5825 University Research Ct

Stevens Point, MD, United States

5825 University Research Ct

Stevens Point, MD, United States
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Lindvall M.,5825 University Research Ct | Porter A.,5825 University Research Ct | Magnusson G.,5825 University Research Ct | Schulze C.,5825 University Research Ct
Proceedings - 2017 IEEE/ACM 2nd International Workshop on Metamorphic Testing, MET 2017 | Year: 2017

Testing becomes difficult when we cannot easily determine whether or not the system under test delivers the correct result. Autonomous systems are a case in point because it is difficult to determine whether a safety-critical autonomous system's behavior meets its specifications. To address the problem of testing autonomous drones, we have developed a framework for automated testing of a simulated autonomous drone system using metamorphic testing principles combined with model-based testing. Based on the results from using the framework to test the drone in the simulator using obstacles that do not move during flight, we have determined that this is a cost beneficial solution allowing for comprehensive testing without having to develop complex testing infrastructure to determine detailed test oracles. Our test cases are automatically generated from a set of testing models where each model encodes a certain scenario that can be varied according to metamorphic principles. © 2017 IEEE.

Zhou Y.,5825 University Research Ct | Gurney K.R.,Arizona State University
Global Biogeochemical Cycles | Year: 2011

Quantification of the spatial distribution of sector-specific fossil fuel CO 2 emissions provides strategic information to public and private decision makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO 2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO 2 emissions differ substantially and these differences are sector-specific. Area-based sources such as those in the residential and commercial sectors are driven by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO 2 emissions confirms that counties with high (low) CO 2 emissions tend to be clustered close to other counties with high (low) CO 2 emissions and some of the spatial clustering extends to multistate spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multistate perspective. Our findings underscore the potential for geographically focused, sector-specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements. Copyright 2011 by the American Geophysical Union.

Zhang X.,South Dakota State University | Tan B.,Earth Resources Technology Inc. | Yu Y.,5825 University Research Ct
International Journal of Biometeorology | Year: 2014

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than 1 % in most of climate regions although it could be as large as 10 %. © 2014 ISB.

Zhang H.,University of Maryland Baltimore County | Lyapustin A.,University of Maryland Baltimore County | Wang Y.,University of Maryland Baltimore County | Kondragunta S.,5825 University Research Ct | And 3 more authors.
Atmospheric Chemistry and Physics | Year: 2011

Aerosol optical depth (AOD) retrievals from geostationary satellites have high temporal resolution compared to the polar orbiting satellites and thus enable us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosols and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) in the channel 1 of GOES is proportional to seasonal average MODIS BRDF in the 2.1 Î1/4m channel. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of AOD and surface reflectance retrievals are evaluated through comparisons against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US with correlation coefficients ranges from 0.71 to 0.85 at five out of six sites. At the two western sites Railroad Valley and UCSB, the MAIAC AOD retrievals have correlations of 0.8 and 0.85 with AERONET AOD, and are more accurate than GASP retrievals, which have correlations of 0.7 and 0.74 with AERONET AOD. At the three eastern sites, the correlations with AERONET AOD are from 0.71 to 0.81, comparable to the GASP retrievals. In the western US where surface reflectance is higher than 0.15, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS. © 2011 Author(s).

Zazworka N.,5825 University Research Ct | Seaman C.,University of Maryland Baltimore County | Shull F.,5825 University Research Ct
Proceedings - International Conference on Software Engineering | Year: 2011

Technical debt is the technical work developers owe a system, typically caused by speeding up development, e.g. before a software release. Approaches, such as code smell detection, have been developed to identify particular kinds of debt, e.g. design debt. Up until now, code smell detection has been used to help point to components that need to be freed from debt by refactoring. To date, a number of methods have been described for finding code smells in a system. However, typical debt properties, such as the value of the debt and interest rate to be paid, have not been well established. This position paper proposes an approach to using cost/benefit analysis to prioritize technical debt reduction work by ranking the value and interest of design debt caused by god classes. The method is based on metric analysis and software repository mining and is demonstrated on a commercial software application at a mid-size development company. The results are promising: the method helps to identify which refactoring activities should be performed first because they are likely to be cheap to make yet have significant effect, and which refactorings should be postponed due to high cost and low payoff. © 2011 ACM.

Nair S.,Certus Center for Software VandV | De La Vara J.L.,Certus Center for Software VandV | Sabetzadeh M.,University of Luxembourg | Falessi D.,5825 University Research Ct
Information and Software Technology | Year: 2015

Context Demonstrating compliance of critical systems with safety standards involves providing convincing evidence that the requirements of a standard are adequately met. For large systems, practitioners need to be able to effectively collect, structure, and assess substantial quantities of evidence. Objective This paper aims to provide insights into how practitioners deal with safety evidence management for critical computer-based systems. The information currently available about how this activity is performed in the industry is very limited. Method We conducted a survey to determine practitioners' perspectives and practices on safety evidence management. A total of 52 practitioners from 15 countries and 11 application domains responded to the survey. The respondents indicated the types of information used as safety evidence, how evidence is structured and assessed, how evidence evolution is addressed, and what challenges are faced in relation to provision of safety evidence. Results Our results indicate that (1) V&V artefacts, requirements specifications, and design specifications are the most frequently used safety evidence types, (2) evidence completeness checking and impact analysis are mostly performed manually at the moment, (3) text-based techniques are used more frequently than graphical notations for evidence structuring, (4) checklists and expert judgement are frequently used for evidence assessment, and (5) significant research effort has been spent on techniques that have seen little adoption in the industry. The main contributions of the survey are to provide an overall and up-to-date understanding of how the industry addresses safety evidence management, and to identify gaps in the state of the art. Conclusion We conclude that (1) V&V plays a major role in safety assurance, (2) the industry will clearly benefit from more tool support for collecting and manipulating safety evidence, and (3) future research on safety evidence management needs to place more emphasis on industrial applications. ©2014 Elsevier B.V. All rights reserved.

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