Polyceptron a polyhedral learning algorithm

In this paper we propose a new algorithm for learning polyhedral classifiers which we call as Polyceptron. It is a Perception like algorithm which updates the parameters only when the current classifier misclassifies any training data. We give both batch and online version of Polyceptron algorithm. Finally we give experimental results to show the effectiveness of our approach.

High power microwave coupling with a buried twisted pair cable

This paper deals with the coupling of High Power Microwaves with a buried twisted pair cable. The electric field at a distance of 1km from the HPM antenna has been computed and is used for further computation of induced voltage and current. It is found that the peak of the induced current and voltage in a buried unshielded twisted pair cable at a distance of 1km from an HPM antenna of power level 10GW is 20A and 2kV respectively.

Water treatment potential in relation to phytoplankton dynamics in tropical sewage-fed urban water bodies

Urban water bodies frequently receive untreated sewage and water levels in such water bodies are maintained by daily inputs of sewage. They function as “variable-zone” anaerobic-aerobic lagoons suffering several macrophyte, biotic and abiotic stresses. We have studied two such lakes in Bangalore (Bellandur-360 ha and Varthur-220 ha) to understand whether such an occurrence could be made beneficial (maintaining water levels as well as treatment). Such hypertrophic water body receives sewage at 180-250mg/L and is discharged at 25-80mg/L COD/BOD in different seasons. In an earlier study we reported macrophyte altering the purification function of the water body. In this paper we studied the impact of phytoplankton dynamics and macrophyte cover on the functions such as organic load removal. Algal community analysis, algal biomass, macrophyte cover, water quality, nutrient status was studied seasonally during 2009-2010. Oxygen deficiency and sometimes anoxia, recorded from surface samples resulted in high quantities of NH4+-N (30-40mg/L) and phosphate (0.5-4mg/L)-characteristics of anoxic hypertrophic urban lakes. The productiveness favoured high phytoplanktonic community characterized by small cells (<10μm; Chlorella sp. - highest numbers). The lake could be clearly demarcated into an initial anaerobic zone (40% area), a facultative zone (20%) and an aerobic zone (40%) based on redox values and GIS/bathymetry. During summer the lake is covered by floating macrophytes converting the lake into an anoxic/anaerobic water pool subduing the water purification function as well as aesthetics. When macrophytes are controlled such sewage fed water bodies can be used for treating urban wastewater while also maintaining water sustainability in these semi-arid ecosystems. This paper reports the community dynamics of phytoplankton, their function and competition with macrophytes.

A Finite Element Method Based Approach for Evaluating the Sensitivity of Faraday-Type Electromagnetic Flow Meter for Liquid Sodium Flow

Faraday-type electromagnetic flow meters are employed for measuring the flow rate of liquid sodium in fast breeder reactors. The calibration of such flow meters, owing to the required elaborative arrangements is rather difficult. On the other hand, theoretical approach requires solution of two coupled electromagnetic partial differential equation with profile of the flow and applied magnetic field as the inputs. This is also quite involved due to the 3D nature of the problem. Alternatively, Galerkin finite element method based numerical solution is suggested in the literature as an attractive option for the required calibration. Based on the same, a computer code in Matlab platform has been developed in this work with both 20 and 27 node brick elements. The boundary conditions are correctly defined and several intermediate validation exercises are carried out. Finally it is shown that the sensitivities predicted by the code for flow meters of four different dimensions agrees well with the results given by analytical expression, thereby providing strong validation. Sensitivity for higher flow rates, for which analytical approach does not exist, is shown to decrease with increase in flow velocity.

Spectral zero-crossings: localization properties and application to epoch extraction in speech signals

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.

A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

Some new results on signal reconstruction from Fourier transform magnitude spectrum

We address the problem of signal reconstruction from Fourier transform magnitude spectrum. The problem arises in many real-world scenarios where magnitude-only measurements are possible, but it is required to construct a complex-valued signal starting from those measurements. We present some new general results in this context and show that the previously known results on minimum-phase rational transfer functions, and recoverability of minimum-phase functions from magnitude spectrum, form special cases of the results reported in this paper. Some simulation results are also provided to demonstrate the practical feasibility of the reconstruction methodology.

A generalized Stein's estimation approach to speech enhancement based on perceptual criteria

We address the problem of speech enhancement using a risk- estimation approach. In particular, we propose the use the Stein’s unbiased risk estimator (SURE) for solving the problem. The need for a suitable finite-sample risk estimator arises because the actual risks invariably depend on the unknown ground truth. We consider the popular mean-squared error (MSE) criterion first, and then compare it against the perceptually-motivated Itakura-Saito (IS) distortion, by deriving unbiased estimators of the corresponding risks. We use a generalized SURE (GSURE) development, recently proposed by Eldar for MSE. We consider dependent observation models from the exponential family with an additive noise model,and derive an unbiased estimator for the risk corresponding to the IS distortion, which is non-quadratic. This serves to address the speech enhancement problem in a more general setting. Experimental results illustrate that the IS metric is efficient in suppressing musical noise, which affects the MSE-enhanced speech. However, in terms of global signal-to-noise ratio (SNR), the minimum MSE solution gives better results.

Power-law transformation for enhanced recognition of born-digital word images

In this paper, we discuss the issues related to word recognition in born-digital word images. We introduce a novel method of power-law transformation on the word image for binarization. We show the improvement in image binarization and the consequent increase in the recognition performance of OCR engine on the word image. The optimal value of gamma for a word image is automatically chosen by our algorithm with fixed stroke width threshold. We have exhaustively experimented our algorithm by varying the gamma and stroke width threshold value. By varying the gamma value, we found that our algorithm performed better than the results reported in the literature. On the ICDAR Robust Reading Systems Challenge-1: Word Recognition Task on born digital dataset, as compared to the recognition rate of 61.5% achieved by TH-OCR after suitable pre-processing by Yang et. al. and 63.4% by ABBYY Fine Reader (used as baseline by the competition organizers without any preprocessing), we achieved 82.9% using Omnipage OCR applied on the images after being processed by our algorithm.

Effects of two-wheelers on saturation flow at signalized intersections in developing countries

Two-wheelers (TW) constitute a major proportion of urban traffic in developing countries and therefore their effect on the saturation flow at signalized intersections could be substantial. This paper attempts to study and analyze the effect of two-wheelers on the saturation flow of signalized intersections by collecting data at a few signalized intersections in Bangalore, India. A strong correlation is observed between the measured saturation flow and the proportion of two-wheeler traffic, which suggest that two-wheelers have significant impact and should be considered in the capacity analysis of signalized intersections. In this paper, the effect of two-wheelers on saturation flow rate is incorporated in a previous model by calibrating and introducing a new adjustment factor for two-wheelers. Results show that saturation flow measured using the modified HCM equation is closer to observed saturation flow values.

Identification of source of heavy metal contamination in a site - a case study

Accidental spills and improper disposal of industrial effluent/sludge containing heavy metals onto the open land or into subsurface result in soil and water contamination. Detailed investigations are carried out to identify the source of contamination of heavy metals in an industrial suburb near Bangalore in India. Detailed investigation of ground water and subsurface soil analysis for various heavy metals has been carried out. Ground water samples were collected in the entire area through the cluster of borewells. Subsurface soil samples were collected from near borewells which were found to contain heavy metals. Water samples and soils samples (after acid digestion) were analysed as per APHO-standard method of analysis. While the results of Zn, Ni and Cd showed that they are within allowable limits in the soil, the ground water and soils in the site have concentration of Cr+6 far exceeding the allowable limits (up to 832 mg/kg). Considering the topography of the area, ground water movement and results of chromium concentration in the borewells and subsurface it was possible to identify the origin, zone of contamination and the migration path of Cr+6. The results indicated that the predominant mechanism of migration of Cr+6 is by diffusion.

Algal biofuel from urban wastewater in India: Scope and challenges

Rapidly depleting stocks of fossil fuels and increasing greenhouse gas (GHG) emissions have necessitated the exploration of cost effective sustainable energy sources focussing on biofuels through algae. Abundant wastewaters generated in urban localities every day provide the nourishment to nurture algae for biofuel generation. The present communication focuses on the lipid prospects of algae grown in wastewater systems. Euglena sp., Spirogyra sp. and Phormidium sp. were collected from selected locations of sewage fed urban lakes and sewage treatment plants of Bangalore and Mysore. The total lipid content of Euglena sp. was higher (24.6%) compared to Spirogyra sp. (18.4%) followed by Phormidium sp. (8.8%) and their annual lipid yield potential was 6.52, 1.94 and 2.856 t/ha/year, respectively. These species showed higher content of fatty acids (palmitate, stearate followed by oleic and linoleic acids) with the desirable biofuel properties. (C) 2013 Elsevier Ltd. All rights reserved.

Analytical Expression for RMS DC Link Capacitor Current in a Three-Level Inverter

An analytical expression is derived for calculating the rms current through the DC link capacitor in a three level inverter. The output current of the inverter is assumed to sinusoidal. Variations in the capacitor rms current with modulation index as well as line side power factor are studied. The worst case current stress on the capacitor is determined. This is required for sizing the capacitor and is useful for predicting the capacitor losses and life. The analytical expression derived is validated through simulations and experimental results at a number of operating points.

miR-219-5p inhibits receptor tyrosine kinase pathway by targeting EGFR in glioblastoma

Glioblastoma is one of the common types of primary brain tumors with a median survival of 12-15 months. The receptor tyrosine kinase (RTK) pathway is known to be deregulated in 88% of the patients with glioblastoma. 45% of GBM patients show amplifications and activating mutations in EGFR gene leading to the upregulation of the pathway. In the present study, we demonstrate that a brain specific miRNA, miR-219-5p, repressed EGFR by directly binding to its 3'-UTR. The expression of miR-219-5p was downregulated in glioblastoma and the overexpression of miR-219-5p in glioma cell lines inhibited the proliferation, anchorage independent growth and migration. In addition, miR-219-5p inhibited MAPK and PI3K pathways in glioma cell lines in concordance with its ability to target EGFR. The inhibitory effect of miR-219-5p on MAPK and PI3K pathways and glioma cell migration could be rescued by the overexpression of wild type EGFR and vIII mutant of EGFR (both lacking 3'-UTR and thus being insensitive to miR-219-5p) suggesting that the inhibitory effects of miR-219-5p were indeed because of its ability to target EGFR. We also found significant negative correlation between miR-219-5p levels and total as well as phosphorylated forms of EGFR in glioblastoma patient samples. This indicated that the downregulation of miR-219-5p in glioblastoma patients contribute to the increased activity of the RTK pathway by the upregulation of EGFR. Thus, we have identified and characterized miR-219-5p as the RTK regulating novel tumor suppressor miRNA in glioblastoma.

Fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group

Background: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Methods: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. Results: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p < 0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. Conclusion: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.