This informational collection is utilized to anticipate the odds of an event of heart assault for a patient. In the season of cutting edge smartphones contributing 12 attributes is not feasible. We play out the product metric examination on the given informational collection. In view of the investigation of information we try to bring the total number of attributes into a small figure and in the end, we may be able to choose which property can be considered and which characteristic can be disregarded. © 2017 IEEE.

Chandra Segar T

Department of Digital Communications

School of Information Technology and Engineering

Vellore Campus

Anudeep duba

Rajasekhar reddy

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)

In the rural side, there is the absence of centers for cardiovascular ailment. Due to this, around 12 million people passing worldwide reported by WHO. The principal purpose of coronary illness is a propensity for smoking. ML classifiers are applied to predict the risk of cardiovascular disease. However, the ML model has some inherent problems like it’s serene to feature selection, splitting attribute, and imbalanced datasets prediction. Most of the mass datasets have multi-class labels, but their combinations are in different proportions. In this paper, we experiment with our system with Cleveland’s heart samples from the UCI repository. Our cluster-based DT learning (CDTL) mainly includes five key stages. At first, the original set has partitioned through target label distribution. From the high distribution samples, the other possible class combination has made. For each class-set combination, the significant features have identified through entropy. With the significant critical features, an entropy-based partition has made. At last, on these entropy clusters, RF performance is made through significant and all features in the prediction of heart disease. From our CDTL approach, the RF classifier achieves 89.30% improved prediction accuracy from 76.70% accuracy (without CDTL). Hence, the error rate of RF with CDTL has significantly reduced from 23.30 to 9.70%. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Evolutionary Intelligence

Optimal feature selection through a cluster-based DT learning (CDTL) in heart disease prediction

This paper is carried on the heuristic prediction of rainfall using machine learning techniques. As we know agriculture was the predominant of our country and economy. While a regular rain pattern is usually played vital for healthy agriculture but too much rainfall or too little rainfall can be harmful, even it led to devastating of crops. This paper discusses the rate of rainfall in previous years according to various crops seasons like rabi, Kharif, zaid and predicts the rainfall in future seasons. The paper also measures the different categories of data by linear regression method in metrics for effective understanding of agriculture in India. We have selected a real dataset which consists of past year's rainfall rate according to various seasons. Results of this application help farmers to make a correct decision to harvest a particular crop accordingly to crops seasons. Linear regression helps to find. © 2017 IEEE.

2017 International Conference on Trends in Electronics and Informatics (ICEI)

Heuristic prediction of rainfall using machine learning techniques

In statistical analysis, we have a collection of data, with the use of these data, we have to do analysis based on our requirements. With the collection of data using Statistical analysis, we deal collection, analysis, presentation and organizing the data. With the help of statistical analysis, we can find underlying patterns, relationships, and trends between data samples. The R system for statistical computing is an environment for data analysis and graphics. Here we are going to implement boxplot method and control chart methods for sales analysis in a stationary shop dataset. With the help of boxplot, we can easily make relations between samples and we can find the outliers. © 2017 IEEE.

Data analysis using box and whisker plot for stationary shop analysis

Nature inspired algorithm

This paper is to predict the real-time data of aggregated maximum temperature (1.2 m above sea level) data from more than 350 stations spread over the country resulting in global warming. The time series we have taken from the year 1970 to 2011 shows a global warming over India during the recent years, with 5 attributes. © 2017 IEEE.

Analysis of global warming in India over maximum temperature using Pearson and machine learning

In the computing world, the digital transformation of data grows exponentially with every year. However, these situations are predominantly tackled by leading enterprises through by adopting a hybrid IT model. This model effectively supports the organization through strategic design to provide standard delivery to customers from independent multi-sourced entities. An experimental design method is applied using hybrid IT architecture with gene-based cryptomata (HITAGC) which is well suited to real-time cloud environments to store and retrieve the cloud space data efficiently. The CSC primarily relies on the service of CSP to keep their confidential data, and this system ultimately uses the PKC crypts. To address this security demand, we propose two different schemes such as HITAGC-PKC and hybrid HITAGC. The first model is designed to generate robust asymmetric keys for the Internet of Things, and the other hybrid HITAGC is for efficient sharing of big data over the cloud in a secure manner. The performance of these crypts is compared with the traditional systems like standard RSA, ESRKGS, SED2, EDCon, and AES. © 2018, Springer-Verlag London Ltd., part of Springer Nature.

Service Oriented Computing and Applications

Hybrid IT architecture by gene-based cryptomata (HITAGC) for lightweight security services

This paper mainly focuses on the design aspects of force balance measurement system for aerodynamic vehicle flying at hypersonic speed. When the speed of vehicle is hypersonic, additional aerodynamic heating creates difficulty in the system and needs change in the design geometry and material type .For the purpose of examining the model we have considered a simulation of blunt cone with following parameters like, length of the string, diameter of string, material of string, drag coefficient, pressure, velocity, density of air, Mach number, Reynolds’s number, stagnation enthalpy were suitably selected. CFD is used as a tool to calculate the drag force generated under the hypersonic conditions. A measurement system was developed for measuring the strain developed in the blunt cone when it is subjected to shock force. The measurement system was calibrated statically using hang weight and dynamically using impact load test performed on the string, from the calibration test impulse response function is calculated. And a fuzzy predication based approach was developed to predict the strain developed in the system.

Materials Today: Proceedings

One-Dimension Force Balance System for Hypersonic Vehicle an experimental and Fuzzy Prediction Approach

IoT devices are everywhere. Shortly, every 'thing' is going to be connected and interact with each other. What are these things? They can be your microwaves, heaters, air conditioners or even your refrigerators. It assessed that there would be 50 billion connected IoT devices by 2020 which is about 7 IoT gadgets for every individual on the planet. IoT devices are low powered devices which have a minimal amount of processing capabilities. With ever increasing number of IoT devices, there is a subsequent need for secure communication among them. In this paper, we aim to propose an encryption algorithm used for secure communication by taking into account the limitations of IoT devices. © 2017 IEEE.

2017 Innovations in Power and Advanced Computing Technologies (i-PACT)

Multi key distribution scheme by diophantine form for secure IoT communications

Decision making is a difficult task over the complex, spirited and competitive environment. A variety of research provides diverse notification for individual failure in making logical decisions under certain circumstances by applying normative approaches. In today's competitive market, the advance of technology is closely related to consumer needs for the extraction of good quality products at less cost which is in rarely finding a model in Consumer to Business (C2B). The aim of the paper is to optimize the C2B model by intuitionistic Fuzzy to resolve multi decision making problems. It derives multi criteria decision making to support complex environments in C2B using membership and non-membership attributes which is built to generate the intuitionistic fuzzy priority weighting vector based on minimum distance and similarity measures. This technique classifies the object type as per the customer needs with a ranking in the optimized way make efficient for the customer satisfaction. © 2017 IEEE.

2017 4th International Conference on Electronics and Communication Systems (ICECS)

An assessment framework of intuitionistic fuzzy network for C2B decision making

This work aims to study the relation between Precipitation and six of its various climatic factors. The analysis shows how much is the contribution of Reference Crop Evapotranspiration, Average Temperature, Wet Day frequency, Potential Evapotranspiration, Vapor Pressure and the Cloud Cover towards precipitation. For the purpose of finding the percentage of contribution by every parameter on Precipitation, we use a method called Analytical Hierarchical Processing. Basically, Analytical Hierarchical Processing is used for decision making. © 2017 IEEE.

Journal	Data powered by Typeset2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)
Publisher	Data powered by TypesetIEEE
Open Access	0