A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

First passage distributions for long memory processes

We study the distribution of first passage time for Levy type anomalous diffusion. A fractional Fokker-Planck equation framework is introduced.For the zero drift case, using fractional calculus an explicit analytic solution for the first passage time density function in terms of Fox or H-functions is given. The asymptotic behaviour of the density function is discussed. For the nonzero drift case, we obtain an expression for the Laplace transform of the first passage time density function, from which the mean first passage time and variance are derived.

Non-linear electrical response of chalcogenide glasses: Memory state phenomena

Investigations on the switching behaviour of arsenic-tellurium glasses with Ge or Al additives, yield interesting information about the dependence of switching on network rigidity, co-ordination of the constituents, glass transition & ambient temperature and glass forming ability.

On-Chip Memory Architecture Exploration Framework for DSP Processor-Based Embedded System on Chip

Today's SoCs are complex designs with multiple embedded processors, memory subsystems, and application specific peripherals. The memory architecture of embedded SoCs strongly influences the power and performance of the entire system. Further, the memory subsystem constitutes a major part (typically up to 70%) of the silicon area for the current day SoC. In this article, we address the on-chip memory architecture exploration for DSP processors which are organized as multiple memory banks, where banks can be single/dual ported with non-uniform bank sizes. In this paper we propose two different methods for physical memory architecture exploration and identify the strengths and applicability of these methods in a systematic way. Both methods address the memory architecture exploration for a given target application by considering the application's data access characteristics and generates a set of Pareto-optimal design points that are interesting from a power, performance and VLSI area perspective. To the best of our knowledge, this is the first comprehensive work on memory space exploration at physical memory level that integrates data layout and memory exploration to address the system objectives from both hardware design and application software development perspective. Further we propose an automatic framework that explores the design space identifying 100's of Pareto-optimal design points within a few hours of running on a standard desktop configuration.

Effect of selenium addition on the GeTe phase change memory alloys

Compositional dependent investigations of the bulk GeTe chalcogenides alloys added with different selenium concentrations are carried out by X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), electron probe micro-analyzer (EPMA) and differential scanning calorimetry (DSC). The measurements reveal that GeTe crystals are predominant in alloys up to 0.20 at.% of Se content indicating interstitial occupancy of Se in the Ge vacancies. Raman modes in the GeTe alloys changes to GeSe modes with the addition of Se. Amorphousness in the alloy increases with increase of Se and 0.50 at.% Se alloy forms a homogeneous amorphous phase with a mixture of Ge-Se and Te-Se bonds. Structural changes are explained with the help of bond theory of solids. Crystallization temperature is found to be increasing with increase of Se, which will enable the amorphous stability. For the optimum 0.50 at.% Se alloy, the melting temperature has reduced which will reduce the RESET current requirement for the phase change memory applications. (C) 2012 Elsevier B.V. All rights reserved.

Nature of Quiet Sun Oscillations Using Data from the Hinode, TRACE, and SOHO Spacecraft

We study the nature of quiet-Sun oscillations using multi-wavelength observations from TRACE, Hinode, and SOHO. The aim is to investigate the existence of propagating waves in the solar chromosphere and the transition region by analyzing the statistical distribution of power in different locations, e.g. in bright magnetic (network), bright non-magnetic and dark non-magnetic (inter-network) regions, separately. We use Fourier power and phase-difference techniques combined with a wavelet analysis. Two-dimensional Fourier power maps were constructed in the period bands 2 -aEuro parts per thousand 4 minutes, 4 -aEuro parts per thousand 6 minutes, 6 -aEuro parts per thousand 15 minutes, and beyond 15 minutes. We detect the presence of long-period oscillations with periods between 15 and 30 minutes in bright magnetic regions. These oscillations were detected from the chromosphere to the transition region. The Fourier power maps show that short-period powers are mainly concentrated in dark regions whereas long-period powers are concentrated in bright magnetic regions. This is the first report of long-period waves in quiet-Sun network regions. We suggest that the observed propagating oscillations are due to magnetoacoustic waves, which can be important for the heating of the solar atmosphere.

TURBULENT PUMPING OF MAGNETIC FLUX REDUCES SOLAR CYCLE MEMORY AND THUS IMPACTS PREDICTABILITY OF THE SUN'S ACTIVITY

Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. have shown that the dynamical memory of the solar dynamo mechanism governs predictability, and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum-allowing about five years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.

Efficient external memory structures for range-aggregate queries

We present external memory data structures for efficiently answering range-aggregate queries. The range-aggregate problem is defined as follows: Given a set of weighted points in R-d, compute the aggregate of the weights of the points that lie inside a d-dimensional orthogonal query rectangle. The aggregates we consider in this paper include COUNT, sum, and MAX. First, we develop a structure for answering two-dimensional range-COUNT queries that uses O(N/B) disk blocks and answers a query in O(log(B) N) I/Os, where N is the number of input points and B is the disk block size. The structure can be extended to obtain a near-linear-size structure for answering range-sum queries using O(log(B) N) I/Os, and a linear-size structure for answering range-MAX queries in O(log(B)(2) N) I/Os. Our structures can be made dynamic and extended to higher dimensions. (C) 2012 Elsevier B.V. All rights reserved.

SEU Tolerant Robust Memory Cell Design

The implementation of semiconductor circuits and systems in nano-technology makes it possible to achieve high speed, lower voltage level and smaller area. The unintended and undesirable result of this scaling is that it makes integrated circuits susceptible to soft errors normally caused by alpha particle or neutron hits. These events of radiation strike resulting into bit upsets referred to as single event upsets(SEU), become increasingly of concern for the reliable circuit operation in the field. Storage elements are worst hit by this phenomenon. As we further scale down, there is greater interest in reliability of the circuits and systems, apart from the performance, power and area aspects. In this paper we propose an improved 12T SEU tolerant SRAM cell design. The proposed SRAM cell is economical in terms of area overhead. It is easy to fabricate as compared to earlier designs. Simulation results show that the proposed cell is highly robust, as it does not flip even for a transient pulse with 62 times the Q(crit) of a standard 6T SRAM cell.

Virtually cool ternary content addressable memory

Fast content addressable data access mechanisms have compelling applications in today's systems. Many of these exploit the powerful wildcard matching capabilities provided by ternary content addressable memories. For example, TCAM based implementations of important algorithms in data mining been developed in recent years; these achieve an an order of magnitude speedup over prevalent techniques. However, large hardware TCAMs are still prohibitively expensive in terms of power consumption and cost per bit. This has been a barrier to extending their exploitation beyond niche and special purpose systems. We propose an approach to overcome this barrier by extending the traditional virtual memory hierarchy to scale up the user visible capacity of TCAMs while mitigating the power consumption overhead. By exploiting the notion of content locality (as opposed to spatial locality), we devise a novel combination of software and hardware techniques to provide an abstraction of a large virtual ternary content addressable space. In the long run, such abstractions enable applications to disassociate considerations of spatial locality and contiguity from the way data is referenced. If successful, ideas for making content addressability a first class abstraction in computing systems can open up a radical shift in the way applications are optimized for memory locality, just as storage class memories are soon expected to shift away from the way in which applications are typically optimized for disk access locality.

Fluoranthene based derivatives for detection of trace explosive Nitroaromatics

A series of fluoranthene derivatives (F1-F5) varied with nature and type of substituents were synthesized via Diels-Alder reaction followed by in situ decarbonylation. The solid state structures have been established through single crystal X-ray diffraction (XRD). The presence of extended conjugation and having two alkyloxy chains on phenyl rings induces flexibility to orient opposite to each other and interacts with another fluoranthene unit with weak pi-pi interactions and show unique supramolecular arrangements. The envisaged photophysical and DFT studies demonstrated that HOMO-LUMO levels were effectively tuned by different substituents with an optical band gap from 3.44 to 3.88 eV provoked to examine as sensitive fluorescent chemosensors for the detection of nitroaromatic compounds (NACs). The sensitivity toward the detection of NACs was evaluated through fluorescence quenching in solution (aqueous and non-aqueous) and solid state (vapor and contact mode). Fluorescence studies demonstrated that electron transfer occurs from the electron rich fluoranthene fluorophores to the electron deficient NACs by the dominant static quenching mechanism and the quenching process is reversible. It was found that the detection sensitivity increases with extent of conjugation on fluoranthene unit. The contact mode approach using thin layer silica chromatographic plates exhibits a femtogram (1.15 fg/cm(2)) detection limit for trinitrotoluene (TNT) and picric acid (PA), while the solution state fluorescence quenching shows for PA detection at the 2-20 ppb level. The sensing performance of fluoranthene thin films to NACs in aqueous solution reveals that fluorophores are highly selective towards the detection of PA. The smart performances of thin film fluorophores with high photostability have great advantage than those of conjugated polymers with superior sensitive detection of PA in groundwater.

A possible connection between antidiabetic and antilipemic properties of psoralea corylifolia seeds and the trace elements present: a LIBS based study

Psoralea corylifolia (PC), a medicinal plant, is used in traditional medicine to treat diabetes. Purpose of the research was to examine the antidiabetic and antilipemic potential of PC and to determine the relationship between its antidiabetic potential and the trace elements present. Wistar rats (150-200 g) with fasting blood glucose (FBG) of 80-110 mg dl(-1)(sub-diabetic) and 150-200 mg dl(-1)(mild diabetic) were selected for the short term antidiabetic studies and severely diabetic rats (FBG > 300 mg dl(-1)) were chosen for the long term antidiabetic and hypolipemic studies of PC seed extract. Laser induced breakdown spectroscopy (LIBS) was used to detect trace elements in the PC extract and the intensity ratios of trace elements were estimated. The dose of 250 mg kg(-1) of PC extract was found to be the most effective in lowering blood glucose level (BGL) of normal, sub, mild and severely diabetic rats during FBG and glucose tolerance test (GTT) studies. Lipid profile studies on severely diabetic rats showed substantial reduction in total cholesterol, triglycerides, very low density lipoprotein, and low density lipoprotein and an increase in the total protein, body weight, high density lipoprotein, and hemoglobin after 28 days of treatment. Significant reduction in urine sugar and protein levels was also observed. LIBS analysis of the PC extract revealed the presence of Mg, Si, Na, K, Ca, Zn and Cl. The study validates the traditional use of PC in the treatment of diabetes and confirms its antilipemic potential. The antidiabetic activity of PC extract may partly be due to the presence of appreciable amounts of insulin potentiating elements like Mg, Ca, and K.

Feasibility of laser-induced breakdown spectroscopy for the study of the temporal distribution of trace elements trapped in snow collected from greater himalayan range

The potential merit of laser-induced breakdown spectroscopy (LIBS) has been demonstrated for detection and quantification of trace pollutants trapped in snow/ice samples. In this technique, a high-power pulsed laser beam from Nd:YAG Laser (Model no. Surelite III-10, Continuum, Santa Clara, CA, USA) is focused on the surface of the target to generate plasma. The characteristic emissions from laser-generated plasma are collected and recorded by a fiber-coupled LIBS 2000+ (Ocean Optics, Santa Clara, CA, USA) spectrometer. The fingerprint of the constituents present in the sample is obtained by analyzing the spectral lines by using OOI LIBS software. Reliable detection of several elements like Zn, Al, Mg, Fe, Ca, C, N, H, and O in snow/ice samples collected from different locations (elevation) of Manali and several snow samples collected from the Greater Himalayan region (from a cold lab in Manali, India) in different months has been demonstrated. The calibration curve approach has been adopted for the quantitative analysis of these elements like Zn, Al, Fe, and Mg. Our results clearly demonstrate that the level of contamination is higher in those samples that were collected in the month of January in comparison to those collected in February and March.