12 resultados para Trace analysis.

em Indian Institute of Science - Bangalore - Índia


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An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

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Several replacement policies for web caches have been proposed and studied extensively in the literature. Different replacement policies perform better in terms of (i) the number of objects found in the cache (cache hit), (ii) the network traffic avoided by fetching the referenced object from the cache, or (iii) the savings in response time. In this paper, we propose a simple and efficient replacement policy (hereafter known as SE) which improves all three performance measures. Trace-driven simulations were done to evaluate the performance of SE. We compare SE with two widely used and efficient replacement policies, namely Least Recently Used (LRU) and Least Unified Value (LUV) algorithms. Our results show that SE performs at least as well as, if not better than, both these replacement policies. Unlike various other replacement policies proposed in literature, our SE policy does not require parameter tuning or a-priori trace analysis and has an efficient and simple implementation that can be incorporated in any existing proxy server or web server with ease.

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Background: Interaction of non-structural protein 5A (NS5A) of Hepatitis C virus (HCV) with human kinases namely, casein kinase 1 alpha (ck1 alpha) and protein kinase R (PKR) have different functional implications such as regulation of viral replication and evasion of interferon induced immune response respectively. Understanding the structural and molecular basis of interactions of the viral protein with two different human kinases can be useful in developing strategies for treatment against HCV. Results: Serine 232 of NS5A is known to be phosphorylated by human ck1 alpha. A structural model of NS5A peptide containing phosphoacceptor residue Serine 232 bound to ck1 alpha has been generated using the known 3-D structures of kinase-peptide complexes. The substrate interacting residues in ck1 alpha has been identified from the model and these are found to be conserved well in the ck1 family. ck1 alpha - substrate peptide complex has also been used to understand the structural basis of association between ck1 alpha and its other viral stress induced substrate, tumour suppressor p53 transactivation domain which has a crystal structure available. Interaction of NS5A with another human kinase PKR is primarily genotype specific. NS5A from genotype 1b has been shown to interact and inhibit PKR whereas NS5A from genotype 2a/3a are unable to bind and inhibit PKR efficiently. This is one of the main reasons for the varied response to interferon therapy in HCV patients across different genotypes. Using PKR crystal structure, sequence alignment and evolutionary trace analysis some of the critical residues responsible for the interaction of NS5A 1b with PKR have been identified. Conclusions: The substrate interacting residues in ck1 alpha have been identified using the structural model of kinase substrate peptide. The PKR interacting NS5A 1b residues have also been predicted using PKR crystal structure, NS5A sequence analysis along with known experimental results. Functional significance and nature of interaction of interferon sensitivity determining region and variable region 3 of NS5A in different genotypes with PKR which was experimentally shown are also supported by the findings of evolutionary trace analysis. Designing inhibitors to prevent this interaction could enable the HCV genotype 1 infected patients respond well to interferon therapy.

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A regular secondary structure is described by a well defined set of values for the backbone dihedral angles (phi,psi and omega) in a polypeptide chain. However in real protein structures small local variations give rise to distortions from the ideal structures, which can lead to considerable variation in higher order organization. Protein structure analysis and accurate assignment of various structural elements, especially their terminii, are important first step in protein structure prediction and design. Various algorithms are available for assigning secondary structure elements in proteins but some lacunae still exist. In this study, results of a recently developed in-house program ASSP have been compared with those from STRIDE, in identification of alpha-helical regions in both globular and membrane proteins. It is found that, while a combination of hydrogen bond patterns and backbone torsional angles (phi-psi) are generally used to define secondary structure elements, the geometry of the C-alpha atom trace by itself is sufficient to define the parameters of helical structures in proteins. It is also possible to differentiate the various helical structures by their C-alpha trace and identify the deviations occurring both at mid-positions as well as at the terminii of alpha-helices, which often lead to occurrence of 3(10) and pi-helical fragments in both globular and membrane proteins.

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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.

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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.

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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.

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The sensitivity of combustion phasing and combustion descriptors to ignition timing, load and mixture quality on fuelling a multi-cylinder natural gas engine with bio-derived H-2 and CO rich syngas is addressed. While the descriptors for conventional fuels are well established and are in use for closed loop engine control, presence of H-2 in syngas potentially alters the mixture properties and hence combustion phasing, necessitating the current study. The ability of the descriptors to predict abnormal combustion, hitherto missing in the literature, is also addressed. Results from experiments using multi-cylinder engines and numerical studies using zero dimensional Wiebe function based simulation models are reported. For syngas with 20% H-2 and CO and 2% CH4 (producer gas), an ignition retard of 5 +/- 1 degrees was required compared to natural gas ignition timing to achieve peak load of 72.8 kWe. It is found that, for syngas, whose flammability limits are 0.42-1.93, the optimal engine operation was at an equivalence ratio of 1.12. The same methodology is extended to a two cylinder engine towards addressing the influence of syngas composition, especially H-2 fraction (varying from 13% to 37%), on the combustion phasing. The study confirms the utility of pressure trace derived combustion descriptors, except for the pressure trace first derivative, in describing the MBT operating condition of the engine when fuelled with an alternative fuel. Both experiments and analysis suggest most of the combustion descriptors to be independent of the engine load and mixture quality. A near linear relationship with ignition angle is observed. The general trend(s) of the combustion descriptors for syngas fuelled operation are similar to those of conventional fuels; the differences in sensitivity of the descriptors for syngas fuelled engine operation requires re-calibration of control logic for MBT conditions. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

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For a domain Omega in C and an operator T in B-n(Omega), Cowen and Douglas construct a Hermitian holomorphic vector bundle E-T over Omega corresponding to T. The Hermitian holomorphic vector bundle E-T is obtained as a pull-back of the tautological bundle S(n, H) defined over by Gr(n, H) a nondegenerate holomorphic map z bar right arrow ker(T - z), z is an element of Omega. To find the answer to the converse, Cowen and Douglas studied the jet bundle in their foundational paper. The computations in this paper for the curvature of the jet bundle are rather intricate. They have given a set of invariants to determine if two rank n Hermitian holomorphic vector bundle are equivalent. These invariants are complicated and not easy to compute. It is natural to expect that the equivalence of Hermitian holomorphic jet bundles should be easier to characterize. In fact, in the case of the Hermitian holomorphic jet bundle J(k)(L-f), we have shown that the curvature of the line bundle L-f completely determines the class of J(k)(L-f). In case of rank Hermitian holomorphic vector bundle E-f, We have calculated the curvature of jet bundle J(k)(E-f) and also obtained a trace formula for jet bundle J(k)(E-f).

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Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

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The effect of doping trace amounts of noblemetals (Pt) on the gas sensing properties of chromium oxide thin films, is studied. The sensors are fabricated by depositing chromium oxide films on a glass substrate using a modified spray pyrolysis technique and characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. The films are porous and nanocrystalline with an average crystallite size of similar to 30 nm. The typical p-type conductivity arises due to the presence of Cr vacancies, formed as a result of Cr non-stoichiometry, which is found to vary upon Pt doping. In order to analyze the effect of doping on the gas sensing properties, we have adopted a kinetic response analysis approach, which is based on Langmuir Adsorption isotherm (LA) theory. The sensor response is analyzed with equations obtained from LA theory and time constants as well as energies of adsorption-desorption are evaluated. It is seen that, Pt doping lowers the Schottky barrier height of the metal oxide semiconductor sensor from 222 meV to 172 meV. Subsequently the reduction in adsorption and desorption energies led to enhancement in sensor response and improvement in the kinetics of the sensor response i.e. the response time as well as recovery times of the sensor.

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We revisit the a posteriori error analysis of discontinuous Galerkin methods for the obstacle problem derived in 25]. Under a mild assumption on the trace of obstacle, we derive a reliable a posteriori error estimator which does not involve min/max functions. A key in this approach is an auxiliary problem with discrete obstacle. Applications to various discontinuous Galerkin finite element methods are presented. Numerical experiments show that the new estimator obtained in this article performs better.