Abusive Words Detection in Online Conversations Using Machine Learning
Authors: Avanthi Kothakonda, Dr. M. Jagadeeshwar
Abstract
According to a new WHO (World Health Organization) report, 17.9 million people die each year from heart-related diseases, and the number is steadily rising. With the increasing population and disease, it is become a challenge to diagnosing disease and providing the appropriate treatment at the right time. But there is a light of hope that recent advances in technology have accelerated the public health sector by developing advanced functional biomedical solutions. This paper examines the various machine learning techniques for heart disease prediction, such as Naive Bayes, Random Forest Classification, Decision Tree, and Support Vector Machine, using a trained dataset that includes attributes such as gender, age, chest pain type, blood pressure, blood sugar, and so on. The research includes finding the correlations between the various attributes of the dataset by utilizing the standard data mining techniques and hence using the attributes suitably to predict the chances of a heart disease. These machine learning techniques take less time for the prediction of the disease with more accuracy which will reduce the dispose of valuable lives all over the world. It can be concluded that Gaussian Naive Bayes and Random Forest are the best algorithms for this data set and possibly other heart disease data sets. For the proper conclusion for this study to be applied clinically, it needs to be further elaborated with the help of experts in both heart and machine leaning domains.
Paradigm shift of Education towards AR and VR tools
Author: R. Nalini
Abstract
COVID-19 Pandemic showed the world the power of Technology in business as well education sphere and it has been growing fast and noticeably influencing different aspects of education. Many studies have proved that (AR) and virtual reality (VR) is the way forward in helping students to improve their skills and knowledge. We criticize the importance of AR/VR and latest improvements to upgrade the skills and values in educational domain.
IOT Based Weather Monitoring System Using Arduino
Authors: J Sri Ram Pavan, P. V. Sai Abhishek, P. Ganapathi Swamy, P. Surya, P. Pavan Kumar
Abstract
Now-a-days many weather reporting applications are available which givesus information about climatic changes that are going to take place by which man can be aware of present and 4 future climatic changes. Most of the weather reporting applications extracts the data from accurate weather system. Here we are building our own weather reporting system which would give us information about present temperature, humidity etc. We can setup this in our home and get time to time changes in climate which would help us in planning our daily work easily. Like It would be helpful fora farmer in this agricultural activity by which he can protect his crops climatic changes. It would help in transportation giving information of weather conditions etc
Construction of Pavers Using Demolished and Waste Materials
Authors: Pradeep Kumar Chaudhary, Prakhar Singh, Sajjad Alam, Prof. Nikhil
Abstract
India is a developing country, and in several other developing countries similar to Indian country economic building material along with economic construction plays a dynamic role in the construction of countries in overall expansion. Building waste material in the building construction sector can show a good role to make it durable and economical due to some of its specific properties relevant to construction materials. The concrete waste was crushed by a laboratory jaw crusher, and after crushing it by laboratory jaw crusher, it can be used as coarse aggregates replacement in the two stages as complete 100 percent replacement and 40 percent partial replacement by IS requirements in paver blocks. Near about twelve to fourteen million of tons per year, waste is generated from the construction. An activity like construction, renovation and demolition is the main reason for the production of waste concrete in huge amount. In this study, the representation of the concept of sustainable use of concrete waste in concrete was used in the manufacturing of interlocking paver blocks with Polymeric material (PET). In this study, analysis was carried out on the properties such as compressive strength, splitting tensile strength and water absorption test to develop paver block along with polymeric materials in different percentages that are 1%, 3% and 5%.
Heart Disease Prediction Using Machine Learning Algorithms
Author: Nivedita Singh
Abstract
According to a new WHO (World Health Organization) report, 17.9 million people die each year from heart-related diseases, and the number is steadily rising. With the increasing population and disease, it is become a challenge to diagnosing disease and providing the appropriate treatment at the right time. But there is a light of hope that recent advances in technology have accelerated the public health sector by developing advanced functional biomedical solutions. This paper examines the various machine learning techniques for heart disease prediction, such as Naive Bayes, Random Forest Classification, Decision Tree, and Support Vector Machine, using a trained dataset that includes attributes such as gender, age, chest pain type, blood pressure, blood sugar, and so on. The research includes finding the correlations between the various attributes of the dataset by utilizing the standard data mining techniques and hence using the attributes suitably to predict the chances of a heart disease. These machine learning techniques take less time for the prediction of the disease with more accuracy which will reduce the dispose of valuable lives all over the world. It can be concluded that Gaussian Naive Bayes and Random Forest are the best algorithms for this data set and possibly other heart disease data sets. For the proper conclusion for this study to be applied clinically, it needs to be further elaborated with the help of experts in both heart and machine leaning domains.