protocols experimentally via nuclear magnetic resonance techniques. In particular, we shall review noninvasive measurements, extracting expectation values of various operators, characterizations of quantum states and quantum processes, and finally quantum noise engineering.

PolyMage: Automatic Optimization for Image Processing Pipelines

This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious. The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

A Numerical Model of Rapid Solidification Processing of Ni-Al Alloy in Planar Flow Casting

A numerical model has been developed for simulating the rapid solidification processing (RSP) of Ni-Al alloy in order to predict the resultant phase composition semi-quantitatively during RSP. The present model couples the initial nucleation temperature evaluating method based on the time dependent nucleation theory, and solidified volume fraction calculation model based on the kinetics model of dendrite growth in undercooled melt. This model has been applied to predict the cooling curve and the volume fraction of solidified phases of Ni-Al alloy in planar flow casting. The numerical results agree with the experimental results semi-quantitatively.

Tailoring of dendritic microstructure in solidification processing by crucible vibration

We analyzed the effects of both natural convection and forced flows on solid–liquid interface morphology during upward Bridgman solidification of metallic alloys. Experiments were carried out on Al–3.5wt% Ni alloy, for a cylindrical sample. The influence of natural convection induced by radial thermal gradient on solidified microstructure was first analyzed as a function of the pulling rate. Then, the influence of axial vibration on solidification microstructure was experimentally investigated by varying vibration parameters (frequency and amplitude). Experimental results demonstrated that vibrations could be used to either attenuate fluid flow in the melt and obtain a uniform dendritic pattern or to promote a fragmented dendritic microstructure. However, no marked effect was observed for cellular growth. This pointed out the critical role of the mushy zone in the interaction between fluid flow and solidification microstructure.

Influence of the Processing Conditions on the Characteristics of the Clad Layers Produced with Laminar Plasma Technology

Laminar plasma technology was used to produce ceramic hardened layers of Al2O3-40% mass Ni composite powders on stainless steel substrates. In order to investigate the influences of processing conditions on the morphologies of the surface modified layers, two different powder-feeding methods were tested, one with carrier gas called the powder injection method, and the other without carrier gas called powder transfers method. The microscopic investigations demonstrate that the cross-section of the clad layers consists of two distinct microstructural regions, in which the Al2O3 phases exhibit different growth mechanisms. When the powder transfers method is adopted, the number density and volume fraction of the Al2O3 particles increase considerably and their distributions exhibit zonal periodical characteristics. When the powder-feeding rate increases, the microstructure of the Al2O3 phases changes from a small globular to a long needle shape. Finite element simulations show that the transient thermo-physical features of the pool substances, such as solidification rate and cooling rate, influence strongly the mechanisms of the nucleation and the directional growth of the Al2O3 phases in the thermal processing.

Determination of Proper Processing Conditions of Material Surface Heat Treatment Through Finite Element Method

A two-dimensional model has been developed based on the experimental results of stainless steel remelting with the laminar plasma technology to investigate the transient thermo-physical characteristics of the melt pool liquids. The influence of the temperature field, temperature gradient, solidification rate and cooling rate on the processing conditions has been investigated numerically. Not only have the appropriate processing conditions been determined according to the calculations, but also they have been predicted with a criterion established based on the concept of equivalent temperature area density (ETAD) that is actually a function of the processing parameters and material properties. The comparison between the resulting conditions shows that the ETAD method can better predict the optimum condition.