Physical Sciences and Mathematics Commons^™

Investigating 9-1-1 Call Experience For Medical Emergencies For Future Design, Leanna Machado

Honors College Theses

Emergency calling services have continued to use the 9-1-1 phone number to share information about a medical emergency for around 60 years. However, there are limitations to the current emergency call services that can have improved communication, speed, and accuracy with the implementation of advancing technology. By examining the experience and opinions of 9-1-1 medical emergency callers, we are able to investigate the design of 9-1-1 services to enhance the call experience. The major challenges found in the study are difficulty in verbally explaining the emergency situation and difficulty in describing the location of the emergency. Technologies such as location …

Testing Research Software: A Survey, Nasir U. Eisty, Jeffrey C. Carver

Computer Science Faculty Publications and Presentations

Background Research software plays an important role in solving real-life problems, empowering scientific innovations, and handling emergency situations. Therefore, the correctness and trustworthiness of research software are of absolute importance. Software testing is an important activity for identifying problematic code and helping to produce high-quality software. However, testing of research software is difficult due to the complexity of the underlying science, relatively unknown results from scientific algorithms, and the culture of the research software community.

Aims The goal of this paper is to better understand current testing practices, identify challenges, and provide recommendations on how to improve the testing process …

Transformers In Remote Sensing: A Survey, Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Anwer, Salman Khan, Hisham Cholakkal, Gui-Song Xia, Fahad Shahbaz Khan

Computer Vision Faculty Publications

Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformers-based architectures, originally introduced in natural language processing, have pervaded computer vision field where the self-attention mechanism has been utilized as a replacement to the popular convolution operator for capturing long-range dependencies. Inspired by recent advances in computer vision, remote sensing community has also witnessed an increased exploration of vision transformers for a diverse set of tasks. Although a number of surveys have focused on transformers in computer vision in general, to the best of our knowledge we are …

3d Vision With Transformers: A Survey, Jean Lahoud, Jiale Cao, Fahad Shahbaz Khan, Hisham Cholakkal, Rao Anwer, Salman Khan, Ming-Hsuan Yang

Computer Vision Faculty Publications

The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field. The transformer has been used as a replacement for the widely used convolution operators, due to its ability to learn long-range dependencies. This replacement was proven to be successful in numerous tasks, in which several state-of-the-art methods rely on transformers for better learning. In computer vision, the 3D field has also witnessed an increase in employing the transformer for 3D convolution neural networks and multi-layer perceptron networks. Although a number of surveys have focused on transformers in vision in general, 3D …

Gauging The Acceptance Of Contact Tracing Technology: An Empirical Study Of Singapore Residents’ Concerns With Sharing Their Information And Willingness To Trust, Ee-Ing Ong, Wee Ling Loo

Research Collection Yong Pung How School Of Law

In response to the COVID-19 pandemic, governments began implementing various forms of contact tracing technology. Singapore’s implementation of its contact tracing technology, TraceTogether, however, was met with significant concern by its population, with regard to privacy and data security. This concern did not fit with the general perception that Singaporeans have a high level of trust in its government. We explore this disconnect, using responses to our survey (conducted pre-COVID-19) in which we asked participants about their level of concern with the government and business collecting certain categories of personal data. The results show that respondents had less concern with …

An Investigation Of The Attitudes And Behavioral Outcomes Of Nebraskan Hunters Toward Tick-Borne Disease, Dominic J. Cristiano

School of Natural Resources: Dissertations, Theses, and Student Research

As changes in climate, land-use, and vegetation alter the landscape of the Great Plains, new threats to public health are emerging. Incidences of tick-borne disease in Nebraska have increased nearly 250% over the past two decades – newly established species like Ixodes scapularis may introduce challenges for health practitioners, including more cases of Lyme disease. Strategies for tick-borne disease prevention must incorporate effective health messaging. Audience segmentation may be a useful technique to provide health communication, as it allows for targeted messaging that speaks to specific attitudes and beliefs of a given population. One tool for usefully segmenting populations is …

Comparing Online Surveys For Cybersecurity: Sona And Mturk, Anne Wagner, Anna Bakas, Shelia Kennison, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

People have many accounts and usually need to create a password for each. They tend to create insecure passwords and re-use passwords, which can lead to compromised data. This research examines if there is a link between personality type and password security among a variety of participants in two groups of participants: SONA and MTurk. Each participant in both surveys answered questions based on password security and their personality type. Our results show that participants in the MTurk survey were more likely to choose a strong password and to exhibit better security behaviors and knowledge than participants in the SONA …

A Deep Dive Into The Impact Of Covid-19 On Software Development, Paulo Anselmo Da Mota Silveira Neto, Umme Ayda Mannan, Eduardo Santana De Almeida, Nachiappan Nagappan, David Lo, Pavneet Singh Kochhar, Cuiyun Gao, Iftekhar Ahmed

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic is considered as the most crucial global health calamity of the century. It has impacted different business sectors around the world and software development is not an exception. This study investigates the impact of COVID-19 on software projects and software development professionals. We conducted a mining software repository study based on 100 GitHub projects developed in Java using ten different metrics. Next, we surveyed 279 software development professionals for better understanding the impact of COVID-19 on daily activities and wellbeing. We identified 12 observations related to productivity, code quality, and wellbeing. Our findings highlight that the impact …

Identifying Available Resources And Agricultural Practices Useful In Soil Fertility Management To Support Orange-Fleshed Sweet Potato Cultivation On Smallholder Farms In Mozambique, Rafaela Feola Conz, Engil Isadora Pujol Pereira, Abdul Naico, Maria Isabel Andrade, Johan Six

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Orange-fleshed sweet potato is an important source of macro-and micronutrients for humans, particularly in resource-poor rural communities. However, sweet potato cultivation removes large amounts of nutrients from the soil. Hence, soil fertility replenishment is vital to secure long-term food production. The lack of access to fertilizers hinders the ability of farmers to supply and replenish soil nutrients, intensifying food insecurity. This study aimed at identifying locally available organic residues and agricultural practices with potential application in soil fertility management to prevent soil degradation in southern Mozambique. We conducted a survey to gather information on the farmers’ demographics and farming systems …

Survey Analysis: Senior And One-Year Out Surveys, Paige Phillips

Computer Science: Student Scholarship & Creative Works

Through surveys colleges are able to collect and analyze data pertaining to the institution's alumni, including valuable information about employment post-graduation. The number of alumni employed after graduation is an important statistic for colleges. In addition, the location, company, industry sector, and relevance to major are other aspects that can be analyzed by the college. Collecting alumni information not only provides pertinent employment status but can also maintain alumni connections. Therefore, this project works to organize and analyze alumni major feedback collected through alumni surveys, in order to provide pertinent information for departments and the college.

Survey Control With Gnss Receiver: Wpes, How Do I...? Quick Guide, Bea E. Van Dam

Non-Thesis Student Work

This document is a quick guide to establishing survey control points using a Global Navigation Satellite Systems (GNSS) receiver and processing collected point coordinate data.

The WPES Research Group uses a Trimble NetR9 GNSS reference receiver, which is reflected in the specific sequences of button presses outlined in the data profile setup, field operation, and data download sections. Readers using a different receiver may still find the general workflow overview useful and should be able to use the data post-processing section directly.

Total Station Field Surveying: Wpes, How Do I...? Quick Guide, Bea E. Van Dam

Non-Thesis Student Work

This document provides step-by-step guidance for performing surveys of field sites using a total station unit (TSU) and connected handheld data collector and for downloading collected point data. WPES uses a Sokkia CX-series TSU and a data collector running Carlson SurvCE software. Minor differences in instrument set-up may arise if using a different TSU. Major differences in data collection procedures will occur if using a different data collection software.

Developers Perception Of Peer Code Review In Research Software Development, Nasir U. Eisty, Jeffrey C. Carver

Computer Science Faculty Publications and Presentations

Context Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As a result, researchers have lower confidence in the correctness of the output of the software. Peer code review, a standard software engineering practice, has helped address this problem in other types of software.

Objective Peer code review is less prevalent in research software than it is in other types of software. In addition, the literature does not contain any studies about the use of peer code …

Predictive Models In Software Engineering: Challenges And Opportunities, Yanming Yang, Xin Xia, David Lo, Tingting Bi, John C. Grundy, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-performed studies in various research domains, including software requirements, software design and development, testing and debugging, and software maintenance. This article is a first attempt to systematically organize knowledge in this area by surveying a body of 421 papers on predictive models published between 2009 and 2020. We describe the key models and approaches used, classify the different models, summarize the range of key application …

Civiic: Cybercrime In Virginia: Impacts On Industry And Citizens Final Report, Randy Gainey, Tancy Vandecar-Burdin, Jay Albanese, Thomas Dearden, James Hawdon, Katalin Parti

Sociology & Criminal Justice Faculty Publications

[First paragraph] Victimization from cybercrime is a major concern in Virginia, the US, and the world. As individuals and businesses spend more time online, it becomes increasingly important to understand cybercrime and how to protect against it. Such an understanding is dependent on valid and reliable baseline data that identifies the specific nature, extent, and outcomes of cybercrime activity. A better understanding of cybercrime activity is needed to target and prevent it more effectively, minimize its consequences, and provide support for both individual and corporate victims. Before that can occur, however, better baseline data are required, and this project was …

Industrial Hemp As A Resource For Birds In Agroecosystems: Human-Wildlife Conflict Or Conservation Opportunity?, Emily A. Kotten, Iona Hennessy, Bryan M. Kluever, Bradley F. Blackwell, Lee A. Humberg, Page E. Klug

United States Department of Agriculture Wildlife Services: Staff Publications

Industrial hemp (Cannabis sativa L.; hemp) is an emerging crop in the United States with little known about bird use or the potential for birds to become an agricultural pest. We identified birds associated with hemp fields, using repeated visits to oilseed plots in North Dakota, USA (n = 6) and cannabinoid (CBD) plots in Florida, USA (n = 4) from August to November 2020. We did not control for plot area or density; our observations were descriptive only. We observed 10 species in hemp, 12 species flying over hemp, and 11 species both foraging in and …

A Literature Review On Combining Heuristics And Exact Algorithms In Combinatorial Optimization, Hesamoddin Tahami, Hengameh Fakhravar

Engineering Management & Systems Engineering Faculty Publications

There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic approaches are two extremely effective streams for combinatorial problems. Different research streams, more or less in isolation from one another, created these two. Only several years ago, many scholars noticed the advantages and enormous potential of building hybrids of combining mathematical programming methodologies and metaheuristics. In reality, many problems can be solved much better by exploiting synergies between these approaches than by “pure” classical algorithms. The key question is how to integrate mathematical programming methods and metaheuristics to achieve such …

A Survey On Deep Learning For Software Engineering, Yanming Yang, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

In 2006, Geoffrey Hinton proposed the concept of training "Deep Neural Networks (DNNs)" and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstrated the powerful learning ability of deep learning and its enormous potential. Deep learning has been increasingly used to develop state-of-the-art software engineering (SE) research tools due to its ability to boost performance for various SE tasks. There are many factors, e.g., deep learning model selection, internal structure differences, and model optimization techniques, that may have an impact on the performance of DNNs applied in …