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At least 127 records · Page 7

Exploring Requirements for Software that Learns: A Research Preview

Context & motivation: The development of software that learns has revolutionized how many systems perform. For the most part, these systems are neither safety- nor mission-critical. However, as technology and aspirations advance, there is an increased desire and need for Machine Learning (ML) software in safety- and mission-critical systems, e.g., driverless cars or autonomous space robotics. Problem: In these domains, reliability is crucial and systems have to undergo much scrutiny in terms of both the developed artefacts and the adopted development process. Central to the development of such systems is the elicitation and definition of software requirements that are used to guide the design and verification process. The addition of software components that learn, and the associated capability for unforeseen behavior, makes defining detailed software requirements especially difficult. Principal ideas/results: In this paper, we identify unique characteristics of software requirements that are specific to ML components. To this end, we collect and examine requirements from both academic and industrial sources. Contribution: To the best of our knowledge, this is the first work that presents real-life, industrial patterns of requirements for ML components. Furthermore, this paper identifies key characteristics and provides a foundation for developing a taxonomy of requirements for software that learns.

Probabilistic requirements↗

EDX4CCS 3D Data Preview Tool

For presentation at the 2023 FECM / NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 30-Septamber 1, 2023.

Wingo, Patrick↗

Preview: What is the Overall Picture?

Infographic on the Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative, an Energy & Environmental Research Center–U.S. Department of Energy project, featuring flowcharts depicting potential pathways from unmined lignite to final products.

01 COAL, LIGNITE, AND PEAT↗

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗

Research project for increasing pool of minority engineers

The Tennessee State University (TSU) Research Project for Increasing the Pool of Minority Engineers is designed to develop engineers who have academic and research experiences in technical areas of interest to NASA. These engineers will also have some degree of familiarity with NASA Lewis Research Center as a result of interaction with Lewis engineers, field trips and internships at Lewis. The Research Project has four components, which are: (1) Minority Introduction to Engineering (MITE), a high school precollege program, (2) engineering and technology previews, (3) the NASA LeRC Scholars program which includes scholarships and summer internships, and (4) undergraduate research experiences on NASA sponsored research. MITE is a two-week summer engineering camp designed to introduce minority high school students to engineering by exposing them to: (1) engineering role models (engineering students and NASA engineer), (2) field trips to engineering firms, (3) in addition to introducing youth to the language of the engineer (i.e., science, mathematics, technical writing, computers, and the engineering laboratory). Three MITE camps are held on the campus of TSU with an average of 40 participants. MITE has grown from 25 participants at its inception in 1990 to 118 participants in 1994 with participants from 17 states, including the District of Columbia, and 51 percent of the participants were female. Over the four-year period, 77 percent of the seniors who participated in MITE have gone to college, while 53 percent of those seniors in college are majoring in science, engineering or mathematics (SEM). This first Engineering and Technology Previews held in 1993 brought 23 youths from Cleveland, Ohio to TSU for a two-day preview of engineering and college life. Two previews are scheduled for 1994-1995. The NASA LeRC Scholars program provides scholarships and summer internships for minority engineering students majoring in electrical or mechanical engineering. Presently six (6) engineering students are in the Scholars program. The average GPA for the scholars is 3.239. Each scholar must maintain a minimum GPA of 3.000/4.000. NASA LeRC Fred Higgs has been awarded a GEM Fellowship. In addition, he will be presenting a paper entitled 'Design of Helical Spring Using Probabilistic Design Methodology' at the Middle Tennessee Section ASME Student Design Presentations in Nashville on March 23rd and at the National Conference on Undergraduate Research to be held at Union College, Schenectady, New York on April 20-22, 1995. Each of the scholars is working on one of the three NASA sponsored research projects in the college.

Rogers, Decatur B.↗

DataComm in Flight Deck Surface Trajectory-Based Operations

The purpose of this pilot-in-the-loop aircraft taxi simulation was to evaluate a NextGen concept for surface trajectory-based operations (STBO) in which air traffic control (ATC) issued taxi clearances with a required time of arrival (RTA) by Data Communications (DataComm). Flight deck avionics, driven by an error-nulling algorithm, displayed the speed needed to meet the RTA. To ensure robustness of the algorithm, the ability of 10 two-pilot crews to meet the RTA was tested in nine experimental trials representing a range of realistic conditions including a taxi route change, an RTA change, a departure clearance change, and a crossing traffic hold scenario. In some trials, these DataComm taxi clearances or clearance modifications were accompanied by preview information, in which the airport map display showed a preview of the proposed route changes, including the necessary speed to meet the RTA. Overall, the results of this study show that with the aid of the RTA speed algorithm, pilots were able to meet their RTAs with very little time error in all of the robustness-testing scenarios. Results indicated that when taxi clearance changes were issued by DataComm only, pilots required longer notification distances than with voice communication. However, when the DataComm was accompanied by graphical preview, the notification distance required by pilots was equivalent to that for voice.

Bakowski, Deborah L.↗

DataComm in Flight Deck Surface Trajectory-Based Operations

The purpose of this pilot-in-the-loop aircraft taxi simulation was to evaluate a NextGen concept for surface trajectory-based operations (STBO) in which air traffic control (ATC) issued taxi clearances with a required time of arrival (RTA) by Data Communications (DataComm). Flight deck avionics, driven by an error-nulling algorithm, displayed the speed needed to meet the RTA. To ensure robustness of the algorithm, the ability of 10 two-pilot crews to meet the RTA was tested in nine experimental trials representing a range of realistic conditions including a taxi route change, an RTA change, a departure clearance change, and a crossing traffic hold scenario. In some trials, these DataComm taxi clearances or clearance modifications were accompanied by 'preview' information, in which the airport map display showed a preview of the proposed route changes, including the necessary speed to meet the RTA. Overall, the results of this study show that with the aid of the RTA speed algorithm, pilots were able to meet their RTAs with very little time error in all of the robustness-testing scenarios. Results indicated that when taxi clearance changes were issued by DataComm only, pilots required longer notification distances than with voice communication. However, when the DataComm was accompanied by graphical preview, the notification distance required by pilots was equivalent to that for voice.

NextGen↗