GROUPING PRECISION IS ENHANCED WITH BASIC PIECES AND CLASS LIMIT CALCULATION USING DATA CLUSTER

Organize frameworks are utilized to see the exchange stamp. Finding the cases and exceptional cases is one of the fundamental issues in the field of information mining. Particularly in the field of human organizations examination has possessed the capacity to be hard to anticipate the cases and basic power. The ask for strategies are utilized to collect the cases in the learning stage and recognize the irregularities in prepare arrange. In social security examination, depictions are restricted with two class levels as positive and negatives. The signs of patients are amassed and requested into outlines then by utilizing the cases; they see the truth level of defilements. The proposed framework in a general sense concentrates on perceiving the truth level of patients by upgrading the purpose of control depictions. The arrangement precision can be enhanced with fundamental pieces and climbing to strengthen multi class (low, medium, high and average) and different quality environment. The purpose of containment gage calculation is improved to decrease the territory multifaceted nature. Post dealing with operations are tuned to perceive classes for different gathering information environment

Dynamics of Crossover from a Chaotic to a Power Law State in Jerky Flow

We study the dynamics of an intriguing crossover from a chaotic to a power law state as a function of strain rate within the context of a recently introduced model which reproduces the crossover. While the chaotic regime has a small set of positive Lyapunov exponents, interestingly, the scaling regime has a power law distribution of null exponents which also exhibits a power law. The slow manifold analysis of the model shows that while a large proportion of dislocations are pinned in the chaotic regime, most of them are pushed to the threshold of unpinning in the scaling regime, thus providing insight into the mechanism of crossover.Comment: 5 pages, 3 figures. In print in Phy. Rev. E Rapid Communication

Effect of Demonetisation of on Indian High Denomination Currencies on Indian Stock Market and its Relationship with Foreign Exchange Rate

This study examines the impact of the foreign exchange rate, i.e., US Dollar to Indian Rupee (USD/INR) on the Indian Stock Market Index (Nifty 50) during the demonetization of high denomination Indian currencies. A daily rate of return of Foreign exchange rate (USD/INR) and the Indian Stock Market Index (Nifty 50) were considered for the study. The Dummy variable was used to measure the effect of demonetization during Nov/Dec 2016. The period of study was restricted to 243 days from 1st April 2016 to 31st March 2017. The study reveals that there was an upward trend observed in the Indian Stock Market and the Indian currency was strengthened with the decrease in the Foreign exchange rate (USD/INR).Comment: 7 pages, 5 Figures, published in International Business Management in 201

Determination of Blast Disease Using SVM And ANN Classifiers

This paper is mainly industrialized to find the blast disease and reduce the crop defeat and hence increase the paddy cultivation production in an effective manner. In modern farming field, pest and disease identification is a major role of paddy cultivation. Image classification by the use of deep convolutional neural networks of training and methodology used the facilitate a quick and easy system implementation. Pests and diseases are a threat to paddy production, especially in India, but identification remains to be a challenge in massive scale and automatically. The results show that we can effectively detect and recognize the paddy diseases and pests including healthy plant class using classifiers, with the best accuracy of 91%. The significantly high success rate makes the model a really useful advisory or early warning tool, and an approach that would be further expanded to support an unified paddy plant disease identification system to work in real cultivation conditions

Effectiveness and safety of intravenous ferric carboxy maltose in anaemic women attending gynecological unit

Background: Anaemia is a significant problem worldwide, particularly in women. Several intravenous iron preparations are available for the treatment of anaemia. Some of them cause life-threatening anaphylactic reactions while others require multiple small infusions to prevent iron reactions. Ferric carboxy maltose (FCM), a non-dextran intravenous iron, is safe and effective option that can be administered as single high dose without serious adverse effects.Methods: A prospective study was undertaken in the department of obstetrics and gynecology, Adichunchungiri institute of medical sciences, B G Nagara, from August 2020 to November 2021 in which 50 cases with iron deficiency anaemia were enrolled. IV FCM 1g was given. Change in the laboratory parameters such as haemoglobin (Hb), mean corpuscular value, serum ferritin levels over a 4 weeks period were observed.Results: A significant increase in mean Hb from 8.14 to 11.71 g was observed in patients treated with FCM after 4 weeks of therapy. Majority belonged to age group of 21-30 years and moderate type of anaemia was most common. No serious drug reaction was reported.Conclusions: IV FCM is safe and effective option for improving Hb in iron deficiency anaemia, in terms of restoring iron stores in short duration of time as well as patient compliance

Assessing Software Reliability Using Modified Genetic Algorithm: Inflection S-Shaped Model

In order to assess software reliability, many software reliability growth models (SRGMs) have been proposed in the past four decades. In principle, two widely used methods for the parameter estimation of SRGMs are the maximum likelihood estimation (MLE) and the least squares estimation (LSE). However, the approach of these two estimations may impose some restrictions on SRGMs, such as the existence of derivatives from formulated models or the needs for complex calculation. In this paper, we propose a modified genetic algorithm (MGA) to assess the reliability of software considering the Time domain software failure data using Inflection S-shaped model which is NonHomogenous Poisson Process (NHPP) based. Experiments based on real software failure data are performed, and the results show that the proposed genetic algorithm is more effective and faster than traditional algorithms

Performance Evaluation of wide Bandwidth RF Signal Generator Chip

The work in this paper is to give an overview of the compact wide band RF signal generator board design, emphasizing on the analyses and evaluation of the performance characteristics corresponding to the output signal purity and stability. The paper describes the design aspects involved in developing a reliable RF generating source which includes details regarding the factors that have taken care for optimum output power, spectral purity and noise performance. The simulation results obtained from the tool given by Maxim integrated are used as reference to evaluate the actual board when it is realised. These results are shown here for reference. Design aspects such as the power supply, noise filtering, loop filter component selection board layout consideration along with easy and compact form factor is considered. The board contains not only the signal generator device but also an FPGA from Xilinx to control the device, to make the board more useful for future applications; the board also has an SDRAM and an USB controller. This paper mainly concentrates on to MAX2870 signal generator and simulation results obtained by EE-Sim tool. Since the actual board is still in the process of being developed, the comparison of the actual performance to the simulation performance may not be possible at this point of time but definitely is in pipeline