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Fast Solution in Sparse LDA for Binary Classification

An algorithm that performs sparse linear discriminant analysis (Sparse-LDA) finds near-optimal solutions in far less time than the prior art when specialized to binary classification (of 2 classes). Sparse-LDA is a type of feature- or variable- selection problem with numerous applications in statistics, machine learning, computer vision, computational finance, operations research, and bio-informatics. Because of its combinatorial nature, feature- or variable-selection problems are NP-hard or computationally intractable in cases involving more than 30 variables or features. Therefore, one typically seeks approximate solutions by means of greedy search algorithms. The prior Sparse-LDA algorithm was a greedy algorithm that considered the best variable or feature to add/ delete to/ from its subsets in order to maximally discriminate between multiple classes of data. The present algorithm is designed for the special but prevalent case of 2-class or binary classification (e.g. 1 vs. 0, functioning vs. malfunctioning, or change versus no change). The present algorithm provides near-optimal solutions on large real-world datasets having hundreds or even thousands of variables or features (e.g. selecting the fewest wavelength bands in a hyperspectral sensor to do terrain classification) and does so in typical computation times of minutes as compared to days or weeks as taken by the prior art. Sparse LDA requires solving generalized eigenvalue problems for a large number of variable subsets (represented by the submatrices of the input within-class and between-class covariance matrices). In the general (fullrank) case, the amount of computation scales at least cubically with the number of variables and thus the size of the problems that can be solved is limited accordingly. However, in binary classification, the principal eigenvalues can be found using a special analytic formula, without resorting to costly iterative techniques. The present algorithm exploits this analytic form along with the inherent sequential nature of greedy search itself. Together this enables the use of highly-efficient partitioned-matrix-inverse techniques that result in large speedups of computation in both the forward-selection and backward-elimination stages of greedy algorithms in general.

Moghaddam, Baback↗

Optimizing Air Transportation Service to Metroplex Airports: Analysis of Historical Data - Part 1

The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation (+4% annual growth), resulting in unreliable service and systemic delays. Estimates of the impact of delays and unreliable air transportation service on the economy range from $32B to $41B per year. This report describes the results of an analysis of airline strategic decision-making with regards to: (1) geographic access, (2) economic access, and (3) airline finances. This analysis evaluated markets-served, scheduled flights, aircraft size, airfares, and profit from 2005-2009. During this period, airlines experienced changes in costs of operation (due to fluctuations in hedged fuel prices), changes in travel demand (due to changes in the economy), and changes in infrastructure capacity (due to the capacity limits at EWR, JFK, and LGA). This analysis captures the impact of the implementation of capacity limits at airports, as well as the effect of increased costs of operation (i.e. hedged fuel prices). The increases in costs of operation serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed.

Donohue, George↗

The Potential for Hosted Payloads at NASA

The 2010 National Space Policy encourages federal agencies to actively explore the use of inventive, nontraditional arrangements for acquiring commercial space goods and services to meet United States Government requirements, including...hosting government capabilities on commercial spacecraft. NASA's Science Mission Directorate has taken an important step towards this goal by adding an option for hosted payload responses to its recent Announcement of Opportunity (AO) for Earth Venture-2 missions. Since NASA selects a significant portion of its science missions through a competitive process, it is useful to understand the implications that this process has on the feasibility of successfully proposing a commercially hosted payload mission. This paper describes some of the impediments associated with proposing a hosted payload mission to NASA, and offers suggestions on how these impediments might be addressed. Commercially hosted payloads provide a novel way to serve the needs of the science and technology demonstration communities at a fraction of the cost of a traditional Geostationary Earth Orbit (GEO) mission. The commercial communications industry launches over 20 satellites to GEO each year. By exercising this repeatable commercial paradigm of privately financed access to space with proven vendors, NASA can achieve science goals at a significantly lower cost than the current dedicated spacecraft and launch vehicle approach affords. Commercial hosting could open up a new realm of opportunities for NASA science missions to make measurements from GEO. This paper also briefly describes two GEO missions recommended by the National Academies of Science Earth Science Decadal Survey, the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Precipitation and All-weather Temperature and Humidity (PATH) mission. Hosted payload missions recently selected for implementation by the Office of the Chief Technologist are also discussed. Finally, there are technical differences specific to hosted payloads and the GEO environment that must be considered when planning and developing a hosted payload mission. This paper addresses some of payload accommodation differences from the typical NASA LEO mission, including spacecraft interfaces, attitude control and knowledge, communications, data handling, mission operations, ground systems, and the thermal, radiation, and electromagnetic environment. The paper also discusses technical and programmatic differences such as limits to NASA's involvement with commercial quality assurance processes to conform to the commercial schedule and minimizing the price that makes hosted payloads an attractive option.

Andraschko, Mark↗

Report on the 2011 and 2012 NASA Ames Research Center (ARC) / Alaska State Cargo Airship Workshops

This presentation will summarize the Cargo Airships for Northern Operations workshop that was held August 24-25, 2011. This workshop co-sponsored by NASA ARC and the Alaska State Department of Transportation was initiated by interest from Alaska Lt. Governor Mead Treadwell for assistance in investigating the potential benefits of proposed cargo airships for the Alaskan economy and societal needs. The workshop provided a brief background on the technology and operational aspects of conventional airships and hybrids followed by presentations on issues affecting cargo airship operations such as weather management, insurance, regulations, crew duty/rest rules, and available support infrastructures. Speakers representing potential cargo airship users from Alaskan State and commercial organizations presented the needs they felt could be met by cargo airship services. Presenters from Canadian private and military interests also detailed applications and missions that cargo airships could provide to remote regions of Canada. Cost drivers of cargo airship operations were also addressed and tools for modeling and analyzing operational factors and costs affecting cargo airship operations were discussed. Four breakout sessions were held which allowed workshop participants to contribute inputs to four topic areas: Business Approaches and Strategies (financing incentives public/private partnerships etc) for Airship Development and Operation, Design, Development, Production Challenges, and Possible Solutions, Regulatory, Certification, Legal, and Insurance Issues, and Operational Issues, Customer Requirements, and Airship Requirements. A follow on to the 2011 cargo airship workshop is being planned for July 31 August 2, 2012. A status update on this second workshop will also be presented.

Hochstettler, Ronald↗

High Resolution Visualization Applied to Future Heavy Airlift Concept Development and Evaluation

This paper explores the use of high resolution 3D visualization tools for exploring the feasibility and advantages of future military cargo airlift concepts and evaluating compatibility with existing and future payload requirements. Realistic 3D graphic representations of future airlifters are immersed in rich, supporting environments to demonstrate concepts of operations to key personnel for evaluation, feedback, and development of critical joint support. Accurate concept visualizations are reviewed by commanders, platform developers, loadmasters, soldiers, scientists, engineers, and key principal decision makers at various stages of development. The insight gained through the review of these physically and operationally realistic visualizations is essential to refining design concepts to meet competing requirements in a fiscally conservative defense finance environment. In addition, highly accurate 3D geometric models of existing and evolving large military vehicles are loaded into existing and proposed aircraft cargo bays. In this virtual aircraft test-loading environment, materiel developers, engineers, managers, and soldiers can realistically evaluate the compatibility of current and next-generation airlifters with proposed cargo.

FordCook, A. B.↗

The Princess Elisabeth Station

Aware of the increasing impact of human activities on the Earth system, Belgian Science Policy Office (Belspo) launched in 1997 a research programme in support of a sustainable development policy. This umbrella programme included the Belgian Scientific Programme on Antarctic Research. The International Polar Foundation, an organization led by the civil engineer and explorer Alain Hubert, was commissioned by the Belgian Federal government in 2004 to design, construct and operate a new Belgian Antarctic Research Station as an element under this umbrella programme. The station was to be designed as a central location for investigating the characteristic sequence of Antarctic geographical regions (polynia, coast, ice shelf, ice sheet, marginal mountain area and dry valleys, inland plateau) within a radius of 200 kilometers (approx.124 miles) of a selected site. The station was also to be designed as "state of the art" with respect to sustainable development, energy consumption, and waste disposal, with a minimum lifetime of 25 years. The goal of the project was to build a station and enable science. So first we needed some basic requirements, which I have listed here; plus we had to finance the station ourselves. Our most important requirement was that we decided to make it a zero emissions station. This was both a philosophical choice as we thought it more consistent with Antarctic Treaty obligations and it was also a logistical advantage. If you are using renewable energy sources, you do not have to bring in all the fuel.

Berte, Johan↗

Moving Technologies from the Test Tube to Commercial Products

Successful technologies include objects, processes, and procedures that share a common theme; they are being used to generate new products that create economic growth. The foundation is the invention, but the invention is a small part of the overall effort. The pathway to success is understanding the competition, proper planning, record keeping, integrating a supply chain, understanding actual costs, intellectual property (IP), benchmarking, and timing. Additionally, there are obstacles that include financing, what to make, buy, and sell, and the division of labor i.e. recognizing who is best at what task. Over the past two decades, NASA Langley Research Center (LaRC) has developed several commercially available technologies. The approach to commercialization of three of these inventions; Langley Research Center-Soluble Imide (LaRC-SI, Imitec Inc.), the Thin Layer Unimorph Driver (THUNDER, FACE International), and the Macrofiber Composite (MFC, Smart Material Corp.) will be described, as well as some of the lessons learned from the process. What makes these three inventions interesting is that one was created in the laboratory; another was built using the previous invention as part of its process, and the last one was created by packaging commercial-off-the-shelf (COTS) materials thereby creating a new component.

Bryant, Robert G.↗

No Need to Wait for the Clean Air Dividend

Controlling smog and soot is the classic win-win situation, so it's great that the world is finally waking up to the idea. WHAT if there was a way to simultaneously slow down climate change, save millions of lives, improve crop yields and contribute to sustainable development and energy security? It sounds too good to be true, but it is possible. It won't be free or easy, but with some effort and moderate investment, it can be done. The way to do it is to reduce emissions leading to two types of pollution: black carbon and ozone. These are the only pollutants that we know contribute to both global warming and poor air quality. Black carbon is essentially soot, emitted from incomplete combustion of fossil fuels and biomass. It warms the climate in two ways: by absorbing heat in the atmosphere - similar to the greenhouse effect - and by reducing Earth's albedo, or ability to reflect sunlight. Inhaled into the lungs, it leads to cancer and cardiovascular disease. Ozone in the atmosphere also acts as a greenhouse gas, while ground-level ozone is toxic to humans and plants, so leads to both premature death and reduced crop yields. Ozone is not emitted directly but is produced by the action of sunlight on other pollutants, which are known as ozone precursors. Since black carbon and ozone are important components of soot and smog, a great deal of effort has already been put into developing methods to reduce emissions. So effective technology is available, but needs wider implementation. The recommended control measures for black carbon include widespread and tight emission standards on diesel cars and trucks; improved solid fuel cooking stoves, brick kilns and coke ovens in the developing world; and a ban on the open burning of agricultural waste. Implementation of these measures would have a rapid impact on the climate and human health, and also have the added benefit of greatly reducing emissions of carbon monoxide, an important ozone precursor. A second key ozone precursor is methane, which is also a powerful greenhouse gas in its own right. Control measures include reducing leaks from natural gas pipelines and storage tanks, and capturing it from coal, gas and oil extraction, landfills and wastewater treatment plants. Aeration of rice paddies and manure management can also reduce methane releases. Captured methane can often be sold or turned into power. In Monterrey, Mexico, for example, electricity generated from methane collected from the city landfill powers the public transportation system. So such measures can be beneficial even when ignoring the health and climate effects, as they can contribute to energy security and often pay for themselves. According to calculations by me and my colleagues, phasing in all these measures over the next 20 years would reduce global warming by about 0.5 degC in 2050, half of the projected increase between now and then (Science, vol 335, p 183). Regional benefits would be even greater, as black carbon disrupts rainfall patterns and magnifies warming and melting of snow and ice in parts of the world including the Arctic and the Himalayas. On top of the climate benefits, cutting black carbon and ozone would prevent over 3 million premature deaths from air pollution, and increase yields of staple crops by roughly 50 million tonnes a year. Improved cooking stoves would also decrease the demand for firewood in the developing world, reducing deforestation and freeing up time for those who collect wood - primarily women and children - to pursue other activities such as education. Similarly, improved brick kilns now being used in parts of Latin America and Asia require half as much fuel as traditional ones and are less time-intensive for the operators. This means that in addition to their environmental benefits, these measures can contribute to sustainable and human development. Tackling black carbon and methane is clearly a great idea, so why hasn't it been done already? There are many barriers. The upfront costs of some measures can be prohibitive even when they eventually pay for themselves. But this can be overcome by mechanisms such as international financing of capital costs. For other measures, the costs are typically borne by a few while the benefits accrue to everybody. In such cases civil society and governments must get involved. Governments are starting to act. In February, the US, Canada, Sweden, Bangladesh, Ghana and Mexico launched the Climate and Clean Air Coalition to support implementation of measures like these. This coalition will hopefully expand and achieve rapid, widespread adoption of measures to cut black carbon and ozone. While the climate benefits will be substantial, it is important to note that these measures cannot substitute for cuts in carbon dioxide. Black carbon, ozone, carbon monoxide and methane stay in the atmosphere for a fairly short time - a few days for black carbon and about a decade for methane. They thus respond quickly to emissions changes and give us substantial leverage over near-term climate change. In contrast, carbon dioxide is very long-lived and so responds slowly to emissions changes. This means that cuts have little immediate impact, but it also means they must be made now to avoid disastrous changes later on. Controlling short-lived climate pollutants is thus an issue of fairness. Much as failure to reduce carbon dioxide emissions soon would condemn future generations to disastrous change, failure to reduce near-term climate change condemns those alive today to suffer worsening effects of the sort already seen. Some wonder if we really can do both. We can, and we must.

Shindell, Drew↗

ARC3.2 Summary for City Leaders Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network

ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

Ecosystems↗

Climate Science for Decision-Making in the New York Metropolitan Region

New York City is one of the world's most vulnerable cities to coastal flooding, due to a high concentration of population and assets near a coastline exposed to warm-season tropical storms and cold -season Nor'easter storms. Among U.S. cities, New York City is second only to New Orleans in population living less than 4 ft above the local high tide. By the 2050s, average annual losses due to coastal flooding alone could exceed $2 billion for the combined New York City-Newark region. Perhaps the most iconic example of a vulnerable New York City asset is the financial district located at the southern tip of Manhattan, however low-lying coastal assets include the full complement of major highways, subways and tunnels, hospitals, schools, wastewater treatment plants, food distribution centers, and people's homes. Given the magnitude of the assets at risk, a compelling case can be made that long-term adaptation makes economic sense for New York City. Given New York's access to economic, human, and technological resources for resilience measures, the City may be able to achieve this resilience. The city's political environment-New York City is a place where climate science is generally not a partisan issue-and the city's experience with uncertainty and overall risk framing (e.g., financing of bond issues for multi-billion dollar infrastructure with multidecade expected lifetimes), encourage climate risk framing.

Horton, Radley↗

Robust Exploration and Commercial Missions to the Moon Using LANTR Propulsion and In-Situ Propellants Derived From Lunar Polar Ice (LPI) Deposits

Since the 1960s, scientists have conjectured that water icecould survive in the cold, permanently shadowed craters located at the Moons poles Clementine (1994), Lunar Prospector (1998),Chandrayaan-1 (2008), and Lunar Reconnaissance Orbiter (LRO) and Lunar CRater Observation and Sensing Satellite(LCROSS) (2009) lunar probes have provided data indicating the existence of large quantities of water ice at the lunar poles The Mini-SAR onboard Chandrayaan-1discovered more than 40 permanently shadowed craters near the lunar north pole that are thought to contain 600 million metric tons of water ice. Using neutron spectrometer data, the Lunar Prospector science team estimated a water ice content (1.5 +-0.8 wt in the regolith) found in the Moons polar cold trap sand estimated the total amount of water at both poles at 2 billion metric tons Using Mini-RF and spectrometry data, the LRO LCROSS science team estimated the water ice content in the regolith in the south polar region to be 5.6 +-2.9 wt. On the basis of the above scientific data, it appears that the water ice content can vary from 1-10 wt and the total quantity of LPI at both poles can range from 600 million to 2 billion metric tons NTP offers significant benefits for lunar missions and can take advantage of the leverage provided from using LDPs when they become available by transitioning to LANTR propulsion. LANTR provides a variablethrust and Isp capability, shortens burn times and extends engine life, and allows bipropellant operation The combination of LANTR and LDP has performance capability equivalent to that of a hypothetical gaseousfuel core NTR (effective Isp 1575 s) and can lead to a robust LTS with unique mission capabilities that include short transit time crewed cargo transports and routine commuter flights to the Moon The biggest challenge to making this vision a reality will be the production of increasing amounts of LDP andthe development of propellant depots in LEO, LLO and LPO. An industry-operated, privately financed venture, with NASA as its initial customer, might provide a possible blueprint for future development and operation With industry interested in developing cislunar space and commerce, and competitive forces at work, the timeline for developing this capability could well be accelerated, quicker than any of us can imagine, and just the beginning of things to come.

Nuclear Thermal Propulsion↗

Identifying Climate-Smart Agriculture Research Needs

Climate-smart agriculture (CSA) is an approach to help agricultural systems worldwide, concurrently addressing three challenge areas: increased adaptation to climate change, mitigation of climate change, and ensuring global food security - through innovative policies, practices, and financing. It involves a set of objectives and multiple transformative transitions for which there are newly identified knowledge gaps. We address these questions raised by CSA within three areas: conceptualization, implementation, and implications for policy and decision-makers. We also draw up scenarios on the future of the CSA concept in relation to the 4 per 1000 Initiative (Soils for Food Security and Climate) launched at UNFCCC 21st Conference of the Parties (COP 21). Our analysis shows that there is still a need for further interdisciplinary research on the theoretical foundation of the CSA concept and on the necessary transformations of agriculture and land use systems. Contrasting views about implementation indicate that CSA focus on the ''triple win'' (adaptation, mitigation, food security) needs to be assessed in terms of science-based practices. CSA policy tools need to incorporate an integrated set of measures supported by reliable metrics. Environmental and social safeguards are necessary to make sure that CSA initiatives conform to the principles of sustainability, both at the agriculture and food system levels.

mitigation↗

The Discovery of the Antarctic Ozone Hole

The author Nassim Taleb has coined the term ‘‘Black Swan’’ event to describe a very low probability event that come as a surprise and has a major effect in the field in which it occurs. He suggests that such events have occurred in history, finance, science, and technology more frequently than one can expect from stochastic theory. The discovery of the Antarctic Ozone Hole fits this description well. In this paper, we describe the events surrounding this discovery and the role of NASA satellite data before and soon after the seminal paper by Farman et al., in May 1985 that first brought this phenomenon to the attention of the broader science community.

Bhartia, Pawan Kumar↗

Application of Machine Learning Techniques to Aviation Operations: Promises and Challenges

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This paper compares the methodology used in and issues to be addressed in applying either model-driven or data-driven methods. Some aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for data-driven methods. The application of MLT to aviation operations falls into three categories: (a) based on the lack of a physics-based model, MLT is the favored approach, (b) marginal difference between regression methods using physics-based models and MLT and (c) better results using a blend of physics-based methods combined with MLT. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Observations on the Application of Machine Learning Techniques to Aviation Operations

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories: (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Application of Machine Learning Techniques to Aviation Operations: A Case Study

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories 58; (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Application of Machine Learning Techniques to Aviation Operations: NASA Case Studies

There is an increasing interest in applying methods based on Machine Learning Techniques(MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues relating to data, feature selection and validation of the models are illustrated by examining case studies of the application of MLT to problems in air traffic management at NASA. Further research is needed in the application of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Lessons Learned in the Application of Machine Learning Techniques to Air Traffic Management

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in Air Traffic Management (ATM). The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large databases. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The promises and challenges in applying MLT to ATM is traced through three examples based on the authors’ experience, each separated by a decade, to show the influence of data and feature selection in the successful application of MLT to ATM. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Machine Learning Techniques↗