Data Analysis of COVID-19 THE GREAT EPIDEMIC OF THE YEAR 2020 (Preprint)

2020 ◽  
Author(s):  
Sonia Singla
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
High Temperature ◽  
Data Science ◽  
Cold Climate ◽  
High Humidity ◽  
Virus Spread ◽  
The World ◽  
Almost All ◽  
Death Cases

UNSTRUCTURED What is COVID-19, and how to deal with COVID-19 during pandemic. Does it is the result of harming nature? Mostly the disease was spread from Wuhan, China and is found bat to be the cause of spreading to other animals which has infected human. Italy, Spain and almost all the world is facing the consequence of COVID-19. In India where the prevalence rate of disease is 1.9% and 2.5% incidence rate, most of the cases are being found in Kerala and Maharashtra with updated data more than 200. Now the question arises is wet and cold climate making the virus spread and can the virus be killed in high temperature and high humidity? After Italy, China more death cases have been found in Spain. Data Science plays a major role by using machine learning to solve various problems and can be used to solve various problems associated with COVID-19. For example, prediction of how many peoples in groups will get effected, which location or area is likely to be get effected, screening of patients, using chat boots for concluding how many peoples have got the symptoms and are likely to be effected and so on. In this paper we have tried to show which areas are more likely to be affected, how lockdown have helped in reduction of death and what in future we can do to not face such situation again in life.

scholarly journals Covid-19 Spread Analysis

2021 ◽  
Vol 9 (VI) ◽  
pp. 310-313
Author(s):  
Prashant Gawande
Keyword(s):  
Data Science ◽  
Virus Spread ◽  
Entire Data ◽  
Corona Virus ◽  
The World ◽  
The Right ◽  
Spread Analysis ◽  
The Impact ◽  
Death Cases

Covid-19 Spread Analysis is a stand-alone application developed in python which will help us to analyse the covid-19 cases all over the world. In this python project, we will implement a live dashboard for COVID 19 spread analysis. This dashboard will provide much insightful visualization for the study of corona virus spread. It will consist of a world map on which circles of the top 15 regions having the largest corona cases of will be displayed. There will be a table in the left panel showing the total active cases till date in the respective region. In the right panel, there will be a world map which will represent the impact of the virus using a red circle. More the number of cases in the region on the map, the bigger are the red circle in that region. Also, the user can see a detailed graph of state wise covid-19 cases of our country. This graph will show the active, confirmed, recovered and death cases. User can see all this information date wise as well as month wise. The graph will be updated every day so that user can clearly analyse the covid-19 spread. The project aims to understand various useful features of this tool and to present different concepts of data science applied within the application along with its importance in managing the ongoing pandemic. . It gives the readers an insight in to covid-19 spread is happening with the help of the entire data.

How Should Data Science Education Be?

2020 ◽  
Vol 9 (2) ◽  
pp. 25-36
Author(s):  
Necmi Gürsakal ◽  
Ecem Ozkan ◽  
Fırat Melih Yılmaz ◽  
Deniz Oktay
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Science Education ◽  
Data Science ◽  
Doctoral Programs ◽  
Time Data ◽  
High Demand ◽  
The Core ◽  
The World ◽  
The Subject

The interest in data science is increasing in recent years. Data science, including mathematics, statistics, big data, machine learning, and deep learning, can be considered as the intersection of statistics, mathematics and computer science. Although the debate continues about the core area of data science, the subject is a huge hit. Universities have a high demand for data science. They are trying to live up to this demand by opening postgraduate and doctoral programs. Since the subject is a new field, there are significant differences between the programs given by universities in data science. Besides, since the subject is close to statistics, most of the time, data science programs are opened in the statistics departments, and this also causes differences between the programs. In this article, we will summarize the data science education developments in the world and in Turkey specifically and how data science education should be at the graduate level.

Data Analysis on Global Stratification

2020 ◽  
pp. 355-378
Author(s):  
Kirti Raj Bhatele ◽  
Stuti Singhal ◽  
Muktasha R. Mithora ◽  
Sneha Sharma
Keyword(s):  
Data Analysis ◽  
Data Science ◽  
Graphical Representation ◽  
Heat Maps ◽  
Python Language ◽  
Graphical Data ◽  
Sentence Form ◽  
The World ◽  
Table Data ◽  
Numeric Data

This chapter will guide you through the modeling, uses, and trends in data analysis and data science. The authors focus on the importance of pictorial data in replacement of numeric data. In most situations, graphical representation of data can present the information more distinctly, informative, and in less space than the same information requires in sentence form. This chapter provides a brief knowledge about representing data to more understandable form such that any person whether layman or not can understand it without any difficulty. This chapter also deals with the software Tableau which we use to convert the table data into graphical data. This Chapter contains 11 heat maps related to the world economies and their detailed study on several different topics. It will also give light on the basics of Python Language and its various algorithm studies to compare all the world economies based on their development.

scholarly journals Studying the capabilities of the analytical system based on the machine learning method

2020 ◽  
Vol 30 (3) ◽  
pp. 112-126
Author(s):  
S. V. Palmov
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Predictive Models ◽  
Arithmetic Mean ◽  
Machine Learning Method ◽  
Learning Method ◽  
Learning Tools ◽  
Analytical System ◽  
Reliability And Robustness ◽  
Almost All

Data analysis carried out by machine learning tools has covered almost all areas of human activity. This is due to a large amount of data that needs to be processed in order, for example, to predict the occurrence of specific events (an emergency, a customer contacting the organization’s technical support, a natural disaster, etc.) or to formulate recommendations regarding interaction with a certain group of people (personalized offers for the customer, a person’s reaction to advertising, etc.). The paper deals with the possibilities of the Multitool analytical system, created based on the machine learning method «decision tree», in terms of building predictive models that are suitable for solving data analysis problems in practical use. For this purpose, a series of ten experiments was conducted, in which the results generated by the system were evaluated in terms of their reliability and robustness using five criteria: arithmetic mean, standard deviation, variance, probability, and F-measure. As a result, it was found that Multitool, despite its limited functionality, allows creating predictive models of sufficient quality and suitable for practical use.

scholarly journals Analisis Pesan Visual Bahaya Virus Covid-19 Dalam Film Animasi “ Larva”

2021 ◽  
Vol 3 (3) ◽  
pp. 161-168
Author(s):  
Hasbullah Hasbullah ◽  
Andi Sofyan Anas ◽  
Anak Agung Gde Agung Indrawan ◽  
Tomi Tri Sujaka
Keyword(s):  
Data Analysis ◽  
Study Data ◽  
Observation Data ◽  
Literature Study ◽  
Hand Sanitizer ◽  
Analysis Techniques ◽  
Community Activities ◽  
Visual Message ◽  
The World ◽  
Almost All

The COVID-19 pandemic has paralyzed all activities and economies in almost all land areas of the world. The paralysis of community activities in various places disturbs creative ideas emerging through visual communication media, one of which is the animation of Larva from South Korea. The problem to be raised in this paper is about how the form of visual messages conveyed through Larva animation. The purpose of this article is for the audience to understand the message that is hidden behind the Larva animation. The method used in this paper is qualitative with observation data collection techniques or direct observation of Larva animation videos and literature study. Data analysis techniques, namely, reduction, presentation, and drawing conclusions based on the semiotic theory of Raland Barthes. The results presented in this paper lead to a visual message that displays the shape at the denotative level of the covid-19 virus in red to purple plus the effect of a dirty brown color that attacks larvae that are eating without implementing health protocols so that the Larva cough and spread the virus a group of larvae. which is enjoying food and immediately dies, then attacks the two red and yellow Larva. However, they apply health protocols such as washing hands using hand sanitizer and wearing masks. Connotatively, this visual message illustrates the importance of implementing health protocols during this COVID-19 period.

scholarly journals Correlation Between Temperature and COVID-19 (Suspected, Confirmed and Death) Cases based on Machine Learning Analysis

2020 ◽  
Vol 14 (suppl 1) ◽  
pp. 1017-1024 ◽  
Author(s):  
Mohammad Khubeb Siddiqui ◽  
Ruben Morales-Menendez ◽  
Pradeep Kumar Gupta ◽  
Hafiz M.N. Iqbal ◽  
Fida Hussain ◽  
...  
Keyword(s):  
Machine Learning ◽  
World Health ◽  
Effect Of Temperature ◽  
Machine Learning Method ◽  
Contributing Factors ◽  
Data Set ◽  
The World ◽  
Health Organization ◽  
Death Cases ◽  
Learning Analysis

Currently, the whole world is struggling with the biggest health problem COVID-19 name coined by the World Health Organization (WHO). This was raised from China in December 2019. This pandemic is going to change the world. Due to its communicable nature, it is contagious to both medically and economically. Though different contributing factors are not known yet. Herein, an effort has been made to find the correlation between temperature and different cases situation (suspected, confirmed, and death cases). For a said purpose, k-means clustering-based machine learning method has been employed on the data set from different regions of China, which has been obtained from the WHO. The novelty of this work is that we have included the temperature field in the original WHO data set and further explore the trends. The trends show the effect of temperature on each region in three different perspectives of COVID-19 – suspected, confirmed and death.

Impact Analysis of Machine Learning Techniques for COVID-19 Diagnosis: A Critical Review

2021 ◽  
Vol 12 (2) ◽  
pp. 510-516
Author(s):  
Anshul, Et. al.
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Severe Acute Respiratory Syndrome ◽  
Impact Analysis ◽  
Machine Learning Techniques ◽  
X Ray ◽  
Learning Techniques ◽  
The World ◽  
Almost All

COVID-19 virus belongs to the severe acute respiratory syndrome (SARS) family raised a situation of health emergency in almost all the countries of the world. Numerous machine learning and deep learning based techniques are used to diagnose COVID positive patients using different image modalities like CT SCAN, X-RAY, or CBX, etc. This paper provides the works done in COVID-19 diagnosis, the role of ML and DL based methods to solve this problem, and presents limitations with respect to COVID-19 diagnosis.

scholarly journals How pandemic affects occupants’ buildings perception: questionnaires investigation and preliminary results

2021 ◽  
Vol 312 ◽  
pp. 02011
Author(s):  
Iole Nardi ◽  
Domenico Palladino
Keyword(s):  
Energy Losses ◽  
Virus Spread ◽  
Economic Activities ◽  
Thermal Discomfort ◽  
Exponential Increase ◽  
Multi Stage ◽  
The World ◽  
Before And After ◽  
Smart Working ◽  
Almost All

The COVID-19 pandemic has changed the living habits all over the world. Countries experienced multiple lockdowns, causing offices, restaurants, school and almost all the economic activities to close. The saying “stay home stay safe”, to which we were invited for preventing the virus spread, and the rise of smart-working, lead to an exponential increase in the time spent in our homes. In this sense, the way to live our homes has changed. Spaces and rooms that (before pandemic) were occupied for just a few hours a day, have become the main places for studying, working, playing or even have fitness. More than ever, people had to face the energy related problems of their house: air leakages, energy losses, expensive billings, and thermal discomfort. This study arises from considerations on buildings use after the pandemic, and it addresses the consequences of COVID-19 to building perception. Anonymous questionnaires were proposed broad wide, asking through a multi-stage survey to compare the feeling before and after the pandemic, also in comparison to the billing of the energy carriers. Results have been analysed, showing how the pandemic has changed the living perception.

scholarly journals The democratization of data science education

2017 ◽  
Author(s):  
Sean Kross ◽  
Roger D Peng ◽  
Brian S Caffo ◽  
Ira Gooding ◽  
Jeffrey T Leek
Keyword(s):  
Machine Learning ◽  
Science Education ◽  
Data Analysis ◽  
Data Science ◽  
Online Data ◽  
The Past ◽  
The Us ◽  
Science Curricula ◽  
The Impact ◽  
And Training

Over the last three decades data has become ubiquitous and cheap. This transition has accelerated over the last five years and training in statistics, machine learning, and data analysis have struggled to keep up. In April 2014 we launched a program of nine courses, the Johns Hopkins Data Science Specialization, which has now had more than 4 million enrollments over the past three years. Here the program is described and compared to both standard and more recently developed data science curricula. We show that novel pedagogical and administrative decisions introduced in our program are now standard in online data science programs. The impact of the Data Science Specialization on data science education in the US is also discussed. Finally we conclude with some thoughts about the future of data science education in a data democratized world.

scholarly journals Scientific Publications of Lecturers in University of Education, Vietnam National University in the Period 2010-2019: Data Analysis Approach

2019 ◽  
Author(s):  
Bui Thi Thanh Huong ◽  
Tran Van Cong ◽  
Nguyen Ha Nam ◽  
Tran Xuan Quang
Keyword(s):  
Data Analysis ◽  
Data Science ◽  
Scientific Data ◽  
Data Preparation ◽  
Scientific Publications ◽  
Policy Makers ◽  
The World ◽  
National University ◽  
University Lecturers ◽  
The University

Teaching and scientific research are two main tasks that interact which help university lecturers improve their capacities and abilities in order to integrate with the scientific flow of the country, the region as well as the world. By approaching the data science, accurate assessments of the quantity, quality, and relationship between lecturers' scientific publications has been modeled based on published scientific data of the lecturers of University of Education in period 2010-2019. Techniques of data preparation, data analysis and data modeling were initially applied in the case of research as the system of published scientific data which has not been yet synchronized. These analytical results can be used as a basis for management levels, policy makers, and the process of developing scientific and technological capacity of officials and lecturers in the University

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