Polyhydroxybutyrate production accompanied by the effective reduction of chemical oxygen demand (COD) and biological oxygen demand (BOD) from industrial effluent

K. V. Radha,Ramanathan Muralidharan,Pillaibakkam Bahukudumbi Sindhuja,Aswathi Sudalai 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.12

Industrial effluents are major pollution-causing agents for our environment. Our study focuses on utilizing effluents from different industries for efficient production of Polyhydroxybutyrate (PHB). Presence of PHB was identified by Sudan Black staining method. The PHB production parameters for Pseudomonas aeruginosa MTCC 4673were studied critically, and it was found that glucose with 8.5 mg/L (0.0550 g PHB/g substrate) PHB concentration yielded the highest among the carbon sources used. Peptone with 8.9 mg/L (0.0524 g PHB/g substrate) of PHB concentration,an incubation period of 48 h and at a pH of 7 yielded the optimum results. These studies were compared with those of Alcaligens latus MTCC 2311. Dairy effluents (DE) and tannery effluents (TE) were considered for the best possible substrate, for the production of PHB in an optimized media. The results indicated that the dairy effluents gave a higher yield of PHB. Amongst various dilution levels studied from 10-100% (v/v), 50% (v/v) concentration of the dairy effluent showed maximum PHB productivity of 0.0582 g PHB/g substrate. A comparison of the chemical oxygen demand (COD) and biological oxygen demand (BOD) from the results, showed a significant removal percentage of 78.97% BOD and 53.482% COD, which highlighted the importance of utilizing effluents for PHB production, in order to reduce the risk of toxic effluent discharge. FT-IR analysis was carried out to confirm the presence of PHB.

Speech Query Recognition in Tamil Language Using Wavelet and Wavelet Packets

P. Iswarya,V. Radha 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5

Speech recognition is one of the fascinating fields in the area of Computer science. Accuracy of speechrecognition system may reduce due to the presence of noise present in speech signal. Therefore noise removalis an essential step in Automatic Speech Recognition (ASR) system and this paper proposes a new techniquecalled combined thresholding for noise removal. Feature extraction is process of converting acoustic signalinto most valuable set of parameters. This paper also concentrates on improving Mel Frequency CepstralCoefficients (MFCC) features by introducing Discrete Wavelet Packet Transform (DWPT) in the place ofDiscrete Fourier Transformation (DFT) block to provide an efficient signal analysis. The feature vector isvaried in size, for choosing the correct length of feature vector Self Organizing Map (SOM) is used. As asingle classifier does not provide enough accuracy, so this research proposes an Ensemble Support VectorMachine (ESVM) classifier where the fixed length feature vector from SOM is given as input, termed asESVM_SOM. The experimental results showed that the proposed methods provide better results than theexisting methods.

Speech Query Recognition for Tamil Language Using Wavelet and Wavelet Packets

( P. Iswarya ),( V. Radha ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5

Speech recognition is one of the fascinating fields in the area of Computer science. Accuracy of speech recognition system may reduce due to the presence of noise present in speech signal. Therefore noise removal is an essential step in Automatic Speech Recognition (ASR) system and this paper proposes a new technique called combined thresholding for noise removal. Feature extraction is process of converting acoustic signal into most valuable set of parameters. This paper also concentrates on improving Mel Frequency Cepstral Coefficients (MFCC) features by introducing Discrete Wavelet Packet Transform (DWPT) in the place of Discrete Fourier Transformation (DFT) block to provide an efficient signal analysis. The feature vector is varied in size, for choosing the correct length of feature vector Self Organizing Map (SOM) is used. As a single classifier does not provide enough accuracy, so this research proposes an Ensemble Support Vector Machine (ESVM) classifier where the fixed length feature vector from SOM is given as input, termed as ESVM_SOM. The experimental results showed that the proposed methods provide better results than the existing methods.

Textile dye wastewater treatment using coriolus versicolor

Sathian, S.,Radha, G.,Priya, V. Shanmuga,Rajasimman, M.,Karthikeyan, C. Techno-Press 2012 Advances in environmental research Vol.1 No.2

Decolourization potential of white rot fungal organism, coriolus versicolor, was investigated in a batch reactor, for textile dye industry wastewater. The influence of process parameters like pH, temperature, agitation speed and dye wastewater concentration on the decolourization of textile dye wastewater was examined by using Response surface methodology (RSM). The maximum decolourization was attained at: pH- 6.8, temperature - $27.9^{\circ}C$, agitation speed - 160 rpm and dye wastewater concentration - 1:2. From the analysis of variance (ANOVA) results it was found that, the linear effect of agitation speed and dye wastewater concentration were significant for the decolourization of textile dye wastewater. At these optimized condition, the maximum decolourization and chemical oxygen demand (COD) reduction was found to be 64.4% and 79.8% respectively. Various external carbon sources were tried to enhance the decolourization of textile dye wastewater. It was observed that the addition of carbon source enhances the decolourization of textile dye wastewater. Kinetics of textile dye degradation process was studied by first order and diffusional model. From the results it was found that the degradation follows first order model with $R^2$ value of 0.9430.

Speech Query Recognition for Tamil Language Using Wavelet and Wavelet Packets

Iswarya, P.,Radha, V. Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.5

Speech recognition is one of the fascinating fields in the area of Computer science. Accuracy of speech recognition system may reduce due to the presence of noise present in speech signal. Therefore noise removal is an essential step in Automatic Speech Recognition (ASR) system and this paper proposes a new technique called combined thresholding for noise removal. Feature extraction is process of converting acoustic signal into most valuable set of parameters. This paper also concentrates on improving Mel Frequency Cepstral Coefficients (MFCC) features by introducing Discrete Wavelet Packet Transform (DWPT) in the place of Discrete Fourier Transformation (DFT) block to provide an efficient signal analysis. The feature vector is varied in size, for choosing the correct length of feature vector Self Organizing Map (SOM) is used. As a single classifier does not provide enough accuracy, so this research proposes an Ensemble Support Vector Machine (ESVM) classifier where the fixed length feature vector from SOM is given as input, termed as ESVM_SOM. The experimental results showed that the proposed methods provide better results than the existing methods.

Hydrodynamic behavior of inverse fluidized bed biofilm reactor for phenol biodegradation using Pseudomonas fluorescens

Sabarunisha Begum S.,Radha K. V. 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.3

The hydrodynamic characteristic performance of an internal draft tube inverse fluidized bed biofilm reactorwas studied for the aerobic biodegradation of phenol (1,200 mg/l) using Pseudomonas fluorescens for various ratiosof settled bed volume to reactor working volume (Vb/Vr) under batchwise condition with respect to liquid phase. Theoperating parameters, such as superficial gas velocity, phase hold ups, aspect ratio and bed height, were analyzed fordifferent ratios of (Vb/Vr). The effect of biodegradation on synthetic phenolic effluent was determined from the reductionin chemical oxygen demand and phenol removal efficiency. The optimum value of (Vb/Vr)m was 0.20 for the optimalsuperficial gas velocity, Ugm=0.220 m/s with the COD reduction efficiency of 98.5% in 48 hours. The biomass andbiofilm characteristics of P. fluorescens were determined for optimal hydrodynamic operating parameters by evaluatingits biofilm dry density and thickness, bioparticle density, suspended and attached biomass concentration.