A Scenario Based Impact Assessment of Trace Metals on Ecosystem of River Ganges Using Multivariate Analysis Coupled with Fuzzy Decision-Making Approach

The growing consciousness about the health risks associated with environmental pollutants has brought a major shift in global concern towards prevention of hazardous/trace metals discharge in water bodies. Majority of these trace metals gets accumulated in the body of aquatic lives, which are considered as potential indicators of hazardous content. This results in an ecological imbalance in the form of poisoning, diseases and even death of fish and other aquatic lives, and ultimately affect humans through food chain. Trace metals such as Cd, Cr, Cu, Mn, Ni, Pb and Zn originated from various industrial operations containing metallic solutions and agricultural practices, have been contributing significantly to cause aquatic pollution. The present study develops a novel approach of expressing sustainability of river’s ecosystem based on health of the fish by coupling fuzzy sensitivity analysis into multivariate analysis. A systematic methodology has been developed by generating monoplot, two dimensional biplot and rotated component matrix (using ‘Analyze it’ and ‘SPSS’ software), which can simultaneously identify critical trace metals and their industrial sources, critical sampling stations, and adversely affected fish species along with their interrelationships. A case study of assessing the impact of trace metals on the aquatic life of river Ganges, India has also been presented to demonstrate effectiveness of the model. The clusters pertaining to various water quality parameters have been identified using Principal Component Analysis (PCA) to determine actual sources of pollutants and their impact on aquatic life. The fuzzy sensitivity analysis reveals the cause-effect relationship of these critical parameters. The study suggests pollution control agencies to enforce appropriate regulations on the wastewater dischargers responsible for polluting river streams with a particular kind of trace metal(s).     

Design of novel compact anti-stiction and low insertion loss RF MEMS switch

A novel torsional RF MEMS capacitive switch design on silicon substrate is presented. The optimized switch topology such as reduction in up-state capacitance results in insertion loss better than ?0.1 dB till 20 GHz. Off to on state capacitance ratio is also improved by 18 fold and isolation is better than ?43 dB at 9.5 GHz. The achieved on state return loss is ?38 dB as compared to ?21 dB at 9.5 GHz. An optimized reduction in contact area and use of floating metal layer increases the switching speed from 56 to 46 μsec. It also increases the switch reliability by alleviating the stiction.     

Absorption of oxygen by 2-ethylhexaldehyde

The kinetics of absorption of oxygen by 2-ethylhexaldehyde dissolved in 2-ethylhexanoic acid at concentrations up to 1.38 × 10^?3 mole/cm³ (20 wt.-%), in the presence of manganese acetate, was studied in a stirred cell and in bubble and packed bubble columns. Diffusion of oxygen was found to play a major role. The reaction was first order in oxygen and second order with respect to the aldehyde, and the overall third-order rate constant was found to be 2.98 × 10⁷ cm⁶ mole^?2 sec^?1 at 30°. The effect of cobaltous acetate on the specific rate of absorption of oxygen was also studied and manganese acetate was found to be the better catalyst.     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Wavelet based sub-band parameters for classification of unaspirated Hindi stop consonants in initial position of CV syllables

This paper proposes a new feature extraction technique using wavelet based sub-band parameters (WBSP) for classification of unaspirated Hindi stop consonants. The extracted acoustic parameters show marked deviation from the values reported for English and other languages, Hindi having distinguishing manner based features. Since acoustic parameters are difficult to be extracted automatically for speech recognition. Mel Frequency Cepstral Coefficient (MFCC) based features are usually used. MFCC are based on short time Fourier transform (STFT) which assumes the speech signal to be stationary over a short period. This assumption is specifically violated in case of stop consonants. In WBSP, from acoustic study, the features derived from CV syllables have different weighting factors with the middle segment having the maximum. The wavelet transform has been applied to splitting of signal into 8 sub-bands of different bandwidths and the variation of energy in different sub-bands is also taken into account. WBSP gives improved classification scores. The number of filters used (8) for feature extraction in WBSP is less compared to the number (24) used for MFCC. Its classification performance has been compared with four other techniques using linear classifier. Further, Principal components analysis (PCA) has also been applied to reduce dimensionality.     

Energy savings by reduced mixing in aeration tanks: results from a full scale investigation and long term implementation at Avedoere wastewater treatment plant

The aim of this project was to investigate the potential of reducing number of mixers in the biological treatment process and thereby achieve energy and economical savings and contribute to cleaner environment. The project was carried out at Avedoere wastewater treatment plant and a full scale investigation was conducted to study the effect of reduced mixing on flow velocity, suspended solid sedimentation, concentration gradients of oxygen and SS with depth and treatment efficiency. The only negative effect observed was on flow velocity; however the velocity was above the critical velocity. The plant has been operating with 50% of its designed number of mixers since September 2007 and long term results also confirm that reduced mixing did not have any negative effect on treatment efficiency. The estimated yearly electricity saving is 0.75 GWh/year.     

Discussion of the enabling environments for decentralised water systems

Decentralised water supply systems are becoming increasingly affordable and commonplace in Australia and have the potential to alleviate urban water shortages and reduce pollution into natural receiving marine and freshwater streams. Learning processes are necessary to support the efficient implementation of decentralised systems. These processes reveal the complex socio-technical and institutional factors to be considered when developing an enabling environment supporting decentralised water and wastewater servicing solutions. Critical to the technological transition towards established decentralised systems is the ability to create strategic and adaptive capacity to promote learning and dialogue. Learning processes require institutional mechanisms to ensure the lessons are incorporated into the formulation of policy and regulation, through constructive involvement of key government institutions. Engagement of stakeholders is essential to the enabling environment. Collaborative learning environments using systems analysis with communities (social learning) and adaptive management techniques are useful in refining and applying scientists' and managers' knowledge (knowledge management).