Surface Topography and Vegetation (STV) is a NASA targeted observable for maturation into an observing system architecture. STV will acquire high-resolution, global height measurements, including bare surface land topography, ice topography, vegetation structure, and shallow water bathymetry. These measurements serve a broad range of science and applications objectives that span solid earth, cryosphere, biosphere and hydrosphere disciplines. A common set of measurements could meet many of the community needs. STV objectives would be best met by new observing strategies that employ flexible multi-source and sensor measurements from a variety of orbital and sub-orbital assets. Science and application objectives would be best met by new, 3-dimensional observations from lidar, radar, and stereoimaging. Simulations, experiments, data analysis and technology development in interferometric SAR, lidar and stereo photogrammetry approaches, platform options and system architectures will all mature STV toward an observing system.

An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observations, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions.Since 2021, NASA’s Advanced Information Systems Technology (AIST) program has invested in two ESDT efforts to tackle the impacts of our changing climate. The establishment of ESDT for flood and air quality enabled our teams to formalize the software framework. The open-source framework is called the Integrated Digital Earth Analysis System (IDEAS). By working with the Apache Science Data Analytics Platform (SDAP) community, IDEAS is now a subproject of SDAP. The paper presents the ongoing development of IDEAS and its current applications.

Access control (AC) policy creation and implementation is challenging because of its complex structure and specifications. This paper explores the potential of two novel interactive graphical displays whose design draws upon alternative principles of effective interface design. One tool (CDAC) exploits the power of Euler diagrams to visualize information and interrelate an organization's management structure and details of the file structure of digital resources. The other tool (DMAC) deploys a diagrammatic matrix to coordinate permissions allocations into a context of structural information. The third tool (SLAC) utilized a conventional visualization and served as the control group for comparison against the other two tools. An experiment with 91 relatively novice participants demonstrates that both tools, even with minimal training, support users' comprehension of AC policies and their implementation, as well as a more familiar traditional design of AC tools.

A new observing strategy for floods was demonstrated and evaluated in a testbed environment. The strategy coordinates several observing platforms, including in situ and space based, to observe a flood from multiple vantage points and dynamically target predicted flood events with highresolution observations. The coordinated observations were assimilated back into the model to continuously improve forecasts and future observation selection. The demonstration shows the potential for coordinated, model-driven observing strategies and the feasibility of the NOS Testbed for demonstrating and evaluating new observing strategies.

We characterize a rich class of valuated matroids, called R-minor valuated matroids that includes the indicator functions of matroids, and is closed under operations such as taking minors, duality, and induction by network. We exhibit a family of valuated matroids that are not R-minor based on sparse paving matroids. Valuated matroids are inherently related to gross substitute valuations in mathematical economics. By the same token we refute the Matroid Based Valuation Conjecture by Ostrovsky and Paes Leme (Theoretical Economics 2015) asserting that every gross substitute valuation arises from weighted matroid rank functions by repeated applications of merge and endowment operations. Our result also has implications in the context of Lorentzian polynomials: it reveals the limitations of known construction operations.

Nearest-neighbor finding is a major bottleneck for sampling-based motion planning algorithms. The cost of finding nearest neighbors grows with the size of the roadmap, leading to significant slowdowns for problems which require many configurations to find a solution. Prior work has investigated relieving this pressure with quicker computational techniques, such as kd-trees or locality-sensitive hashing. In this work, we investigate an alternative direction for expediting this process based on workspace connectivity. We present an algorithm called Topological Nearest-Neighbor Filtering, which employs a workspace decomposition to select a topologically relevant set of candidate neighbor configurations as a pre-processing step for a nearest-neighbor algorithm. We investigate the application of this filter to several varieties of RRT and demonstrate that the filter improves both nearest-neighbor time and overall planning performance.

Security experts use their knowledge to attempt attacks on an application in an exploratory and opportunistic way in a process known as penetration testing. However, building security into a product is the responsibility of the whole team, not just the security experts who are often only involved in the final phases of testing. Through the development of a black box security test plan, software testers who are not necessarily security experts can work proactively with the developers early in the software development lifecycle. The team can then establish how security will be evaluated such that the product can be designed and implemented with security in mind. The goal of this research is to improve the security of applications by introducing a methodology that uses the software system's requirements specification statements to systematically generate a set of black box security tests. We used our methodology on a public requirements specification to create 137 tests and executed these tests on five electronic health record systems. The tests revealed 253 successful attacks on these five systems, which are used to manage the clinical records for approximately 59 million patients, collectively. If non-expert testers can surface the more common vulnerabilities present in an application, security experts can attempt more devious, novel attacks.

Software engineers regularly build systems that are required to comply with laws and regulations. To this end, software engineers must determine which requirements have met or exceeded their legal obligations and which requirements have not. Requirements that have met or exceeded their legal obligations are legally implementation ready, whereas requirements that have not met or exceeded their legal obligations need further refinement. Research is needed to better understand how to support software engineers in making these determinations. In this paper, we describe a case study in which we asked graduate-level software engineering students to assess whether a set of software requirements for an electronic health record system met or exceeded their corresponding legal obligations as expressed in regulations created pursuant to the U.S. Health Insurance Portability and Accountability Act (HIPAA). We compare the assessment made by graduate students with an assessment made by HIPAA compliance subject matter experts. Additionally, we contrast these results with those generated by a legal requirements triage algorithm. Our findings suggest that the average graduate-level software engineering student is ill-prepared to write legally compliant software with any confidence and that domain experts are an absolute necessity. Our findings also indicate the potential utility of legal requirements metrics in aiding software engineers as they make legal compliance decisions.

Satellite and aircraft observations have revealed that remarkable changes in the Earth's polar ice cover have occurred in the last decade. The impacts of these changes, which include dramatic ice loss from ice sheets and rapid declines in Arctic sea ice, could be quite large in terms of sea level rise and global climate. NASA's Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), currently planned for launch in 2015, is specifically intended to quantify the amount of change in ice sheets and sea ice and provide key insights into their behavior. It will achieve these objectives through the use of precise laser measurements of surface elevation, building on the groundbreaking capabilities of its predecessor, the Ice Cloud and Land Elevation Satellite (ICESat). In particular, ICESat-2 will measure the temporal and spatial character of ice sheet elevation change to enable assessment of ice sheet mass balance and examination of the underlying mechanisms that control it. The precision of ICESat-2's elevation measurement will also allow for accurate measurements of sea ice freeboard height, from which sea ice thickness and its temporal changes can be estimated. ICESat-2 will provide important information on other components of the Earth System as well, most notably large-scale vegetation biomass estimates through the measurement of vegetation canopy height. When combined with the original ICESat observations, ICESat-2 will provide ice change measurements across more than a 15-year time span. Its significantly improved laser system will also provide observations with much greater spatial resolution, temporal resolution, and accuracy than has ever been possible before.

Clustering support with a single-system image for large-scale Web servers is important to improve the system scalability in processing a large number of concurrent requests from Internet, especially when those requests involve resource-intensive dynamic content generation.This paper proposes scheduling optimization for a Web server cluster with a master/slave architecture which separates static and dynamic content processing.Our experimental results show that the proposed optimization using reservation-based scheduling can produce up to a 68% performance improvement.

We propose a new method for improving the average response time of Web servers by cooperatively caching the results of requests for dynamic content. The work is motivated by our recent study of access logs from the Alexandria Digital Library server at UCSB, which demonstrates that approximately a 30 percent decrease in average response time could be achieved by caching dynamically generated content. We have developed a distributed Web server called Swala, in which the nodes cooperatively cache the results of CGI requests, and the cache meta-data is stored in a replicated global cache directory. Our experiments show that the single-node performance of Swala without caching is comparable to the Netscape Enterprise server, that considerable speedups are obtained using caching, and that the cache hit ratio is substantially higher with cooperative cache than with stand-alone cache.