Stroke prediction using decision trees in artificial intelligence
Artificial Intelligence has become a hot topic in the present tech-driven world. Artificial Intelligence is one of the promising technology that has been greatly evolved from the past years. Artificial intelligence (AI) aims to serve as human cognitive functions. It will be of great importance to healthcare, p by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its applications in future. AI can be applied to various types of structured and unstructured healthcare data. There are various popular AI techniques that include machine learning methods for both structured data and unstructured data, such as support vector machine, neural networks, natural language processing respectively. The disease like cancer, neurology, and stokes can be easily detected by AI. We conducted a survey about AI applications in stroke, in major areas that include detection and diagnosis, treatment, and lastly outcome prediction and prognosis evaluation. Our project is based on how we can make accurate predictions of stroke occurrence that can be of great help for the doctors. This can be time-saving. It can also serve as a helping hand for the new practitioners. The predictive algorithm that will be used will increase the efficiency of stroke prevention that will surely improve the patients’ health through early detection and treatment. The objective of this project is to have a system that can make accurate predictions on stroke so that it can be cured as early as possible. For this, we need some predictive algorithms and parameters that includes patient’s characteristics like age, gender, weight, BMW, height etc. We will have a data model that will analyze all these parameters. After having this survey, whenever a new patient will come this trained data model will compare the new parameters with it surveyed parameter with the help of learning algorithm.
Published by: Aishwarya Roy, Anwesh Kumar, Navin Kumar Singh, Shashank D
Author: Aishwarya Roy
Paper ID: V4I2-1667
Paper Status: published
Published: April 12, 2018
Internal migration of construction workers in India: Reference to Chennai city of Tamil Nadu
The migration of labor in the world is not a new phenomenon; it had started in an ancient period and is continuing. The migration labour started moving from one place to another place for the purpose of seeking the job. These labour were placed in unorganized sectors like construction, brick kilns, road, railways, plantation, agriculture, canal work, etc. The human rights of migrant labor are violated in many ways in their workplace. The main causes of migration of these people from one place to another place, poverty are one of the major causes and there is lack of job opportunity and low wage in their own village. These are the major causes of migration people of underdeveloped states like Orissa, Bihar, and Jharkhand. For the eradication of poverty, the government of India has been implemented many programme MGNREGA, SGRY, NSFW, and PDS, but these programmes are not effectively implemented in these states. So the people are migrating one place another place for seeking of the job. For the protection of migrant labour, the government formed legislation. The results were tabulated by using the logistic regression model. The present study had map out the determinants and consequences of migration in Chennai city. The study also introspected the differences between the Tamil Migrants and north Indian migrants in order to map out how far the social capital or economic sociology operates in economic activity which has not been dealt by the previous studies adequately.
Published by: Yasmeen Sultana H
Author: Yasmeen Sultana H
Paper ID: V4I2-1811
Paper Status: published
Published: April 12, 2018
Experimental investigation on self-compacting concrete by using fly ash
Self-compacting concrete is a fluid mixture suitable for placing in structures with congested reinforcement without vibration. Self-compacting concrete development must ensure a good balance between deformability and stability. Also, compactibility is affected by the characteristics of materials and the mix proportions; it becomes necessary to evolve a procedure for mix design of SCC. The paper presents an experimental procedure for the design of self-compacting concrete mixes. The test results for acceptance characteristics of self-compacting concrete such as slump flow; J-ring, V-funnel, and L-Box are presented. Further, the compressive strength at the ages of 7, 14, and 28 days was also determined and results are included here.For SSC, it is generally necessary to use superplasticizers in order to obtain high mobility. Adding a large volume of powdered material or viscosity modifying admixture can eliminate segregation. The powdered materials that can be added are flyash, silica fume, lime stone powder, glass filler and quartzite filler. Since self-compactability is largely affected by the characteristics of materials and the mix proportions, it becomes necessary to evolve a procedure for mix design of SCC.
Published by: CH. Siddarda, G. Rajinikanth, P. Ravi, M. Narender, G. Kiran Reddy, J. Amjad
Author: CH. Siddarda
Paper ID: V4I2-1734
Paper Status: published
Published: April 12, 2018
Experimental investigation of the strength of concrete by partial replacement of cement with industrial wastes
Cement the main binding ingredient in concrete is becoming expensive and its production contributing to environmental pollution by emitting CO2 gases that are the main cause of global warming so efforts are being taken to utilize local natural or solid waste resources as a supplementary cementing material.RHA is a by-product of paddy industry, highly reactive pozzolana which is produced by burning rice husk at controlled temperatures. FA is collected from the combustion air-stream exiting the power plant. Fly ash is pozzolanic, which means it’s a siliceous or siliceous-and-aluminous material that reacts with calcium hydroxide to form a cement. WGP Glass is amorphous and contains a large amount of silicon and calcium. Thus it can be claimed that it is pozzolanic or even cementitious in nature even when it is finely ground, waste glass powder is formed from grinding industry by grinding waste glass obtained from lights bulbs, bottles and so on. The details of experimental investigations are done to study the effect of replacing a portion of cement with rice husk ash, fly ash and waste glass powder is reported in this paper. The main aim of this work is to determine the optimum percentage of RHA, FA, and WGP as a partial replacement of cement for the conventional grade of concrete and to study the strength variation in its percentage replacement with RHA, WGP, and FA. The studies conducted on cement concrete reveal that 10% RHA,5 and 5% WGP give optimum results for cement replacement in concrete.
Published by: Sarmilee Patnaik, P. K Parhi
Author: Sarmilee Patnaik
Paper ID: V4I2-1577
Paper Status: published
Published: April 12, 2018
Wind speed prediction using tree ensemble
The wind energy has emerged as one of the safest growing renewable energy to address the crisis witnessed in power generation. Wind speed is an important factor in wind power production and integration. However, the complex nature of wind speed limits the dependability and induces high fluctuation in power generation. The accurate prediction of wind speed energy with minimum accepted errors will increase to harness the energy content in a wind efficiently. In recent years, machine learning algorithms are used to analyze and predict data to make better decisions. Ensemble model is one of the supervised machine learning approaches to predict numerical data. In this project, the speed of wind is predicted through XGBoost 4j package in a distributed programming environment of Apache Spark. XGBOOST is a short form of Extreme Gradient Boosting tool of supervised machine learning, where the training data set xi is used to predict a target variable Yi. The results are compared with different iterations in order to minimize the uncertainties and to evaluate the efficiency and accuracy. The main findings were that Ensemble model was the most accurate method.
Published by: Pooja Varshini R, Farzana Begum S, Saranya M, Dr. B. Vanathi
Author: Pooja Varshini R
Paper ID: V4I2-1843
Paper Status: published
Published: April 12, 2018
Design of thermostatic expansion valve to increase COP of VCR system
The thermal expansion valve is used many vapor compression refrigeration systems such as refrigerator, air- conditioner etc. Hence many techniques have been investigated on thermal expansion valve to increase COP of VCR system. COP of thermal expansion valve can be increased either by controlling the bulb pressure or by decreasing compression work. This is an attempt to design expansion valve for increased COP with respect to mass flow control of refrigerant and the particular thermal parameter which are affecting to COP. The validation of design of thermal expansion valve is planned to validate by CFD analysis.
Published by: Rathava Vinodkumar Bhilsingbhai, Snehal Trivedi, Arjun Vyas
Author: Rathava Vinodkumar Bhilsingbhai
Paper ID: V4I2-1797
Paper Status: published
Published: April 11, 2018
