1,720,956 research outputs found
Billion-Dollar Natural Disasters: What Does the Future Look Like?
The average cost of natural disasters and damage to the U.S. economy has increased each year from approximately 300 billion in 2017. This increase in the cost of natural disasters could be due to an increase in the strength and frequency of natural disasters and/or growth in the U.S. economy. We forecast the cost of natural disasters by fitting probability distributions to the historical cost of billion-dollar disasters. We model the cost of natural disasters based on all weather-related natural disasters that cost more than 1 billion that occurred in the past 20 years. Using the data from 1980 to 2018, the model forecasts the annual expected cost to be 93 billion.The proceeding is published as Shukla, Charchit, and Cameron A. MacKenzie. "Billion-Dollar Natural Disasters: What Does the Future Look Like?" In: L. Cromarty, R. Shirwaiker, P. Wang, eds., IISE Annual Conference and Expo 2020. Proceedings of a meeting held May 3-June 2, 2020. Posted with permission.</p
Analyzing the financial risk of billion-dollar disasters in the United States: Simulating the frequency and economic costs of U.S. natural disasters
The number of billion-dollar natural disasters in the United States has increased from 28 in 1980-1989 to 105 in 2010-2018. During these same time periods, the total cost of these natural disasters increased from 755 billion. Generating probabilistic assessments of the cost of these billion-dollar natural disasters can provide insight into the financial risks posed by these disasters while accounting for the uncertainty and variation in these disasters. This article simulates the frequency and cost of billion-dollar disasters and analyzes the financial risk of these disasters in the United States. We use a probabilistic approach to quantify and create five models. These models are created by fitting probability distributions to the historical cost of billion-dollar disasters. The cost of each billion-dollar natural disaster and U.S. GDP from 1980 to 2018 are analyzed and used. The model that perhaps fits the data best and accounts for the recent increase in the cost and frequency of billion-dollar disasters forecasts that the expected annual cost of these disasters is 500 billion. Simulating the costs and frequency of natural disasters provides an understanding of the risks of different types of disasters to the United States. It helps policymakers allocate resources effectively to build a resilient nation.This is a pre-print of the article Shukla, Charchit, and Cameron A. MacKenzie. "Analyzing the financial risk of billion-dollar disasters in the United States: Simulating the frequency and economic costs of US natural disasters." (2022).
DOI: 10.21203/rs.3.rs-1929931/v1.
Attribution 4.0 International (CC BY 4.0).
Copyright 2022 The Authors.
Posted with permission
An analysis of billion-dollar natural disasters in the United States
The average cost of natural disasters and damage to the U.S. economy has increased each year from approximately 300 billion in 2017. This increase in the cost of natural disasters could be due to an increase in the strength and frequency of natural disasters and/or growth in the U.S. economy. This thesis forecasts the cost of natural disasters by fitting probability distributions to the historical cost of billion-dollar disasters. This thesis models the cost of natural disasters based on all weather-related natural disasters that cost more than 1 billion that occurred in the past 20 years. Using the data from 1980 to 2018, the model forecasts the annual expected cost to be 91 billion
An analysis of billion-dollar natural disasters in the United States
The average cost of natural disasters and damage to the U.S. economy has increased each year from approximately 300 billion in 2017. This increase in the cost of natural disasters could be due to an increase in the strength and frequency of natural disasters and/or growth in the U.S. economy. This thesis forecasts the cost of natural disasters by fitting probability distributions to the historical cost of billion-dollar disasters. This thesis models the cost of natural disasters based on all weather-related natural disasters that cost more than 1 billion that occurred in the past 20 years. Using the data from 1980 to 2018, the model forecasts the annual expected cost to be 91 billion.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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