MULTI-PITCH TRACKING USING GAUSSIAN MIXTURE MODEL WITH TIME VARYING PARAMETERS AND GRATING COMPRESSION TRANSFORM

Grating Compression Transform (GCT) is a two-dimensional analysis of speech signal which has been shown to be effective in multi-pitch tracking in speech mixtures. Multi-pitch tracking methods using GCT apply Kalman filter framework to obtain pitch tracks which requires training of the filter parameters using true pitch tracks. We propose an unsupervised method for obtaining multiple pitch tracks. In the proposed method, multiple pitch tracks are modeled using time-varying means of a Gaussian mixture model (GMM), referred to as TVGMM. The TVGMM parameters are estimated using multiple pitch values at each frame in a given utterance obtained from different patches of the spectrogram using GCT. We evaluate the performance of the proposed method on all voiced speech mixtures as well as random speech mixtures having well separated and close pitch tracks. TVGMM achieves multi-pitch tracking with 51% and 53% multi-pitch estimates having error <= 20% for random mixtures and all-voiced mixtures respectively. TVGMM also results in lower root mean squared error in pitch track estimation compared to that by Kalman filtering.

VISUAL OBJECT TRACKING VIA RANDOM FERNS BASED CLASSIFICATION

Designing a robust algorithm for visual object tracking has been a challenging task since many years. There are trackers in the literature that are reasonably accurate for many tracking scenarios but most of them are computationally expensive. This narrows down their applicability as many tracking applications demand real time response. In this paper, we present a tracker based on random ferns. Tracking is posed as a classification problem and classification is done using ferns. We used ferns as they rely on binary features and are extremely fast at both training and classification as compared to other classification algorithms. Our experiments show that the proposed tracker performs well on some of the most challenging tracking datasets and executes much faster than one of the state-of-the-art trackers, without much difference in tracking accuracy.

TIME VARYING LINEAR PREDICTION USING SPARSITY CONSTRAINTS

Time-varying linear prediction has been studied in the context of speech signals, in which the auto-regressive (AR) coefficients of the system function are modeled as a linear combination of a set of known bases. Traditionally, least squares minimization is used for the estimation of model parameters of the system. Motivated by the sparse nature of the excitation signal for voiced sounds, we explore the time-varying linear prediction modeling of speech signals using sparsity constraints. Parameter estimation is posed as a 0-norm minimization problem. The re-weighted 1-norm minimization technique is used to estimate the model parameters. We show that for sparsely excited time-varying systems, the formulation models the underlying system function better than the least squares error minimization approach. Evaluation with synthetic and real speech examples show that the estimated model parameters track the formant trajectories closer than the least squares approach.

ELLIPSE FITTING USING FINITE RATE OF INNOVATION PRINCIPLES

We address the problem of parameter estimation of an ellipse from a limited number of samples. We develop a new approach for solving the ellipse fitting problem by showing that the x and y coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals. Uniform samples of x and y coordinate functions of the ellipse are modeled as a sum of weighted complex exponentials, for which we propose an efficient annihilating filter technique to estimate the ellipse parameters from the samples. The FRI framework allows for estimating the ellipse parameters reliably from partial or incomplete measurements even in the presence of noise. The efficiency and robustness of the proposed method is compared with state-of-art direct method. The experimental results show that the estimated parameters have lesser bias compared with the direct method and the estimation error is reduced by 5-10 dB relative to the direct method.

ON THE ROLE OF THE HILBERT TRANSFORM IN BOOSTING THE PERFORMANCE OF THE ANNIHILATING FILTER

We consider the problem of parameter estimation from real-valued multi-tone signals. Such problems arise frequently in spectral estimation. More recently, they have gained new importance in finite-rate-of-innovation signal sampling and reconstruction. The annihilating filter is a key tool for parameter estimation in these problems. The standard annihilating filter design has to be modified to result in accurate estimation when dealing with real sinusoids, particularly because the real-valued nature of the sinusoids must be factored into the annihilating filter design. We show that the constraint on the annihilating filter can be relaxed by making use of the Hilbert transform. We refer to this approach as the Hilbert annihilating filter approach. We show that accurate parameter estimation is possible by this approach. In the single-tone case, the mean-square error performance increases by 6 dB for signal-to-noise ratio (SNR) greater than 0 dB. We also present experimental results in the multi-tone case, which show that a significant improvement (about 6 dB) is obtained when the parameters are close to 0 or pi. In the mid-frequency range, the improvement is about 2 to 3 dB.

NESTED SPARSE BAYESIAN LEARNING FOR BLOCK-SPARSE SIGNALS WITH INTRA-BLOCK CORRELATION

In this work, we address the recovery of block sparse vectors with intra-block correlation, i.e., the recovery of vectors in which the correlated nonzero entries are constrained to lie in a few clusters, from noisy underdetermined linear measurements. Among Bayesian sparse recovery techniques, the cluster Sparse Bayesian Learning (SBL) is an efficient tool for block-sparse vector recovery, with intra-block correlation. However, this technique uses a heuristic method to estimate the intra-block correlation. In this paper, we propose the Nested SBL (NSBL) algorithm, which we derive using a novel Bayesian formulation that facilitates the use of the monotonically convergent nested Expectation Maximization (EM) and a Kalman filtering based learning framework. Unlike the cluster-SBL algorithm, this formulation leads to closed-form EMupdates for estimating the correlation coefficient. We demonstrate the efficacy of the proposed NSBL algorithm using Monte Carlo simulations.

AN OPTIMUM SHRINKAGE ESTIMATOR BASED ON MINIMUM-PROBABILITY-OF-ERROR CRITERION AND APPLICATION TO SIGNAL DENOISING

We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.

MAXIMUM A-POSTERIORI ESTIMATION OF MISSING SAMPLES WITH CONTINUITY CONSTRAINT IN ELECTROMAGNETIC ARTICULOGRAPHY DATA

Electromagnetic Articulography (EMA) technique is used to record the kinematics of different articulators while one speaks. EMA data often contains missing segments due to sensor failure. In this work, we propose a maximum a-posteriori (MAP) estimation with continuity constraint to recover the missing samples in the articulatory trajectories recorded using EMA. In this approach, we combine the benefits of statistical MAP estimation as well as the temporal continuity of the articulatory trajectories. Experiments on articulatory corpus using different missing segment durations show that the proposed continuity constraint results in a 30% reduction in average root mean squared error in estimation over statistical estimation of missing segments without any continuity constraint.

ADAPTATION OF MW LEVEL NATURAL GAS LEAN BURN ENGINE FOR PRODUCER GAS OPERATION A GRID CONNECTED POWER PLANT

Availability of producer gas engines at MW being limited necessitates to adapt engine from natural gas operation. The present work focus on the development of necessary kit for adapting a 12 cylinder lean burn turbo-charged natural gas engine rated at 900 kWe (Waukesha make VHP5904LTD) to operate on producer and set up an appropriate capacity biomass gasification system for grid linked power generation in Thailand. The overall plant configuration had fuel processing, drying, reactor, cooling and cleaning system, water treatment, engine generator and power evacuation. The overall project is designed for evacuation of 1.5 MWe power to the state grid and had 2 gasification system with the above configuration and 3 engines. Two gasification system each designed for about 1100 kg/hr of woody biomass was connected to the engine using a producer gas carburetor for the necessary Air to fuel ratio control. In the use of PG to fuel IC engines, it has been recognized that the engine response will differ as compared to the response with conventional fueled operation due to the differences in the thermo-physical properties of PG. On fuelling a conventional engine with PG, power de-rating can be expected due to the lower calorific value (LCV), lower adiabatic flame temperature (AFT) and the lower than unity product to reactant more ratio. Further the A/F ratio for producer gas is about 1/10th that of natural gas and requires a different carburetor for engine operation. The research involved in developing a carburetor for varying load conditions. The patented carburetor is based on area ratio control, consisting of a zero pressure regulator and a separate gas and air line along with a mixing zone. The 95 litre engine at 1000 rpm has an electrical efficiency of 33.5 % with a heat input of 2.62 MW. Each engine had two carburetors designed for producer gas flow each capable of handling about 1200 m3/hr in order to provide similar engine heat input at a lower conversion efficiency. Cold flow studies simulating the engine carburetion system results showed that the A/F was maintained in the range of 1.3 +/- 0.1 over the entire flow range. Initially, the gasification system was tested using woody biomass and the gas composition was found to be CO 15 +/- 1.5 % H-2 22 +/- 2% CH4 2.2 +/- 0.5 CO2 11.25 +/- 1.4 % and rest N-2, with the calorific value in the range of 5.0 MJ/kg. After initial trials on the engine to fine tune the control system and adjust various engine operating parameter a peak load of 800 kWe was achieved, while a stable operating conditions was found to be at 750 kWe which is nearly 85 % of the natural gas rating. The specific fuel consumption was found to be 0.9 kg of biomass per kWh.

EXPERIENCE OF OPERATING OPEN TOP BIOMASS GASIFIER USING A LOW DENSITY FUEL-COCONUT FRONDS

Use of fuel other than woody generally has been limited to rice husk and other residues are rarely tried as a fuel in a gasification system. With the availability of woody biomass in most countries like India, alternates fuels are being explored for sustainable supply of fuel. Use of agro residues has been explored after briquetting. There are few feedstock's like coconut fronts, maize cobs, etc, that might require lesser preprocessing steps compared to briquetting. The paper presents a detailed investigation into using coconut fronds as a fuel in an open top down draft gasification system. The fuel has ash content of 7% and was dried to moisture levels of 12 %. The average bulk density was found to be 230 kg/m3 with a fuel size particle of an average size 40 mm as compared to 350 kg/m3 for a standard wood pieces. A typical dry coconut fronds weighs about 2.5kgs and on an average 6 m long and 90 % of the frond is the petiole which is generally used as a fuel. The focus was also to compare the overall process with respect to operating with a typical woody biomass like subabul whose ash content is 1 %. The open top gasification system consists of a reactor, cooling and cleaning system along with water treatment. The performance parameters studied were the gas composition, tar and particulates in the clean gas, water quality and reactor pressure drop apart from other standard data collection of fuel flow rate, etc. The average gas composition was found to be CO 15 1.0 % H-2 16 +/- 1% CH4 0.5 +/- 0.1 % CO2 12.0 +/- 1.0 % and rest N2 compared to CO 19 +/- 1.0 % H-2 17 +/- 1.0 %, CH4 1 +/- 0.2 %, CO2 12 +/- 1.0 % and rest N2. The tar and particulate content in the clean gas has been found to be about 10 and 12 mg/m3 in both cases. The presence of high ash content material increased the pressure drop with coconut frond compared to woody biomass.

SWEETENING OF BIOGAS IN SPRAY TOWERS FOR POWER GENERATION

This paper presents the experience of the new design of using impinging jet spray columns for scrubbing hydrogen sulfide from biogas that has been developed by Indian Institute of Science and patented. The process uses a chelated polyvalent metal ion which oxidizes the hydrogen sulfide to sulfur as a precipitate. The sulfur generated is filtered and the scrubbing liquid recycled after oxidation. The process involves in bringing contact the sour gas with chelated liquid in the spray columns where H2S reacts with chelated Fe3+ and precipitates as sulfur, whereas Fe3+ gets reduced to Fe2+. Fe2+ is regenerated to Fe3+ by reaction of oxygen in air in a separate packed column. The regenerated liquid is recirculated. Sulfur is filtered and separated as a byproduct. The paper presents the experience in using the spray towers for hydrogen sulfide removal and further use of the clean gas for generating power using gas engines. The maximum allowable limit of H2S for the gas engine is 200 ppm (v/v) in order to prevent any corrosion of engine parts and fouling of the lubricating oil. With the current ISET process, the hydrogen sulfide from the biogas is cleaned to less than 100 ppm (v/v) and the sweet gas is used for power generation. The system is designed for 550 NM3/hr of biogas and inlet H2S concentration of 2.5 %. The inlet concentration of the H2S is about 1 - 1.5 % and average measured outlet concentration is about 30 ppm, with an average gas flow of about 300 - 350 NM3/hr, which is the current gas production rate. The sweet gas is used for power generation in a 1.2 MWe V 12 engine. The average power generation is about 650 - 750 kWe, which is the captive load of the industry. The plant is a CHP (combined heat power) unit with heat from the cylinder cooling and flue being recovered for hot water and steam generation respectively. The specific fuel consumption is 2.29 kWh/m(3) of gas. The system has been in operation for more than 13,000 hours in last one year in the industry. About 8.4 million units of electricity has been generated scrubbing about 2.1 million m3 of gas. Performance of the scrubber and the engine is discussed at daily performance level and also the overall performance with an environment sustenance by precipitating over 27 tons of sulfur.

BIOMASS GASIFICATION TO SUBSTITUTE FOSSIL FUEL IN FOOD INDUSTRY

Food industries like biscuit and confectionary use significant amount of fossil fuel for thermal energy. Biscuit manufacturing in India is carried out both by organized and unorganized sector. The ratio of organized to unorganized sector is 60 : 40 (1). The total biscuit manufacturing in the organized sector India in 2008 was about 1.7 million metric tons (1). Accounting for the unorganized sector in India, the total biscuit manufacturing would have been about 2.9 million metric tons/annum. A typical biscuit baking is carried in a long tunnel kiln with varying temperature in different zones. Generally diesel is used to provide the necessary heat energy for the baking purpose, with temperature ranging from 190 C in the drying zone to about 300 C in the baking area and has to maintain in the temperature range of +/- 5 C. Typical oil consumption is about 40 litres per ton of biscuit production. The paper discusses the experience in substituting about 120 lts per hour kiln for manufacturing about 70 tons of biscuit daily. The system configuration consists of a 500 kg/hr gasification system comprising of a reactor, multicyclone, water scrubbers, and two blowers for maintaining the constant gas pressure in the header before the burners. Cold producer gas is piped to the oven located about 200 meters away from the gasifier. Fuel used in the gasification system is coconut shells. All the control system existing on the diesel burner has been suitably adapted for producer gas operation to maintain the total flow, A/F control so as to maintain the temperature. A total of 7 burners are used in different zones. Over 17000 hour of operation has resulted in replacing over 1800 tons of diesel over the last 30 months. The system operates for over 6 days a week with average operational hours of 160. It has been found that on an average 3.5 kg of biomass has replaced one liter of diesel.

La urna (1911) de Enrique Banchs : un cancionero argentino del siglo XX

Integran este número de la revista ponencias presentadas en Studia Hispanica Medievalia VIII : Actas de las X Jornadas Internacionales de Literatura Española Medieval, 2011, y de Homenaje al Quinto Centenario del Cancionero General de Hernando del Castillo.

El pensamiento católico medieval sobre los bosques, los animales y el subsuelo

Resumen: El autor plantea un recorrido por el pensamiento católico medieval sobre los bosques, los animales y el subsuelo. Da cuenta de cómo filósofos morales como San Antonino de Florencia, Francisco de Vitoria, Domingo de Soto y San Francisco de Asís, entre otros, contribuyeron grandemente al pensamiento económico. Luego, dedica un apartado al análisis sobre cómo la teoría del dominio y la propiedad privada se aplica a los bienes de la naturaleza. Además, el autor se refiere también a la cuestión relativa a la propiedad del subsuelo. Finalmente, destaca que en ninguno de los postulados de tales filósofos se contempla el daño a la naturaleza como tal, sino en relación al impacto sobre la persona humana y el bien común.