Author(s): Ahn, KH; Wu, XW; Liu, K; Chien, CL | Abstract: The effect of Fe doping (l20%) on the Mn site in the ferromagnetic ((Formula presented)) and the antiferromagnetic ((Formula presented)) phases of (Formula presented) has been studied. The same ionic radii of (Formula presented) and (Formula presented) cause no structure change in either series, yet conduction and ferromagnetism have been consistently suppressed by Fe doping. Colossal magnetoresistance has been shifted to lower temperatures, and in some cases enhanced by Fe doping. Doping with Fe bypasses the usually dominant lattice effects, but depopulates the hopping electrons and thus weakens the double exchange. © 1996 The American Physical Society.

Magnetic properties and colossal magnetoresistance of LaÑCaÖMnO3 materials doped with Fe

Efficient hydrogenation of stearic acid over carbon coated NiFe catalyst

The insurance industry has a giant role in the sustainable economic growth of any country. With an increase in the number of insurance buyers, it has become an absolute necessity for an insurance company to have a detailed claim analysis system in place. Claim Analysis is performed by insurance companies to distinguish between fraudulent and genuine claims. Apart from that, Claim Analysis can also be used to understand the client strata in a much better way and implement the results further during the underwriting and acceptance/denial stage of policy enrollment. The main objective of this research work is to identify meaningful and decisive factors for claim filing and acceptance in a learning context through exploratory data analysis (EDA) and feature selection techniques. Also, machine learning algorithms are applied to the datasets and are evaluated using performance metrics.

Application of machine learning and data visualization techniques for decision support in the insurance sector

State-of-the-Art Review on Advancements of Data Mining in Structural Health Monitoring

Automatic robotic system design and development for vertical hydroponic farming using IoT and big data analysis

This paper plans to develop an effective machine learning system integrated with the Internet of Things (IoT) to predict the health insurance amount. IoT in healthcare enables interoperability, mac...

Optimal feature extraction and classification-oriented medical insurance prediction model: machine learning integrated with the internet of things

In this research work. Voting is commonly related to politics and is finished with often exploitation and manual approach where voters stand to vote for his or her decisions. Manual voting may lead to malpractices sometimes.so there is a need to implement online voting system. This is for expand the technology from manual voting system to digital voting system. In this specific research our idea is to implement online voting system with features like the schemes that the specific party has implemented, based on the features we are going to vote. The main reason we need to shift from normal voting system to online voting system is that we can consume our time and can vote from anywhere through online. We have implemented this by using C# as a programming language, Microsoft SQL server 2012 and Microsoft azure as a cloud.

Online Voting System using Cloud

A survey on applications and security issues of blockchain technology in business sectors

Mossbauer spectroscopy measurements have been carried out in nano particles of Fe3O4 to understand in a detailed manner about the point defects that are present and compared with the results of the bulk magnetite. Mossbauer measurements have been carried out in the as formed magnetite nano particles and subsequent to annealing in vacuum at different temperatures. The present study elucidates the implication of point defects on the local structural and magnetic properties of magnetites in terms of deduction of hyperfine parameters of Fe ions such as valence, quadrupole splitting and magnetic hyperfine field.

Point defects aspect of magnetite nano particles as studied by Mossbauer spectroscopy

Mixture of iron with 25 wt% of hematite has been subjected to high energy ball milling and Mossbauer measurements have been carried out at room temperature in the as ball milled condition and subsequent to annealing at different elevated temperatures at a pressure of 10−6 mbar. Mossbauer results imply the dispersion of α‐Fe2O3 particles in metallic iron matrix in the as ball milled sample. Evolution of α‐Fe2O3 in to γ‐Fe2O3, Fe3O4 and FeO by means of reducing the valence of Fe ion of the oxide due to vacuum annealing in the range of 600–1000 K in this ball milled mixture has been elucidated in the present study.

R. Govindaraj

Papers

Optimal feature extraction and classification-oriented medical insurance prediction model: machine learning integrated with the internet of things

Online Voting System using Cloud

A survey on applications and security issues of blockchain technology in business sectors

Point defects aspect of magnetite nano particles as studied by Mossbauer spectroscopy

Mössbauer Studies of Local Environments of 57Fe in Iron Oxide Particles Dispersed Fe Matrix