Heart disease prediction using classification and feature selection techniques
The value of measurement age, blood pressure, weight, smoking habits, exercise, and blood serum cholesterol in predicting death and coronary cardiopathy was studied over an amount of ten years. Sixteen teams comprising 12 763 men aged 40-59 years (at the outset) from 7 countries (Yugoslavia, Finland, Italy, Kingdom of The Netherlands, Greece, USA, and Japan) were studied. the very best risk factors were found to be age, pulse blood pressure, and blood serum cholesterol concentration (related to saturated fatty acids within the diet). Variations in incidence rates couldn't be shown to be associated with characteristics of the cohorts in relative weight, smoking habits or physical activity. To design a perceptive model for heart illnesses acknowledgment using data mining strategies that are fit for enhancing the constancy of heart infections conclusion. Thereafter, we divide this data into Training and Testing Data Sets and employ Naïve Bayes technique to obtain relatively higher prediction accuracy. The primary goal of this research would be given a highly accurate prediction of Heart Disease. As we have done a combination of Genetic and Naïve Bayes Technique, the Investigation would be developed a Hybrid model of both these techniques and called it Hybrid Genetic Naïve Bayes Model for predicting high accuracy in results.
Published by: Navdeep Singh, Sonika Jindal
Author: Navdeep Singh
Paper ID: V4I2-1527
Paper Status: published
Published: March 31, 2018
Design and implementation of IoT based smart irrigation system
India is the agriculture-based country. Our ancient people completely depended on the agricultural harvesting. Agriculture is a source of livelihood of majority Indians and has the great impact on the economy of the country. In dry areas or in case of inadequate rainfall, irrigation becomes difficult. So, it needs to be automated for proper yield and handled remotely for farmer safety. Increasing energy costs and decreasing water supplies point out the need for better water management. Irrigation management is a complex decision-making process to determine when and how much water to apply to a growing crop to meet specific management objectives. If the farmer is far From the agricultural land he will not be noticed of current conditions. So, efficient water management plays an important role in the irrigated agricultural cropping systems. A low-cost alternative solution for efficient water management currently in use is drip irrigation systems that consist of an automated irrigation mechanism which turns the pumping motor ON and OFF on detecting the moisture content of the earth using the soil moisture sensor without the intervention of a human. The benefit of employing these techniques is to decrease human interference and it is quite feasible and affordable. This Smart irrigation system project is using an Arduino microcontroller, that is programmed to collect the input signal according to a moisture content of the soil and its output is given to the mobile application that will operate the pump.
Published by: Rasika Arsade, Monali Daf, Oshin Nagpure, Ritika Charpe, Alok Chauhan
Author: Rasika Arsade
Paper ID: V4I2-1367
Paper Status: published
Published: March 31, 2018
Stabilization of rammed earth with sawdust ash
Rammed earth is a technique of forming in-situ structural wall elements using rigid formwork. Advantages of rammed earth walls include flexibility in plan form, a scope for adjusting the strength and wall thickness, variety of textural finishes, lower embodied carbon and energy, etc.. The thesis deals with an extensive experimentation on sawdust ash stabilized rammed earth specimens. Two varieties of specimens (cylindrical, cubes) are to be used in the experiments. A natural soil and its reconstituted variants were used in the experimental work. Details of the experimental programme, characteristics of raw materials used in the experimental investigations, methods of preparing different types of specimens and their testing procedures are discussed in detail. The aim is to establish properties of locally available natural soil and comparing it with properties of soil suitable for rammed earth construction and effect of Sawdust ash (SDA) on properties of natural soil used for rammed earth.
Published by: Sri Vishnu Kailash. K, B. Karthick, C. Savinth Kumar
Author: Sri Vishnu Kailash. K
Paper ID: V4I2-1518
Paper Status: published
Published: March 31, 2018
Automatic car driving system for handicapped and polio-persons with the scooter handle
Nowadays in our country, the handicapped people are facing a lot of struggles in their life to survive. To overcome that, the person with handicapped is more interested in driving the bike.etc. If the case is based on the bike why can’t they ride the automatic car with the scooter handle has the steering system.
Published by: A J Reuben Thomas Raj, B Silpa
Author: A J Reuben Thomas Raj
Paper ID: V4I2-1525
Paper Status: published
Published: March 31, 2018
Mathematical treatment of enzyme kinetics using differential method
In this article, we studied the theoretical investigation of basic enzyme reactions of substrate and product concentrations. The enzyme kinetics helps in drug designing, Drug Metabolism and the determination of disassociation constants for antigen-antibody interactions in solutions. The arising physical governing system we solved by using the general ordinary differential method. The obtained results show the substrate, enzyme, substrate-enzyme, and product concentration profiles are presented with help of graphs and tables. From this study, we found that as increasing substrate value improves the rate of reaction. If the rate constant is greater than substrate concentration, the rate of reaction depends on free enzyme content and substrate amount. In a similar way, the substrate concentration is greater than rate constant the rate of reaction depends only on free enzyme content.
Published by: Kodathala Sai Varun, Kandagadla Ashok Kumar, Vunnam Rakesh Chowdary, C. S. K Raju
Author: Kodathala Sai Varun
Paper ID: V4I2-1534
Paper Status: published
Published: March 31, 2018
Arrhythmia classification using ECG Signal based on BFO with LMA Classifier
Electrocardiogram (ECG), a non-invasive technique is used as a primary diagnostic tool for cardiovascular diseases. ECG provides valuable information about the functional aspects of the heart and cardiovascular system. The detection of cardiac arrhythmias in the ECG signal consists of detection of QRS complex in ECG signal; feature extraction from detected QRS complexes; classification of beats using extracted feature set from QRS complexes. Earlier methods have been developed by authors to predict heart disease on the basis of ECG but as each method has its own advantage as well disadvantage. Hence, in this thesis, the best training method i.e. Levenberg Marquardt algorithm has been utilized for classification on the basis of validation checks or epochs with an optimization technique. The purpose of this research work is to classify the disease dataset using Bacterial Foraging Optimization (BFO) Algorithm and trained by Levenberg Marquardt algorithm on the basis of the features extracted and also to test the image on the basis of the features at the database and the features extracted of the waveform, to be tested. The advantage of the proposed method is to minimize the error rate of the classification which occurs due to an insignificant count of R-peaks. The database from physionet.org has been used for performance analysis. Several experiments are performed on the test dataset and it is observed that Levenberg-Marquardt Algorithm classifies ECG beats better as compared to Back Propagation Neural Network (BPNN). FAR, FRR and accuracy parameters are used for detecting the ECG disease. The simulation process is undergone by using MATLAB simulation tool.
Published by: Shikha Sharma, Aman Kumar, Astha Gautam
Author: Shikha Sharma
Paper ID: V4I2-1528
Paper Status: published
Published: March 31, 2018
