Class prediction of the prevalent transmission mode of COVID-19 within a geographic area

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Ruth Wario ◽  
Donald Douglas Atsa'am
Keyword(s):  
Geographic Area ◽  
Transmission Mode ◽  
Class Prediction

scholarly journals Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus Within Localities

2021 ◽  
Vol 12 (6) ◽  
pp. 1-12
Author(s):  
Donald Douglas Atsa'am ◽  
Ruth Wario
Keyword(s):  
Predictive Accuracy ◽  
Multinomial Logistic Regression ◽  
Geographic Area ◽  
Stochastic Gradient ◽  
Transmission Mode ◽  
Gradient Boosting ◽  
Support Vector ◽  
Linear Discriminant ◽  
Classifier Selection ◽  
Stochastic Gradient Boosting

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include; multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, naïve Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-fold cross validation with three repeats. The Friedman’s test was conducted and the outcome showed the performance of each algorithm is significantly different. The stochastic gradient boosting yielded the highest predictive accuracy, 81%. This finding should be valuable to health informaticians, health analysts and others regarding which machine learning tool to adopt in the efforts to detect dominant transmission mode of the virus within localities.

scholarly journals Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus within Localities

2021 ◽  
Vol 12 (6) ◽  
pp. 0-0
Keyword(s):  
Predictive Accuracy ◽  
Multinomial Logistic Regression ◽  
Geographic Area ◽  
Stochastic Gradient ◽  
Transmission Mode ◽  
Gradient Boosting ◽  
Support Vector ◽  
Linear Discriminant ◽  
Classifier Selection ◽  
Stochastic Gradient Boosting

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include; multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, naïve Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-fold cross validation with three repeats. The Friedman’s test was conducted and the outcome showed the performance of each algorithm is significantly different. The stochastic gradient boosting yielded the highest predictive accuracy, 81%. This finding should be valuable to health informaticians, health analysts and others regarding which machine learning tool to adopt in the efforts to detect dominant transmission mode of the virus within localities.

Observation of surface morphology by reflection electron holography

1989 ◽  
Vol 47 ◽  
pp. 536-537
Author(s):  
N. Osakabe ◽  
J. Endo ◽  
T. Matsuda ◽  
A. Tonomura
Keyword(s):  
Phase Shift ◽  
Surface Morphology ◽  
High Sensitivity ◽  
High Energy ◽  
Path Difference ◽  
Transmission Mode ◽  
Electron Holography ◽  
Dynamical Process ◽  
High Vertical Resolution ◽  
Amplification Technique

Progress in microscopy such as STM and TEM-TED has revealed surface structures in atomic dimension. REM has been used for the observation of surface dynamical process and surface morphology. Recently developed reflection electron holography, which employes REM optics to measure the phase shift of reflected electron, has been proved to be effective for the observation of surface morphology in high vertical resolution ≃ 0.01 Å.The key to the high sensitivity of the method is best shown by comparing the phase shift generation by surface topography with that in transmission mode. Difference in refractive index between vacuum and material Vo/2E≃10-4 owes the phase shift in transmission mode as shownn Fig. 1( a). While geometrical path difference is created in reflection mode( Fig. 1(b) ), which is measured interferometrically using high energy electron beam of wavelength ≃0.01 Å. Together with the phase amplification technique , the vertivcal resolution is expected to be ≤0.01 Å in an ideal case.

Information and Communication Technologies (ICTs) for Inclusive Human Development: A Review

2017 ◽  
Vol 6 (10) ◽  
pp. 130 ◽  
Author(s):  
Rakesh Kumar Gulati ◽  
Manveen Kaur
Keyword(s):  
Human Development ◽  
Information And Communication Technologies ◽  
Rural Areas ◽  
New Technologies ◽  
Clean Energy ◽  
Geographic Area ◽  
Cognitive Responses ◽  
Information And Communications Technologies ◽  
Main Challenge ◽  
Work Family

Information and Communications Technologies (ICTs) adoption is increasing globally for human development because of its potential affect in many aspects of economic and societal activities such as GDP growth, employment, productivity, poverty alleviation, quality of life, education, clean water and sanitation, clean energy, and healthcare. Adoption of new technologies has been the main challenge in rural areas and is the main reason for the growing gap between rural and urban economy. The work related ICT use have also yielded mixed results; some studies show the individual’s perceived work-family conflict, negative cognitive responses e.g. techno stress while others show increased productivity, improved job satisfaction and work-family balance due to flexible work timings. This paper attempts to understand the role of ICT in human development areas of health, education and citizen empowerment taking into consideration of digital divide which exists in geographic area and within the communities through literature review.

Features of economic development of entrepreneurship in suburban areas of the region

2020 ◽  
pp. 22-25
Author(s):  
Viktoriya Bondarenko
Keyword(s):  
Economic Theory ◽  
Economic Development ◽  
National Economy ◽  
Geographic Area ◽  
Developed Countries ◽  
World Market ◽  
Production Costs ◽  
Goods And Services ◽  
Suburban Areas ◽  
The World

The level of economic development of entrepreneurship in any country in the world is crucial in increasing the competitiveness of the national economy in the world market of goods and services. The activities of economic entities are the driving force for the sustainable development of regions and their suburban areas, and they also impact the welfare of population. The article dwells on the analysis of scientific approaches to the regulation of economic development of enterprises in suburban areas of the region. The article analyzes the scientific approaches to the regulation of economic development of enterprises in suburban areas of the region. According to the well-known classics of the fundamental economic theory of entrepreneurship development (A. Smith, D. Ricardo, V. Laungard, A. Loria) the peculiarities of economic development of entrepreneurship in suburban territories of the region are determined by the possibility of distribution of surplus production, minimum production costs per unit of production, availability of labor resources. In modern economic theory (M. Weber, A. Pre, S.M. Kimelberg, E. Williams, C. Vlachou, O. Iakovidou, J. van Dijk, P. Pellenbarg) the development of entrepreneurship in suburban areas of the region can be determined by institutional, innovation, technological, social, ecological and other features of the economy at the regional, state or world levels. The complex and comprehensive generalization of the features of economic development of entrepreneurship in suburban areas is proposed. There are (1) the type of decision taken by an enterprise to carry out business activities in the relevant suburban area of the region, and (2) the influence of internal and external factors on economic activity. The article argues that large enterprises are guided by more objective decision-making reasons, attaching the most importance to the physical and innovative environment. Medium and small enterprises are mainly focused on getting benefits for the entrepreneur in the short-term time period and location in the nearest geographic area. The attention was paid to the tools of ensuring economic development of entrepreneurship in suburban areas of the region, taking into account institutional changes in the national economy and the experience of developed countries of the world.

Statistical Processing and Correlations Between Concentrations of Some Atmospheric Pollutants in Suceava and Botosani Counties

2020 ◽  
Vol 71 (7) ◽  
pp. 175-186
Author(s):  
Doina Lutic ◽  
Danut-Gabriel Cozma
Keyword(s):  
Nitrogen Monoxide ◽  
Statistical Processing ◽  
Geographic Area ◽  
The Other ◽  
Atmospheric Pollutants ◽  
Climate Conditions ◽  
National Network ◽  
Different Seasons ◽  
Official Site ◽  
Social Wealth

The abundance of some pollutants from the air depend on the geographic area, the human activities intensity, the climate, the season and even on the hour within a day. The nitrogen oxides are the most abundant and most dangerous toxic species from the air, and these emissions are tightly connected to human polluting activities. Therefore, in our work, the first part is assigned for a wide literature search concerning the incidence of the keywords �nitrogen oxide� and searching the connections with other significant related terms and formulas, investigated by the researches worldwide. Then, a statistic approach was applied trying to correlate the values of the concentration in air of nitrogen monoxide, nitrogen dioxide, carbon monoxide, sulfur dioxide, benzene and particulate matter PM10, all of these being generated to a large extent from the exhaust gases from different automotives. The data were collected from the official site of the National Network of Air Quality Monitoring from Romania, and processed by statistical methods, using specific software and methods, in order to find significant differences between the pollutants concentrations values in two neighbor counties (Suceava and Botosani), with relatively similar climate conditions, but different social wealth. The findings of these statistical processing indicate that the PM10 values do not present significant differences between the two locations, neither the time within a day, while the other parameters exhibit distinctions between the values of the other pollutants concentrations in different seasons (summer and winter) and hourly intervals within a day (night, morning, afternoon and evening).

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