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Alīgarh, India

Ganga basin is one of the world's biggest aquifer repositories. The thick alluvium of the basin hosts its three tier aquifer system. The aquifer of the basin is under high stress due to unethical human intervention in the natural system. This warrants the need to evolve the basic hydrochemistry of every bit of the basin to make a scientific planning followed by a pragmatic execution. A multivariate statistical analysis was carried in order to give the hydrochemistry of the shallow aquifer a new dimension which is easily understood at a glance. In the present paper an attempt has been made to study the hydro chemical analysis data of shallow groundwater in parts of Karwan - Sengar sub basin, Central Ganga basin. The study is made of shallow aquifer of the region in which the movement of groundwater is from northwest to southeast. The descriptive statistical analysis was done beside Pearson correlation, principle component and regression analysis. All these are synthesized here to decipher the dynamics involved in the hydrochemistry of the area. The principle component analysis identified five factors that are responsible for the data structure explaining 83.49 % of the total variance of the data set. Factor 1 to 5 explains variance of 31.23, 19.445, 13.131, 12.105 and 8.647% respectively. Regression analysis show that Electric Conductivity (EC) as an independent variable which can be used to measure Carbonate (CO 3 2-), Chloride(Cl -), Sodium (Na +), and Total Dissolve Solids (TDS). Further Magnesium (Mg 2+) can be used to calculate the Total Hardness (TH) directly in the area. © 2011 Global NEST Printed in Greece. All rights reserved. Source

Patel K.K.,Indian Agricultural Research Institute | Kar A.,Indian Agricultural Research Institute | Jha S.N.,CIPHET | Khan M.A.,AMU
Journal of Food Science and Technology | Year: 2012

Quality inspection of food and agricultural produce are difficult and labor intensive. Simultaneously, with increased expectations for food products of high quality and safety standards, the need for accurate, fast and objective quality determination of these characteristics in food products continues to grow. However, these operations generally in India are manual which is costly as well as unreliable because human decision in identifying quality factors such as appearance, flavor, nutrient, texture, etc., is inconsistent, subjective and slow. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. This inspection approach based on image analysis and processing has found a variety of different applications in the food industry. Considerable research has highlighted its potential for the inspection and grading of fruits and vegetables, grain quality and characteristic examination and quality evaluation of other food products like bakery products, pizza, cheese, and noodles etc. The objective of this paper is to provide in depth introduction of machine vision system, its components and recent work reported on food and agricultural produce. © Association of Food Scientists & Technologists (India) 2011. Source

Parveen T.,AMU
2011 International Conference on Multimedia, Signal Processing and Communication Technologies, IMPACT 2011 | Year: 2011

This paper introduces a single input multi output (SIMO) current mode universal biquadratic filter using low voltage Multioutput Operational Floating Conveyors (MOOFCs) along with grounded passive components. The circuit is constructed with two MOOFCs, and four grounded components. The circuit can realize all standard biquadratic responses i.e., low pass, high pass, band pass, band elimination and all pass filter, without any matching conditions. The filter circuit is simple in structure and has high impedance outputs enables easy cascading in current mode operations and can realize all standard high order filters. The proposed circuit also has the additional advantage of low component count, low sensitivity, and high performance at low supply voltage of ±0.75 volts. The performance of the filter is verified through PSPICE simulation. © 2011 IEEE. Source

Beg P.,AMU
The Scientific World Journal | Year: 2014

This paper presents a voltage mode cascadable single active element tunable first-order all-pass filter with a single passive component. The active element used to realise the filter is a new building block termed as differential difference dual-X current conveyor with a buffered output (DD-DXCCII). The filter is thus realized with the help of a DD-DXCCII, a capacitor, and a MOS transistor. By exploiting the low output impedance, a higher order filter is also realized. Nonideal and parasitic study is also carried out on the realised filters. The proposed DD-DXCCII filters are simulated using TSMC the 0.25 μm technology. © 2014 Parveen Beg. Source

Muzzammil M.,AMU
Journal of Hydroinformatics | Year: 2010

An accurate estimation of the maximum possible scour depth at bridge abutments is of paramount importance in decision-making for the safe abutment foundation depth and also for the degree of scour counter-measure to be implemented against excessive scouring. Despite analysis of innumerable prototype and hydraulic model studies in the past, the scour depth prediction at the bridge abutments has remained inconclusive. This paper presents an alternative to the conventional regression model (RM) in the form of an adaptive network-based fuzzy inference system (ANFlS) modelling. The performance of ANFIS over RM and artificial neural networks (ANNs) is assessed here. It was found that the ANFlS model performed best among of these methods. The causative variables in raw form result in a more accurate prediction of the scour depth than that of their grouped form. © IWA Publishing 2010. Source

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