Application of Data Visualization and Numerical Analysis for Evaluating Propagation of Uncertainty

Propagation of uncertainty is a key factor in uncertainty evaluation. We propose a method using data visualization and numerical analysis for evaluating propagation of uncertainty. In this paper, the main stages of the method are described. Then, the implementation of the method in linear and nonlinear model is illustrated through some examples. These examples show appropriate use of data visualization and numerical analysis can be helpful to provide a concise qualitative overview and accurate quantitative analysis for the uncertainty.

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Between automation and interpretation : Using data visualization in social media analytics companies

Data Visualization in Society ◽

10.5117/9789463722902_ch06 ◽

2020 ◽

Author(s):

Salla-Maaria Laaksonen ◽

Juho Pääkkönen

Keyword(s):

Social Media ◽

Data Visualization ◽

Social Media Analytics ◽

Use Of Data ◽

Representational Practice ◽

Field Notes ◽

Using Data ◽

Data Visualizations ◽

Knowledge Claims

This chapter explores the use of data visualizations in social media analytics companies. Drawing on a dataset of ethnographic field notes and thematic interviews in four Finnish social media analytics companies, we argue that data visualizations are crucially involved in how analytics-based knowledge claims become accepted by companies and their clients. Basing on previous research on visualizations in organizations and as a representational practice, we explore their role in social media analytics. We identify three practices of using visualizations, which we have named have simple-boxing, flatter-boxing, and pretty-boxing. We argue that these practices enable analysts to achieve the simultaneous aims of producing credible and valuable analytics in a context marked by high business promises.

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Qualitative Sentiment Analysis with Implementation of Neuro-Linguistic Programming Techniques

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.d1937.029420 ◽

2020 ◽

Vol 9 (4) ◽

pp. 2556-2560

Keyword(s):

Data Visualization ◽

Behavior Pattern ◽

Human Mind ◽

Social Aspects ◽

Behavior Patterns ◽

Tabular Form ◽

Huge Amount ◽

Key Factor ◽

Programming Techniques ◽

Using Data

This Paper lights on Neuro-Linguistic Programming (NLP) Techniques, which is used to implement with the help of Qualitative Sentiment surveys. Neuro-Linguistic Programming techniques with Qualitative Sentiment Surveys helps in determining the behavior pattern of the human mind. Nowadays there is a huge amount of data available related to many social aspects. Participants’ satisfaction is the key factor for Qualitative Surveys. In this paper, Neuro-Linguistic Programming techniques are used to change the behavior patterns of the human mind. Datasets of 81 participants are being used for analysis. NLP thinking, imagining and feeling techniques are used by the participants to make a change in their behavior pattern. Results are shown in tabular form. Participants’ satisfactory results are shown with the help of python by using data visualization and matplotlib.

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Quantification of Silica Uptake by Alveolar Macrophages - An Emperical Scanning Electron Microprobe Method

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100054297 ◽

1982 ◽

Vol 40 ◽

pp. 332-333

Author(s):

V. V. Damiano ◽

R. P. Daniele ◽

H. T. Tucker ◽

J. H. Dauber

Keyword(s):

Quantitative Analysis ◽

Alveolar Macrophages ◽

Bulk Sample ◽

Silica Particles ◽

Empirical Method ◽

Phagocytic Cells ◽

Calibration Standards ◽

X Ray ◽

Accurate Quantitative Analysis ◽

Scanning Electron

An important example of intracellular particles is encountered in silicosis where alveolar macrophages ingest inspired silica particles. The quantitation of the silica uptake by these cells may be a potentially useful method for monitoring silica exposure. Accurate quantitative analysis of ingested silica by phagocytic cells is difficult because the particles are frequently small, irregularly shaped and cannot be visualized within the cells. Semiquantitative methods which make use of particles of known size, shape and composition as calibration standards may be the most direct and simplest approach to undertake. The present paper describes an empirical method in which glass microspheres were used as a model to show how the ratio of the silicon Kα peak X-ray intensity from the microspheres to that of a bulk sample of the same composition correlated to the mass of the microsphere contained within the cell. Irregular shaped silica particles were also analyzed and a calibration curve was generated from these data.

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Lifestyle carbon footprints and changes in lifestyles to limit global warming to 1.5 °C, and ways forward for related research

Sustainability Science ◽

10.1007/s11625-021-01018-6 ◽

2021 ◽

Author(s):

Ryu Koide ◽

Michael Lettenmeier ◽

Lewis Akenji ◽

Viivi Toivio ◽

Aryanie Amellina ◽

...

Keyword(s):

Global Warming ◽

Quantitative Analysis ◽

Sustainability Science ◽

Scenario Development ◽

Carbon Footprints ◽

Related Research ◽

Living Lab ◽

Per Capita ◽

Using Data ◽

Subnational Analysis

AbstractThis paper presents an approach for assessing lifestyle carbon footprints and lifestyle change options aimed at achieving the 1.5 °C climate goal and facilitating the transition to decarbonized lifestyles through stakeholder participatory research. Using data on Finland and Japan it shows potential impacts of reducing carbon footprints through changes in lifestyles for around 30 options covering food, housing, and mobility domains, in comparison with the 2030 and 2050 per-capita targets (2.5–3.2 tCO2e by 2030; 0.7–1.4 tCO2e by 2050). It discusses research opportunities for expanding the footprint-based quantitative analysis to incorporate subnational analysis, living lab, and scenario development aiming at advancing sustainability science on the transition to decarbonized lifestyles.

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Health and Housing Energy Expenditures: A Two-Part Model Approach

Processes ◽

10.3390/pr9060943 ◽

2021 ◽

Vol 9 (6) ◽

pp. 943

Author(s):

Fátima Lima ◽

Paula Ferreira ◽

Vítor Leal

Keyword(s):

Low Income ◽

Health Expenditures ◽

Household Level ◽

Energy Expenditures ◽

Health And Wellbeing ◽

Health Gains ◽

Key Factor ◽

Using Data ◽

Part Model ◽

Model Approach

Interest in the interaction between energy and health within the built environment has been increasing in recent years, in the context of sustainable development. However, in order to promote health and wellbeing across all ages it is necessary to have a better understanding of the association between health and energy at household level. This study contributes to this debate by addressing the case of Portugal using data from the Household Budget Survey (HBS) microdata database. A two-part model is applied to estimate health expenditures based on energy-related expenditures, as well as socioeconomic variables. Additional statistical methods are used to enhance the perception of relevant predictors for health expenditures. Our findings suggest that given the high significance and coefficient value, energy expenditure is a relevant explanatory variable for health expenditures. This result is further validated by a dominance analysis ranking. Moreover, the results show that health gains and medical cost reductions can be a key factor to consider on the assessment of the economic viability of energy efficiency projects in buildings. This is particularly relevant for the older and low-income segments of the population.

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Determinants of Corporate Anti-Corruption Disclosure: The Case of the Emerging Economics

Sustainability ◽

10.3390/su13063462 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3462

Author(s):

Maider Aldaz Odriozola ◽

Igor Álvarez Etxeberria

Keyword(s):

Empirical Studies ◽

Geographical Area ◽

Control Variable ◽

Emerging Countries ◽

Point Of View ◽

Press Freedom ◽

Negative Effects ◽

Key Factor ◽

Using Data ◽

Positive Effect

Corruption is a key factor that affects countries’ development, with emerging countries being a geographical area in which it tends to generate greater negative effects. However, few empirical studies analyze corruption from the point of view of disclosure by companies in this relevant geographical area. Based on a regression analysis using data from the 96 large companies from 15 emerging countries included in the 2016 International Transparency Report, this paper seeks to understand what determinants affect such disclosure. In that context, this paper provides empirical evidence to understand the factors that influence reporting on anti-corruption mechanisms in an area of high economic importance that has been little studied to date, pointing to the positive effect of press freedom in a country where the company is located and with the industry being the unique control variable that strengthens this relationship.

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Embracing School Counselors’ Situatedness: Data-Based Decision Making as Fulfillment of a Complex Identity

Professional School Counseling ◽

10.1177/2156759x211011922 ◽

2021 ◽

Vol 24 (1_part_3) ◽

pp. 2156759X2110119

Author(s):

Brett Zyromski ◽

Catherine Griffith ◽

Jihyeon Choi

Keyword(s):

Decision Making ◽

School Counselors ◽

School Counselor ◽

Use Of Data ◽

Counselor Identity ◽

Using Data ◽

Definition Of ◽

Support Students ◽

Students Success ◽

Data Based Decision Making

Since at least the 1930s, school counselors have used data to inform school counseling programming. However, the evolving complexity of school counselors’ identity calls for an updated understanding of the use of data. We offer an expanded definition of data-based decision making that reflects the purpose of using data in educational settings and an appreciation of the complexity of the school counselor identity. We discuss implications for applying the data-based decision-making process using a multifaceted school counselor identity lens to support students’ success.

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