Methods for Automatic Evaluation of Sentence Extract Summaries

This paper describes three novel techniques to automatically evaluate sentence extract summaries. Two of these techniques called FuSE and DeFuSE evaluate the quality of the generated extract summary based on the degree of similarity to the model summary. They use a fuzzy set theoretic basis to generate a match score. DeFuSE is an enhancement to FuSE and uses WordNet based hypernymy structures to detect similarity between sentences at abstracted levels. The third technique focuses on quantifying the quality of an extract summary based on the difficulty in generating such a summary. Advantages of these techniques are described with examples.

Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method

In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA) and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation to extract road segments where as, Normalizedcut method for road extraction is a graph based method that generates optimal partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments in urban region from high resolution satellite image.

Direct stability evaluation of power systems with detailed generator models using structure-preserving energy functions

Energy-based direct methods for transient stability analysis are potentially useful both as offline tools for planning purposes as well as for online security assessment. In this paper, a novel structure-preserving energy function (SPEF) is developed using the philosophy of structure-preserving model for the system and detailed generator model including flux decay, transient saliency, automatic voltage regulator (AVR), exciter and damper winding. A simpler and yet general expression for the SPEF is also derived which can simplify the computation of the energy function. The system equations and the energy function are derived using the centre-of-inertia (COI) formulation and the system loads are modelled as arbitrary functions of the respective bus voltages. Application of the proposed SPEF to transient stability evaluation of power systems is illustrated with numerical examples.

Automatic Compilation of MATLAB Programs for Synergistic Execution on Heterogeneous Processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

An Evaluation of Inventory Management and Performance in Indian Machine Tool SMEs: An Exploratory Study

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.

Evaluation of CaO-CeO2-partially stabilized zirconia thermal barrier coatings

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.

Synthesis of some copper(II)-chelating (dialkylamino)pyridine amphiphiles and evaluation of their esterolytic capacities in cationic micellar media

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.

Fabrication and evaluation of 1 Ah silver/metal hydride cells

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.

Oxovanadium(IV)-based near-IR PDT agents: design to biological evaluation

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.

Synthesis of 2-(5-((5-(4-chlorophenyl)furan 2-yl)methylene)-4-oxo-2-thioxo-thiazolidi n-3-yl)acetic acid derivatives and evaluation of their cytotoxicity and induction of apoptosis in human leukemia cells

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.

Optimum Evaluation of Reactive Power Requirements in Power Distribution-Systems

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.