44 resultados para Evaluation metrics

em Indian Institute of Science - Bangalore - Índia


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This study presents a comprehensive evaluation of five widely used multisatellite precipitation estimates (MPEs) against 1 degrees x 1 degrees gridded rain gauge data set as ground truth over India. One decade observations are used to assess the performance of various MPEs (Climate Prediction Center (CPC)-South Asia data set, CPC Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks, Tropical Rainfall Measuring Mission's Multisatellite Precipitation Analysis (TMPA-3B42), and Global Precipitation Climatology Project). All MPEs have high detection skills of rain with larger probability of detection (POD) and smaller ``missing'' values. However, the detection sensitivity differs from one product (and also one region) to the other. While the CMORPH has the lowest sensitivity of detecting rain, CPC shows highest sensitivity and often overdetects rain, as evidenced by large POD and false alarm ratio and small missing values. All MPEs show higher rain sensitivity over eastern India than western India. These differential sensitivities are found to alter the biases in rain amount differently. All MPEs show similar spatial patterns of seasonal rain bias and root-mean-square error, but their spatial variability across India is complex and pronounced. The MPEs overestimate the rainfall over the dry regions (northwest and southeast India) and severely underestimate over mountainous regions (west coast and northeast India), whereas the bias is relatively small over the core monsoon zone. Higher occurrence of virga rain due to subcloud evaporation and possible missing of small-scale convective events by gauges over the dry regions are the main reasons for the observed overestimation of rain by MPEs. The decomposed components of total bias show that the major part of overestimation is due to false precipitation. The severe underestimation of rain along the west coast is attributed to the predominant occurrence of shallow rain and underestimation of moderate to heavy rain by MPEs. The decomposed components suggest that the missed precipitation and hit bias are the leading error sources for the total bias along the west coast. All evaluation metrics are found to be nearly equal in two contrasting monsoon seasons (southwest and northeast), indicating that the performance of MPEs does not change with the season, at least over southeast India. Among various MPEs, the performance of TMPA is found to be better than others, as it reproduced most of the spatial variability exhibited by the reference.

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Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

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The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

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The spatial error structure of daily precipitation derived from the latest version 7 (v7) tropical rainfall measuring mission (TRMM) level 2 data products are studied through comparison with the Asian precipitation highly resolved observational data integration toward evaluation of the water resources (APHRODITE) data over a subtropical region of the Indian subcontinent for the seasonal rainfall over 6 years from June 2002 to September 2007. The data products examined include v7 data from the TRMM radiometer Microwave Imager (TMI) and radar precipitation radar (PR), namely, 2A12, 2A25, and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products were quantified based on performance metrics derived from the contingency table. For the seasonal daily precipitation over a subtropical basin in India, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with the 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition techniques performed to disentangle systematic and random errors verify that the multiplicative error model representing rainfall from 2A12 algorithm successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results verify that although the radiometer derived 2A12 rainfall data is known to suffer from many sources of uncertainties, spatial analysis over the case study region of India testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered.

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Inventory Management (IM) plays a decisive role in the enhancement of efficiency and competitiveness of manufacturing enterprises. Therefore, major manufacturing enterprises are following IM practices as a strategy to improve efficiency and achieve competitiveness. However, the spread of IM culture among Small and Medium Enterprises (SMEs) is limited due to lack of initiation, expertise and financial limitations in developed countries, leave alone developing countries. With this backdrop, this paper makes an attempt to ascertain the role and importance of IM practices and performance of SMEs in the machine tools industry of Bangalore, India. The relationship between inventory management practices and inventory cost are probed based on primary data gathered from 91 SMEs. The paper brings out that formal IM practices have a positive impact on the inventory performance of SMEs.

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Plasma sprayable powders were prepared from ZrO2-CaO-CeO2 system using an organic binder and coated onto stainless steel substrates previously coated by a bond coat (Ni 22Cr 20Al 1.0Y) using plasma spraying. The coatings exhibited good thermal barrier characteristics and excellent resistance to thermal shock at 1000 degrees C under simulated laboratory conditions (90 half hour cycles without failure) and at 1200 degrees C under accelerated burner rig test conditions (500 2 min cycles without failure). No destabilization of cubic/tetragonal ZrO2 phase fraction occured either during the long hours (45 h cumulative) or the large number of thermal shock tests. Growth of a distinct SiO2 rich region within the ceramic was observed in the specimens thermal shock cycled at 1000 degrees C apart from mild oxidation of the bond coat. The specimens tested at 1200 degrees C had a glassy appearance on the top surface and exhibited severe oxidation of the bond coat at the ceramic-bond coat interface. The glassy appearance of the surface is due to the formation of a liquid silicate layer attributable to the impurity phase present in commercial grade ZrO2 powder. These observations are supported by SEM analysis and quantitative EDAX data.

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Three new (dialkylamino)pyridine (DAAP)-based ligand amphiphiles 3-5 have been synthesized. All of the compounds possess a metal ion binding subunit in the form of a 2,6-disubstituted DAAP moiety. In addition, at least one ortho-CH2OH substituent is present in all the ligands. Complex formation by these ligands with various metal ions were examined under micellar conditions, but only complexes with Cu(II) ions showed kinetically potent esterolytic capacities under micellar conditions. Complexes with Cu(II) were prepared in host comicellar cetyltrimethylammonium bromide (CTABr) media at pH 7.6. Individual complexes were characterized by UV-visible absorption spectroscopy and electron paramagnetic resonance spectroscopy. These metallomicelles speed the cleavage of the substrates p-nitrophenyl hexanoate or p-nitrophenyl diphenyl phosphate. To ascertain the nature of the active esterolytic species, the stoichiometries of the respective Cu(II) complexes were determined from the kinetic version of Job's plot. In all the instances, 2:1 complex ligand/Cu(II) ion are the most kinetically competent species. The apparent pK(a) values of the Cu(II)-coordinated hydroxyl groups of the ligands 3, 4, and 5, in the comicellar aggregate, are 7.8, 8.0, and 8.0, respectively, as estimated from the rate constant vs pH: profiles of the ester cleavage reactions. The nucleophilic metallomicellar reagents and the second-order "catalytic" rate constants toward esterolysis of the substrate p-nitrophenyl hexanoate (at 25 degrees C, pH 7.6) are 37.5 for 3, 11.4 for 4, and 13.8 for 5. All catalytic systems comprising the coaggregates of 3, 4, or 5 and CTABr demonstrate turnover behavior in the presence of excess substrate.

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Silver/metal hydride (Ag/MH) cells of about 1 Ah capacity have been fabricated and their discharge characteristics at different rates of discharge, faradaic efficiency, cycle life and a.c. impedance have been evaluated. These cells comprise metal-hydride electrodes prepared by employing similar to 60 mu m powder of an AB(2)-Laves phase alloy of nominal composition Zr0.5Ti0.5V0.6Cr0.2Ni1.2 with PTFE binder on a nickel-mesh substrate as the negative plates and commercial-grade silver electrodes as the positive plates. The cells are positive limited and exhibit two distinct voltage plateaus characteristic of two-step reduction of AgO to Ag during their low rates of discharge between C/20 and C/10. This feature is, however, absent when the cells are discharged at C/5 rate. On charging the cells to 100% of their capacity, the faradaic efficiency is found to be 100%. The impedance of the Ag/MH cell is essentially due to the impedance of the silver electrodes, since MH electrodes offer negligible impedance. The cells may be subjected to a large number of charge-discharge cycles with little deterioration.

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An oxovanadium(IV) complex of dipyridophenazine, as a potent metal-based PDT agent, shows efficient DNA photocleavage activity at near-IR region and high photocytotoxicity in both UV-A and visible light in HeLa cells.

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In order to explore the anticancer effect associated with the thiazolidinone framework, several 2-(5-((5-(4-chlorophenyl)furan-2-yl)methylene)-4-oxo-2-thioxothiazolidin-3-yl)acetic acid derivatives 5(a-1) were synthesized. Variation in the functional group at C-terminal of the thiazolidinone led to set of compounds bearing amide moiety. Their chemical structures were confirmed by H-1 NMR, IR and Mass Spectra analysis. These thiazolidinone compounds containing furan moiety exhibits moderate to strong antiproliferative activity in a cell cycle stage-dependent and dose dependent manner in two different human leukemia cell lines. The importance of the electron donating groups on thiazolidinone moiety was confirmed by MTT and Trypan blue assays and it was concluded that the 4th position of the substituted aryl ring plays a dominant role for its anticancer property. Among the synthesized compounds, 5e and 5f have shown potent anticancer activity on both the cell lines tested. To rationalize the role of electron donating group in the induction of cytotoxicity we have chosen two molecules (5e and 5k) having different electron donating group at different positions. LDH assay, Flow cytometric analysis and DNA fragmentation suggest that 5e is more cytotoxic and able to induce the apoptosis. (C) 2009 Elsevier Ltd. All rights reserved.

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This paper presents three methodologies for determining optimum locations and magnitudes of reactive power compensation in power distribution systems. Method I and Method II are suitable for complex distribution systems with a combination of both radial and ring-main feeders and having different voltage levels. Method III is suitable for low-tension single voltage level radial feeders. Method I is based on an iterative scheme with successive powerflow analyses, with formulation and solution of the optimization problem using linear programming. Method II and Method III are essentially based on the steady state performance of distribution systems. These methods are simple to implement and yield satisfactory results comparable with the results of Method I. The proposed methods have been applied to a few distribution systems, and results obtained for two typical systems are presented for illustration purposes.

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A simple cconversence technique is applied to obtain accurate estimates of critical temperatures and critical it\ponmts of a few two- and threpdiniensional king models. When applied to the virial series for hard spheres and hard discs, this method predicts a divergence of the equation-of-state at the density of closest packing.

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In this paper, the design and implementation of a single shared bus, shared memory multiprocessing system using Intel's single board computers is presented. The hardware configuration and the operating system developed to execute the parallel algorithms are discussed. The performance evaluation studies carried out on Image are outlined.

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An exact expression for the calculation of gaussian path integrals involving non-local potentials is given. Its utility is demonstrated by using it to evaluate a path integral arising in the study of an electron gas in a random potential.