Performance of DF Incremental Relaying with Energy Harvesting Relays in Underlay CRNs

In this paper, we analyze the throughput performance of incremental relaying using energy harvesting (EH) decode-and-forward (DF) relays in underlay cognitive radio networks (CRNs). The destination combines the direct and relayed signals when the direct link is in outage. From the derived closed-form expressions, we present an expression for the power-splitting parameter of the EH relay that optimizes the throughput performance. We demonstrate that relaying using EH DF relays results in better performance than direct signalling without a relay only when the destination combines the direct signal from the source with the relayed signal. Computer simulations demonstrate accuracy of the derived expressions

An Experimental Study of Hydraulic Jump Due to Moving Jet Impingement

The objective of this project work is to study experimentally the hydraulic jump with a moving jet impingement on a glass plate surface. The jet strikes the horizontally placed glass plate and the jump occur which is investigated with different flow rate and discussed here in detail. Hydraulic jump of two different variety has been observed in this study when jet is stationary with respect to horizontal glass plate and moving. When jet is stationary with higher angle of jet inclination, smooth curve is appeared at the jump location, and for lower angle of jet inclination, curve with sharp change in profile is observed. Radius of hydraulic jump and the profile formed due to variation in flow rate are studied experimentally. When jet is in still condition we found that the radius of hydraulic jump increases with the flow rate and elliptical shape is formed due to jet inclination and when it moves normally with respect to horizontal glass plate a semicircular shape occur in the direction of jet movement. The result are found out for hydraulic jump with variation of flow rate through graph and validate with existing results of literature. The jet is moved by the means of slider crank mechanis

Indirect Spectrophometric Determination of Fly-Fighter Insecticide in Agricultural & Environmental Samples.

Indirect spectrophotometric method is developed for the determination of widely used organophosphorus insecticide Fly-Fighter. The method is based on alkaline hydrolysis of Fly-Fighter to dichloroacetaldehyde followed by benzoic acid in alkaline medium. The absorption maxima of the reddish-brown dye formed is measured at 510 nm. Beer’s law is obeyed over the concentration range of 2.3 to 25 µg in a final volume of 25 ml (0.092-1.00 ppm). The molar absorptivity, Sandell’s sensitivity and correlation coefficient were found to be 1.8x104 l mole-1cm-1, 0.002 µg cm-2 and 09989 respectively. The lower limit of detection is about 0.001. The standard deviation and relative standard deviation were found to be ± 0.002 and 1.98% respectively. The method is simple sensitive and free from interferences of other pesticides and diverse ions. Other organophosphorous pesticides do not interfere with the proposed method. The method is simple, fast and has been satisfactorily applied to the determination of Fly-Fighter in agricultural & environmental samples. Key Words : Spectrophotometer, Fly-Fighter, Benzoic Acid Agricultural, Environmental Samples

Diagnosis of Breast Cancer by Modular Evolutionary Neural Networks

Abstract Machine learning and pattern recognition play a vital role in the field of biomedical engineering, where the task is to identify or classify a disease based on a set of observations. The inability of a single method to effectively solve the problem gives rise to the use multiple models for solving the same problem in a 'Mixture of Experts' mode. Further the data may be too large for any system to effectively solve the problem. This motivates the use of computational modularity in the system where a number of modules independently solve part of the problem. In this paper we construct a Mixture of Experts model where a number of different techniques are applied to solve the same problem. The individual decision by each of these experts is fused by an integrator that gives the final output. Each of the units is a complex modular neural network. The first modularity clusters the entire input space into a set of modules. The second modularity divides the number of attributes. Each cluster is a neural network that solves the problem. The individual neural networks are evolved using Genetic Algorithms which optimizes both the architecture and the parameters. The complete system is used for the diagnosis of Breast Cancer. Experimental results show that the proposed system outperforms the traditional simple and hybrid approaches. The system on the whole is highly scalable to both number of attributes and data items

A new sensitive spectrophotometric determination of cypermethrin insecticide in environmental and biological samples

A new and highly sensitive spectrophotometric method was developed for the determination of parts per million levels of widely used cypermethrin insecticide. The method is based on alkaline hydrolysis of cypermethrin to cyanide ion, which further reacts with potassium iodide and leuco crystal violet. The absorption maxima of the crystal violet dye formed was measured at 595 nm in acidic medium. Beer's law obeys over the concentration range of 3.0 to 17 µg in a final solution volume of 25 mL (0.12-0.68 ppm). The molar absorptivity and Sandell's sensitivity were found to be 3.3<FONT FACE=Symbol>&acute;</FONT>10(5) L mol-1 cm-1 and 0.054 µg cm-2, respectively. The standard deviation and relative standard deviation were found to be &plusmn; 0.001 and 0.22%, respectively. The method is simple, sensitive and free from interferences of other pesticides and diverse ions. Other pyrethroid insecticides do not interfere in the proposed method. The method has been satisfactorily applied to the determination of cypermethrin in environmental and biological samples

Performance Analysis of Machine Learning Algorithms in SMP: A Case Study of Twitter

The number of people using Social Media Platform (SMP) is increasing day by day. A few users may hide their identity with malicious intentions. Previous research has detected fake accounts created by bots using machine learning concepts. These ML concepts used engineered features such as the ‘following-to-followers ratio’ which is generally available in their accounts. In previous studies these similarly clustered features were applied to the machine learning models for detection of fake and real accounts. In the recent research the behavioural features like the sentient of the tweet posted on twitter is considered along with the parameters. Here, the ML models are also trained to use engineered features depending on behavioural data

A note on the clonal propagation of depleted threatened species Boswellia serrata Roxb. through branch cuttings

An experiment was conducted to propagate Boswellia serrata Roxb., an important pharmaceutical species, through seeds and branch cuttings to develop a method of propagation adoptable to the personnel working in forest nurseries. Successful rooting and leaves emergences was achieved through branch cuttings of up to 1m length and 4 cm diameter planted 15 cm deep into the potting mixture