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- Creators: Milovanovic, Jelena
- Creators: Arizona State University
Description
Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project features three new pieces for oboe commissioned from three different composers. Each piece explores styles and/or instrumentations that are less common in the current body of repertoire. These pieces are Scenes for Charlie by Bryan Kennard, Love’s Last Gift by Thomas Juneau, and But Joy Comes in the Morning by William Brusick. A performance guide has been included for each piece, providing tips and suggestions for musicians wanting to perform these pieces in the future. In addition to the performance guide, each composer answered a list of interview questions to provide background information and give insight into their compositional process. Accompanying this document are recordings performed by the author.
ContributorsSummers, Season (Author) / Schuring, Martin (Thesis advisor) / Gardner, Joshua (Committee member) / Norton, Kay (Committee member) / Arizona State University (Publisher)
Created2021
Description
The development of biosensing platforms not only has an immediate lifesaving effect but also has a significant socio-economic impact. In this dissertation, three very important biomarkers with immense importance were chosen for further investigation, reducing the technological gap and improving their sensing platform.Firstly, gold nanoparticles (AuNP) aggregation and sedimentation-based assays were developed for the sensitive, specific, and rapid detection of Ebola virus secreted glycoprotein (sGP)and severe acute respiratory syndrome coronavirus 2 (SARS-COV2) receptor-binding domain (RBD) antigens. An extensive study was done to develop a complete assay workflow from critical nanobody generation to optimization of AuNP size for rapid detection. A rapid portable electronic reader costing (<$5, <100 cm3), and digital data output was developed. Together with the developed workflow, this portable electronic reader showed a high sensitivity (limit of detection of ~10 pg/mL, or 0.13 pM for sGP and ~40 pg/mL, or ~1.3 pM for RBD in diluted human serum), a high specificity, a large dynamic range (~7 logs), and accelerated readout within minutes. Secondly, A general framework was established for small molecule detection using plasmonic metal nanoparticles through wide-ranging investigation and optimization of assay parameters with demonstrated detection of Cannabidiol (CBD). An unfiltered assay suitable for personalized dosage monitoring was developed and demonstrated. A portable electronic reader demonstrated optoelectronic detection of CBD with a limit of detection (LOD) of <100 pM in urine and saliva, a large dynamic range (5 logs), and a high specificity that differentiates closely related Tetrahydrocannabinol (THC). Finally, with careful biomolecular design and expansion of the portable reader to a dual-wavelength detector the classification of antibodies based on their affinity to SARS-COV2 RBD and their ability to neutralize the RBD from binding to the human Angiotensin-Converting Enzyme 2 (ACE2) was demonstrated with the capability to detect antibody concentration as low as 1 pM and observed neutralization starting as low as 10 pM with different viral load and variant. This portable, low-cost, and versatile readout system holds great promise for rapid, digital, and portable data collection in the field of biosensing.
ContributorsIkbal, Md Ashif (Author) / Wang, Chao (Thesis advisor) / Goryll, Michael (Committee member) / Zhao, Yuji (Committee member) / Wang, Shaopeng (Committee member) / Arizona State University (Publisher)
Created2022
Description
Contaminated aerosols and micro droplets are easily generated by infected hosts through sneezing, coughing, speaking and breathing1-3 and harm humans’ health and the global economy. While most of the efforts are usually targeted towards protecting individuals from getting infected,4 eliminating transmissions from infection sources is also important to prevent disease transmission. Supportive therapies for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) pneumonia such as oxygen supplementation, nebulizers and non-invasive mechanical ventilation all carry an increased risk for viral transmission via aerosol to healthcare workers.5-9 In this work, I study the efficacy of five methods for self-containing aerosols emitted from infected subjects undergoing nebulization therapies with a diverse spectrum on Non-Invasive Positive Pressure Ventilator (NIPPV) with oxygen delivery therapies. The work includes five study cases: Case I: Use of a Full-Face Mask with biofilter in bilevel positive airway pressure device (BiPAP) therapy, Case II: Use of surgical mask in High Flow Nasal Cannula (HFNC) therapy, Case III: Use of a modified silicone disposable mask in a HFNC therapy, Case IV: Use of a modified silicone disposable mask with a regular nebulizer and normal breathing, Case V: Use of a mitigation box with biofilter in a BiPAP. We demonstrate that while cases I, III and IV showed efficacies of 98-100%; cases II and V, which are the most commonly used, resulted with significantly lower efficacies of 10-24% to mitigate the dispersion of nebulization aerosols. Therefore, implementing cases I, III and IV in health care facilities may help battle the contaminations and infections via aerosol transmission during a pandemic.
ContributorsShyamala Pandian, Adithya (Author) / Forzani, Erica (Thesis advisor) / Patel, Bhavesh (Committee member) / Xian, Xiaojun (Committee member) / Arizona State University (Publisher)
Created2021
Description
AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting any of these options, there has been very few alternatives. Now, the emergence of the continuing care at home program is providing hope for a different method of elder care moving forward. CCaH programs offer services such as: skilled nursing care, care coordination, emergency response systems, aid with personal and health care, and transportation. Such services allow seniors to continue to live in their own home with assistance as their health deteriorates over time. Currently, only 30 CCaH programs exist. With the growth of the elderly population in the coming years, this model seems poised for growth.
ContributorsSturm, Brendan (Author) / Milovanovic, Jelena (Thesis director) / Hassett, Matthew (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be taken into account while estimating unpaid claims. Reserve-estimating functions such as glmReserve from the “ChainLadder” package in the statistical software R were experimented with to produce their own results. Because of their insufficiency, a manual approach to building the model turned out to be the most proficient method. Utilizing the GLM function, a model was built that emulated linear regression with a factor for COVID-19. The effects of such a model are analyzed based on effectiveness and interpretablility. A model such as this would prove useful for future calculations, especially as society is now returning to a “normal” state.
ContributorsKossler, Patrick (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
Description
The objective of this study is to build a model using R and RStudio that automates ratemaking procedures for Company XYZ’s actuaries in their commercial general liability pricing department. The purpose and importance of this objective is to allow actuaries to work more efficiently and effectively by using this model that outputs the results they otherwise would have had to code and calculate on their own. Instead of spending time working towards these results, the actuaries can analyze the findings, strategize accordingly, and communicate with business partners. The model was built from R code that was later transformed to Shiny, a package within RStudio that allows for the build-up of interactive web applications. The final result is a Shiny app that first takes in multiple datasets from Company XYZ’s data warehouse and displays different views of the data in order for actuaries to make selections on development and trend methods. The app outputs the re-created ratemaking exhibits showing the resulting developed and trended loss and premium as well as the experience-based indicated rate level change based on prior selections. The ratemaking process and Shiny app functionality will be detailed in this report.
ContributorsGilkey, Gina (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05