CROP HEIGHT ESTIMATION WITH UNMANNED AERIAL VEHICLES

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two - dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed range of distances based on the maximum range of the laser scanner. The control system determines, using range data from the laser scanner, a crop height from the top of the crops to the ground

Infrastructure Support for Controlled Experimentation with Software Testing and Regression Testing Techniques

Where the development, understanding, and assessment of software testing and regression testing techniques are concerned, controlled experimentation is an indispensable research methodology. Obtaining the infrastructure necessary to support rigorous controlled experimentation with testing techniques, however, is difficult and expensive. As a result, progress in experimentation with testing techniques has been slow, and empirical data on the costs and effectiveness of testing techniques remains relatively scarce. To help address this problem, we have been designing and constructing infrastructure to support controlled experimentation with software testing and regression testing techniques. This paper reports on the challenges faced by researchers experimenting with testing techniques, including those that inform the design of our infrastructure. The paper then describes the infrastructure that we are creating in response to these challenges, and that we are now making available to other researchers, and discusses the impact that this infrastructure has and can be expected to have on controlled experimentation with testing techniques

Public Opinions of Unmanned Aerial Technologies in 2014 to 2019: A Technical and Descriptive Report

The primary purpose of this report is to provide a descriptive and technical summary of the results from similar surveys administered in fall 2014 (n = 576), 2015 (n = 301), 2016 (ns = 1946 and 2089), and 2018 (n = 1050) and summer 2019 (n = 1300). In order to explore a variety of factors that may impact public perceptions of unmanned aerial technologies (UATs), we conducted survey experiments over time. These experiments randomly varied the terminology (drone, aerial robot, unmanned aerial vehicle (UAV), unmanned aerial system (UAS)) used to describe the technology, the purposes of the technology (for economic, environmental, or security goals), the actors (public or private) using the technology, the technology’s autonomy (fully autonomous, partially autonomous, no autonomy), and the framing (promotion or prevention) used to describe the technology’s purpose. Initially, samples were recruited through Amazon’s Mechanical Turk, required to be Americans, and paid a small amount for participation. In 2016 we also examined a nationally representative samples recruited from Qualtrics panels. After 2016 we only used nationally representative samples from Qualtrics. Major findings are reported along with details regarding the research methods and analyses

Dynamic Characterization of Web Application Interfaces

Web applications are increasingly prominent in society, serving a wide variety of user needs. Engineers seeking to enhance, test, and maintain these applications and third-party programmers wishing to utilize these applications need to understand their interfaces. In this paper, therefore, we present methodologies for characterizing the interfaces of web applications through a form of dynamic analysis, in which directed requests are sent to the application, and responses are analyzed to draw inferences about its interface. We also provide mechanisms to increase the scalability of the approach. Finally, we evaluate the approach’s performance on six non-trivial web applications

A Drone by Any Other Name: Purposes, End-User Trustworthiness, and Framing, but not Terminology, Affect Public Support for Drones

Projections indicate that, as an industry, unmanned aerial vehicles (UAVs, commonly known as drones) could bring more than 100 000 jobs and $80 billion in economic growth to the U.S. by 2025 [1]. However, these promising projections do not account for how various publics may perceive such technologies. Understanding public perceptions is important because the attitudes of different groups can have large effects on the trajectory of a technology, strongly facilitating or hindering technology acceptance and uptake [2]. To advance understanding of U.S. public perceptions of UAV technologies, we conducted a nationwide survey of a convenience sample of 877 Americans recruited from Amazon’s pool of Mechanical Turk (MTurk) workers. In our surveys, we used short scenarios to experimentally vary UAV characteristics, the end-users of the technology, and certain communication factors (terminology and framing). This allowed us to investigate the impacts of these factors alone and in combination. In addition, given the conflicts that sometimes arise around scientific findings and technologies (e.g., climate change, vaccines, [3], [4]), we also gave explicit attention to whether and how public support for UAVs varied by self-reported political ideology, issue attitudes, and perceptions of end-user trustworthiness. Finally, because UAVs for civilian purposes represented relatively new technologies at the time of the first survey, we examined whether public opinion is changing over time, as more people become aware of UAVs. We thus administered the same survey twice, separated by one year, in the fall of 2014 and 2015. The results of our experimental manipulations revealed a surprising lack of impact of terminology and UAV autonomy, a small impact of message framing and UAV end-user, and a relatively large impact of UAV purpose. We did not find that public attitudes changed much over the year between samples, and perceptions of end-user trustworthiness were strong predictors of public support. Still, our regression models only accounted for about 40% of the variance in public support, suggesting that additional variables should be studied in future work to gain a more complete understanding of public support for UAVs. We also found evidence of a small amount of political polarization of public opinion related to who was using the UAVs for what purpose, and this polarization appeared to be changing over time. Taken together, our results — which may be especially useful to UAV designers, marketers, and policy makers — suggest there is a need to establish that the UAVs are used for valued purposes and by users that publics find to be trustworthy. However, public judgments might be significantly impacted by personal or local ideologies rather than national priorities. In the next section, we describe in more detail prior research on public support for UAVs, and how we formulated our research questions and hypotheses. We then describe our methods, results, and findings in greater detail