Physical Sciences and Mathematics Commons^™

Usf Jamovi Tutorial Project: Open Education Resource, Aline Hitti, Saera Khan

USF OER Faculty Grant

Jamovi is an open source free software that USF staff, faculty and student can download to carry out any statistical analyses. The current report summarizes the progress made on an Open Education Resource Grant funded project, which aimed to created Jamovi tutorials. In this report, student feedback and faculty reaction are summarized after one semester of using the tutorials created.

Dynamic Relationship Study Between The Observed Seismicity And Spatiotemporal Pattern Of Lineament Changes In Palghar, North Maharashtra (India), Biswajit Nath, Ramesh P. Singh, Vineet K. Gahalaut, Ajay P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Palghar region (north Maharashtra, India), located in the northwestern part of the stable continental region of India, experienced a low magnitude earthquake swarm, which was initiated in September 2018 and is continuing to date (as of October 2021). From December 2018 to December 2020, ~5000 earthquakes with magnitudes from M1.2 to M3.8 occurred in a small region of 20 × 10 km². These earthquakes were probably triggered by fluid migration during seasonal rainfall. In this study, we have used multi-temporal Landsat satellite data of the year 2000, 2015, 2018, 2019, and 2020, extracted lineaments, and studied the …

Progressive Destabilization And Triggering Mechanism Analysis Using Multiple Data For Chamoli Rockslide Of 7 February 2021, Wenfei Mao, Lixin Wu, Ramesh P. Singh, Yuan Qi, Busheng Xie, Yingjia Liu, Yifan Ding, Zilong Zhou, Jia Li

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic rockslide occurred on 7 February 2021 in Chamoli area in the high Himalaya. In the absence of field data, multiple satellites data of decade span have been used to investigate and understand the progressive destabilization of rockslide body. A 3D geometric model was developed using geospatial information about geology, terrain, and ice cover to understand the triggering mechanism. Several causes are uncovered as: the pronounced long-term change of land surface temperature facilitated local permafrost degradation and led to ice cover shrinking since 2010; the occurrence of ice avalanche nearby in 2016 accompanying with sidewall-to-bedrock fracturing enhanced the ice …

Teaching Computer Science Csc 222, Harrison Dekker

Library Impact Statements

No abstract provided.

Introduction To Using Python In The Digital Humanities, Elisabeth Shook

Library Faculty Publications and Presentations

The materials here are from the Python for Digital Humanities Workshop taught on December 13, 2021 for the Boise State University Digital Humanities Group. This 3-hour workshop was created to provide both a very brief introduction to the various capabilities of Python and a small lesson in using Python to pull meaningful insight out of text files.

Newgrange Skyscape In Stellarium, Frank Prendergast

Articles

Newgrange Skyscape in Stellarium is a new customised landscape planetarium model giving the user the unique ability to interrogate the dynamic sky above the Boyne Valley on any date of interest during the hours of daylight or darkness. Archaeological, astronomical and topographical points of interest are labelled in the model and visible even during the hours of darkness. These are summarily described in a short gazetteer appended at the end of the instruction document to encourage further exploration of the wonderful heritage found in the Boyne Valley and beyond.

Watch on Youtube: https://www.youtube.com/watch?app=desktop&v=aGPsVGBXkY4

Watch on Vimeo: https://vimeo.com/493351576

Proquest Tdm Studio: A Text And Data Mining Solution, Anamika Megwalu, Anne Marie Engelsen

Faculty Research, Scholarly, and Creative Activity

TDM Studio is an integrated platform offered by ProQuest for data and text mining. TDM stands for text and data mining. This cloud-based, all-in-one innovative product is designed to offer researchers a clean interface with rights-cleared content, Jupyter notebook, and data visualization tools. As a result, researchers can now search Pro-Quest databases, create large datasets, import data to Jupyter notebook for analysis, and download results within a day.

Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …

How Community Participation In Water And Sanitation Interventions Impacts Human Health, Wash Infrastructure And Service Longevity In Low-Income And Middle-Income Countries: A Realist Review, Sarah Nelson, Dorothy Drabarek, Aaron Jenkins, Joel Negin, Seye Abimbola

Research outputs 2014 to 2021

Objective:

To understand how, and under what circumstances community participation in water and sanitation interventions impacts the availability of safe water and sanitation, a change in health status or behaviour and the longevity of water, sanitation and hygiene (WASH) resources and services.

Design:

Realist review.

Data sources:

PubMed, Web of Science and Scopus databases were used to identify papers from low-income and middle-income countries from 2010 to 2020.

Eligibility criteria for selecting studies:

Criteria were developed for papers to be included. The contribution of each paper was assessed based on its relevance and rigour (eg, can it contribute to context, …

South Dakota Farmers’ Perceived Extreme Weather Frequency And Adaptation Measures, Tong Wang, Jim Ristau

South Dakota Farm Survey

Researchers at South Dakota State University (SDSU) conducted surveys of eastern South Dakota (SD) commodity crop producers with the support of the South Dakota Corn Utilization Council. Using publicly available addresses of government program participants, a random sample of 3,000 producers were sent the survey in 2018. 650 were ineligible and 708 responded to the survey for a response rate of 30%. In 2021, the same producers who took the survey in 2018 were asked to take a follow up survey. 94 were ineligible, and 350 responded for a 59% response rate. Producers could take the survey online or via …

Law Library Blog (December 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Evaluation Of The Trunarc Handheld Narcotics Analyzer As A Pre-Analysis Screening Device For The Orange County Crime Lab, Sarah Yang, D. Bauer, C. Woltz, S. Soto, Michael Ibba

Student Scholar Symposium Abstracts and Posters

Forensic analysis of suspected narcotics is often dangerous as the substances’ composition is unknown. Many techniques for drug identification require handling of the substance outside of its packaging, which can expose the analyst to potentially harmful chemicals. The TruNarc Handheld Narcotics Analyzer is a portable Raman spectroscopy device that is non-destructive of evidence and can be used to screen drugs through simple packaging to minimize the risk of exposure. The Orange County Crime Lab (OCCL) is testing the limits of this device to determine if it can be used to screen new evidence within the Seized Drugs Lab. The OCCL …

Measuring Ecosystem Services From Soil Health. Vermont Payment For Ecosystem Services Technical Research Report #1, Alissa C. White, Heather M. Darby, Benjamin Timothy Dube, Bryony Sands, Joshua W. Faulkner, Meredith Albers, Maggie Payne

UVM Extension Faculty Publications

There are a multitude of approaches to evaluating soil health and the soil processes influenced by soil health. As the state of Vermont explores innovative programs that compensate farmers for soil health and associated ecosystem services, the selection of soil health indicators and quantification methods is a foundational first step that influences other aspects of program design. What is measured determines the ecosystem services that can be inferred, the accuracy of data that informs decisions, and programmatic transaction costs. Simply put, what is measured matters. The PES Working Group identified organic matter, bulk density, aggregate stability, greenhouse gas flux from …

Ai And The Future Of Work: What We Know Today, Steven M. Miller, Thomas H. Davenport

Research Collection School Of Computing and Information Systems

To contribute to a better understanding of the contemporary realities of AI workplace deployments, the authors recently completed 29 case studies of people doing their everyday work with AI-enabled smart machines. Twenty-three of these examples were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. In this essay, we compare our findings on job and workplace impacts to those reported in the MIT Task Force on the Work of the Future report, as we consider that to be the most comprehensive recent study on this topic.

Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng

Research Collection School Of Computing and Information Systems

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.

Why Science Is Important To Us All: Identity And Environment, Anita K. Foeman

Sustainability Research & Practice Seminar Presentations

Professor Anita Foeman, Communication and Media - Why Science is Important to Us All: Identity and Environment

Spurring Digital Transformation In Singapore's Legal Industry, Xin Juan Chua, Steven M. Miller

Research Collection School Of Computing and Information Systems

COVID-19 has transformed the way we live and work. It has caused the processes and operations of businesses and organisations to be restructured, as well as transformed business models. A 2020 McKinsey Global survey reported that companies all over the world claim they have accelerated the digitalisation of their customer and supply-chain interactions, as well as their internal operations, by three to four years. They also said they thought the share of digital or digitally enabled products in their portfolios has advanced by seven years. While technology transformation is not new to the legal profession, COVID-19 has cemented the importance …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Regulating New Tech: Problems, Pathways, And People, Cary Coglianese

All Faculty Scholarship

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …

Introduction To Malware Analysis, Harrison Dekker

Library Impact Statements

No abstract provided.

Survey Data On Energy And Fuel Use Of Firms In Economic Zones In The Philippines, Majah-Leah V. Ravago, Raul V. Fabella, Karl Robert L. Jandoc, Renzi G. Frias, J. Kathleen P. Magadia

Economics Department Faculty Publications

The data describe characteristics, operations, utilities, and fuels used in the production of 115 manufacturing and agro-industrial firms in Philippine special economic zones. The data include information on the firm's production, sales, and schedules; electricity sources, requirements, and uses; the importance of various conventional fuels, and the firms’ fuel expenditure in their major production processes. The data also include their employee's aptitude, knowledge, considerations, and opinions on alternative fuels and primary energies, and experiences in using them. The data were gathered through a series of focus group discussions (FGDs) in June 2019 and an online survey conducted in August to …

Spatial Distribution Of Pm2.5-Related Premature Mortality In China, Sheng Zheng, Uwe Schlink, Kin-Fai Ho, Ramesh P. Singh, Andrea Pozzer

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

PM_2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM_2.5 exposure. This study analyzed the spatial distribution of PM_2.5 concentration (45.9 μg/m³ national average in 2016) and premature mortality attributed to PM_2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 …

Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter

Articles

The threat posed by misinformation and disinformation is one of the defining challenges of the 21st century. Provenance is designed to help combat this threat by warning users when the content they are looking at may be misinformation or disinformation. It is also designed to improve media literacy among its users and ultimately reduce susceptibility to the threat among vulnerable groups within society. The Provenance browser plugin checks the content that users see on the Internet and social media and provides warnings in their browser or social media feed. Unlike similar plugins, which require human experts to provide evaluations and …

A Practical Solution: The Anthropocene Is A Geological Event, Not A Formal Epoch, Philip L. Gibbard, Andrew M. Bauer, Matthew Edgeworth, William F. Ruddiman, Jacquelyn L. Gill, Dorothy J. Merritts, Stanley C. Finney, Lucy E. Edwards, Michael J. C. Walker, Mark Maslin, Erle C. Ellis

Biology and Ecology Faculty Scholarship

The Anthropocene has yet to be defined in a way that is functional both to the international geological community and to the broader fields of environmental and social sciences. Formally defining the Anthropocene as a chronostratigraphical series and geochronological epoch with a precise global start date would drastically reduce the Anthropocene’s utility across disciplines. Instead, we propose the Anthropocene be defined as a geological event, thereby facilitating a robust geological definition linked with a scholarly framework more useful to and congruent with the many disciplines engaging with human-environment interactions. Unlike formal epochal definitions, geological events can recognize the spatial and …

Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.

Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and …

The Maritime Domain Awareness Center– A Human-Centered Design Approach, Gary Gomez

Political Science & Geography Faculty Publications

This paper contends that Maritime Domain Awareness Center (MDAC) design should be a holistic approach integrating established knowledge about human factors, decision making, cognitive tasks, complexity science, and human information interaction. The design effort should not be primarily a technology effort that focuses on computer screens, information feeds, display technologies, or user interfaces. The existence of a room with access to vast amounts of information and wall-to-wall video screens of ships, aircraft, weather data, and other regional information does not necessarily correlate to possessing situation awareness. Fundamental principles of human-centered information design should guide MDAC design and technology selection, and …

The Imperative For Climate Action At Portland State University, Stephen Percy

Office of the President Publications and Presentations

Portland State University President Stephen Percy announces the formation of the Climate Change Initiative.

Pre-Earthquake Ionospheric Perturbation Identification Using Cses Data Via Transfer Learning, Pan Xiong, Cheng Long, Huiyu Zhou, Roberto Battiston, Angelo De Santis, Dimitar Ouzounov, Xuemin Zhang, Xuhui Shen

Mathematics, Physics, and Computer Science Faculty Articles and Research

During the lithospheric buildup to an earthquake, complex physical changes occur within the earthquake hypocenter. Data pertaining to the changes in the ionosphere may be obtained by satellites, and the analysis of data anomalies can help identify earthquake precursors. In this paper, we present a deep-learning model, SeqNetQuake, that uses data from the first China Seismo-Electromagnetic Satellite (CSES) to identify ionospheric perturbations prior to earthquakes. SeqNetQuake achieves the best performance [F-measure (F1) = 0.6792 and Matthews correlation coefficient (MCC) = 0.427] when directly trained on the CSES dataset with a spatial window centered on the earthquake epicenter with the Dobrovolsky …

Predicting The Adoption Of Password Managers: A Tale Of Two Samples, Shelia Kennison, D. Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Using weak passwords and re-using passwords can make one vulnerable to cybersecurity breaches. Cybersecurity experts recommend the adoption of password managers (PMs), as they generate and store strong passwords for all accounts. Prior research has shown that few people adopt PMs. Our research examined PM adoption in a sample of 221 undergraduates from psychology courses and a sample of 278 MTurk workers. We hypothesized that PM adoption could be predicted using a small set of user characteristics (i.e., gender, age, Big Five personality traits, number of devices used, frequency of using social media, and cybersecurity knowledge). The results showed that …

Risk Management And Biases In How Drivers Respond To Nuisance Flooding, Saige Hill, Juita-Elena (Wie) Yusuf, Burton St. John Iii, Pragati Rawat, Carol Considine

School of Public Service Faculty Publications

Nuisance flooding, or recurrent flooding, occurs during high tide and may be exacerbated when combined with other events such as heavy precipitation, strong winds, or storm surge. Sea level rise has contributed to increased frequency and duration of nuisance flooding in low-lying coastal areas and is causing community-specific impacts such as transportation disruption, road closures, compromises to life and property, overwhelmed storm water systems, and infrastructure damage. This chapter focuses on how drivers respond during nuisance flooding events. Specifically, we discuss how drivers in the Hampton Roads region of southeastern coastal Virginia obtain information about road flooding, how they respond, …