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Enhanced Images for Checked and Carry-on Baggage and Cargo Screening

The current X-ray systems used by airport security personnel for the detection of contraband, and objects such as knives and guns that can impact the security of a flight, have limited effect because of the limited display quality of the X-ray images. Since the displayed images do not possess optimal contrast and sharpness, it is possible for the security personnel to miss potentially hazardous objects. This problem is also common to other disciplines such as medical X-rays, and can be mitigated, to a large extent, by the use of state-of-the-art image processing techniques to enhance the contrast and sharpness of the displayed image. The NASA Langley Research Centers Visual Information Processing Group has developed an image enhancement technology that has direct applications to this problem of inadequate display quality. Airport security X-ray imaging systems would benefit considerably by using this novel technology, making the task of the personnel who have to interpret the X-ray images considerably easier, faster, and more reliable. This improvement would translate into more accurate screening as well as minimizing the screening time delays to airline passengers. This technology, Retinex, has been optimized for consumer applications but has been applied to medical X-rays on a very preliminary basis. The resultant technology could be incorporated into a new breed of commercial x-ray imaging systems which would be transparent to the screener yet allow them to see subtle detail much more easily, reducing the amount of time needed for screening while greatly increasing the effectiveness of contraband detection and thus public safety.

Woodell, Glen↗

Learning from Space Entrepreneurs

The early days of rocketry and space exploration in the United States were marked by incredibly rapid progress: a seemingly endless parade of firsts. Not coincidentally, this period also saw more than its fair share of failure, especially in the infamous "kaputnik" days prior to the successful launch of Explorer. Without a standard canon of known quantities to turn to, the early pioneers of rocketry and space flight were forced to dream up new ideas that ranged from the elegant to the bizarre and to accept the fact that the price of radical progress is occasional failure. Nowadays, rapid prototyping and testing have slowed, as we rely more and more on the extensive knowledge pined by our predecessors and on the embarrassment of riches modern engineers get from computational modeling and computer assisted design. In many cases, this leads to much improved or phenomenally more efficient designs. It also, however, fosters a culture so terrified of failure that we over-engineer and overanalyze everything, often tweaking designs for decades before a new system takes flight. (This is not a problem unique to rockets; the same phenomenon seems to have occurred in high-performance jets.) This is one reason why it was possible for President Kennedy to dream of the completion of the Mercury and Gemini missions and a successful landing on the moon in under a decade, while returning to the moon may take nearly twice as long. Lacking access to the tremendous computational resources of the national space program-and, just as importantly, removed from the harsh judgment of public shareholders or congressional appropriations committees-the hungry entrepreneurs who compete for our prizes tend not to display such fear of failure. Instead, most of them follow a rapid "build, test, fly" program. They are willing to throw a handful of concepts against the wall and see what sticks. They often go from drawing on the back of a napkin to firing engines or even flying vehicles in a matter of weeks or months, learning valuable lessons along the way. Indeed, our teams have repeatedly learned many of the most valuable lessons after only a few moments of working with real hardware-lessons that could never have been learned from a CAD drawing, like finding the failure modes of different welding practices or tracking down the interference between an onboard camera and a GPS unit. As Paul Breed, the leader of a Northrop Grumman Lunar Lander Challenge team (playfully called Unreasonable Rocket), is fond of saying, "In computer simulations the plumbing never leaks. In real life, it always does."

Pomerantz, William↗

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗

Modeling Bird Migration under Climate Change: A Mechanistic Approach

How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this behavior can be maintained over increasing and sustained environmental change. Also, the problem is much more complex than described by the current processes captured in our model. We have taken some important and interesting steps, and our model does demonstrate how local scale information about individual stop-over sites can be linked into the migratory flyway as a whole. We are incorporating additional, species specific, mechanistic processes to better reflect different climate change scenarios

Smith, James A.↗

Responding to Climate Change: Adelie Penguins Confront Astronomical and Ocean Boundaries

Long-distance migration enables many organisms to take advantage of lucrative breeding and feeding opportunities during summer at high latitudes and then to move to lower, more temperate latitudes for the remainder of the year. The latitudinal range of the Ad lie penguin spans ~ 22 deg. Penguins from northern colonies may not migrate, but due to the high latitude of Ross Island colonies, these penguins almost certainly undertake the longest migrations for the species. Previous work has suggested that Adelies require both pack ice and some ambient light at all times of year. Over a 3-yr period, which included winters of both extensive and reduced sea ice, we investigated migratory routes and characteristics and wintering locations of Adelie Penguins from two colonies of very different size on Ross Island, Ross Sea, the southernmost colonies for any penguin. We acquired data from 3-16 Geolocation Sensors affixed to penguins each year at both Cape Royds and Cape Crozier in 2003-2005. Migrations averaged 12,760 km, with the longest being 17,600 km, and were in part facilitated by pack ice movement. Trip distances varied annually, but not by colony. Penguins rarely traveled north of the main sea ice pack, and used areas with high sea-ice concentration, ranging from 75-85%, about 500 km inward from the ice edge. They also used locations where there was some twilight (2-7 hr with sun greater than 6 below horizon). We review how Adelie Penguin migration has likely changed since withdrawal of the West Antarctic Ice 35 Sheet across the Ross Sea beginning 12,000 yBP. If sea ice extent in the Ross Sea sector decreases, as predicted by climate models, we can expect change in wintering areas, the location of which ultimately may be limited more by the availability of adequate light for visual foraging than by the availability of suitable pack-ice.

Ballard, Grant↗

Processing Satellite Imagery To Detect Waste Tire Piles

A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed. The TIRe model identifies the darkest objects in the images and, on the basis of spatial and spectral image characteristics, discriminates against other dark objects, which can include vegetation, some bodies of water, and dark soils. The TIRe model can identify piles of as few as 100 tires. The output of the TIRe model is a binary mask showing areas containing suspected tire piles and spectrally similar features. This mask is overlaid on the original satellite imagery and examined by a trained image analyst, who strives to further discriminate against non-tire objects that the TIRe model tentatively identified as tire piles. After the analyst has made adjustments, the mask is used to create a synoptic, geographically accurate tire-pile survey map, which can be overlaid with a road map and/or any other map or set of georeferenced data, according to a customer s preferences.

Skiles, Joseph↗

High Performance Non-Dispersive X-Ray Spectrometers for Charge Exchange Measurements

Currently, the only measurements of cosmological charge exchange have been made using low resolution, non-dispersive spectrometers like the PSPC on ROSAT and the CCD instruments on Chandra and XMM/Newton. However, upcoming cryogenic spectrometers on Astro-H and IXO will add vast new capabilities to investigate charge exchange in local objects such as comets and planetary atmospheres. They may also allow us to observe charge exchange in extra-solar objects such as galactic supernova remnants. With low spectral resolution instruments such as CCDs, x-ray emission due to charge exchange recombination really only provides information on the acceptor species, such as the solar wind. With the new breed of x-ray calorimeter instruments, emission from charge exchange becomes highly diagnostic allowing one to uniquely determine the acceptor species, ionization state, donor species and ionization state, and the relative velocity of the interaction. We will describe x-ray calorimeter instrumentation and its potential for charge exchange measurements in the near term. We will also touch on the instrumentation behind a decade of high resolution measurements of charge exchange using an x-ray calorimeter at the Lawrence Livermore National Laboratory.

Porter Frederick↗

The Impact of Ocean Data Assimilation on Seasonal-to-Interannual Forecasts: A Case Study of the 2006 El Nino Event

This study investigates the impact of four different ocean analyses on coupled forecasts of the 2006 El Nino event. Forecasts initialized in June 2006 using ocean analyses from an assimilation that uses flow-dependent background error covariances are compared with those using static error covariances that are not flow dependent. The flow-dependent error covariances reflect the error structures related to the background ENSO instability and are generated by the coupled breeding method. The ocean analyses used in this study result from the assimilation of temperature and salinity, with the salinity data available from Argo floats. Of the analyses, the one using information from the coupled bred vectors (BV) replicates the observed equatorial long wave propagation best and exhibits more warming features leading to the 2006 El Nino event. The forecasts initialized from the BV-based analysis agree best with the observations in terms of the growth of the warm anomaly through two warming phases. This better performance is related to the impact of the salinity analysis on the state evolution in the equatorial thermocline. The early warming is traced back to salinity differences in the upper ocean of the equatorial central Pacific, while the second warming, corresponding to the mature phase, is associated with the effect of the salinity assimilation on the depth of the thermocline in the western equatorial Pacific. The series of forecast experiments conducted here show that the structure of the salinity in the initial conditions is important to the forecasts of the extension of the warm pool and the evolution of the 2006 El Ni o event.

Yang, Shu-Chih↗

Gas Exchange, Transpiration and Yield of Sweetpotato Grown in a Controlled Environment

Sweetpotato was grown to harvest maturity within NASA Johnson Space Center's Variable Pressure Growth Chamber (VPGC) to characterize crop performance for potential use in advanced life support systems as a contributor to food production, air revitalization and resource recovery. Stem cuttings of breeding clone "TU-82-155" were grown hydroponically at a density of 17 plants m(sup -2) using a modified pressure-plate growing system (Patent No. 4860-490, Tuskegee University). Lighting was provided by HPS lamps at a photoperiod of 12h light: 12h dark. The photosynthetic photon flux was maintained at 500, 750 and 1000 micro mol m(sup -2) s(sub -1) during days 1-15, 16-28, 29-119, respectively. Canopy temperatures were maintained at 28 C: light: 22 C:dark. During the light period, relative humidity and carbon dioxide were maintained at 70% and 1200 micro liters l(sup -1), respectively. Nutrient solution was manually adjusted 2 to 4 times per week by addition of 10X concentrated modified half-strength Hoagland nutrient salts and NaOH to return the electrical conductivity and pH to 1.2 mS cm(sup -1) and 6.0, respectively. At 17 weeks (119 days) from transplanting, a total of 56.5 kilograms fresh mass of storage roots (84.1% moisture) were harvested from the 11.2 m(sup 2) chamber, resulting in a yield 5.0 kilograms m(sup -2). Harvest index, based on fresh mass, was 38.6%. Rates of net photosynthesis, dark respiration, transpiration, and ethylene production will be reported.

Barta, Daniel J.↗

Comparison of Two Digital Stethoscopes with the Traditional Stethoscope Used on International Space Station

A traditional stethoscope is currently flown on the International Space Station (ISS). The background noise on the ISS is much higher than a normal exam room, and the literature shows that traditional stethoscopes are unable to function effectively in high noise environments. Digital stethoscopes provide amplification which improves the audibility in a quiet environment. This study is designed to determine if digital stethoscopes offer any advantage over traditional stethoscopes in being able to identify normal and abnormal sounds in the ISS noise environment. Methods: An ISS noise simulation facility was created to reproduce ISS noise profiles by modifying pink noise with a software-based graphic equalizer. The files were played in a continuous loop on a computer, amplified through a high-end stereo system and adjusted using a sound level meter. Nine caregiver analogues were given the same auscultation lesson received by astronauts. They began testing by becoming familiar with normal and abnormal sounds on a Student Auscultation Manikin . They then used two digital stethoscopes and a traditional stethoscope identical to the one flown on the ISS to auscultate the manikin sounds in the noise facility. They identified the sounds on a questionnaire and picked which of the three stethoscopes they preferred. Results: Evaluators displayed equivalent accuracy in sound identification when using either the 3M model 4000 digital stethoscope or traditional stethoscope. However, the 3M was preferred 2 to 1 by the evaluators, primarily because of additional amplification of the sounds. Discussion: Although our results show that the current ISS stethoscope and the "best-of-breed" digital stethoscope provide essentially the same auscultation utility, the latter has the advantage of recording and transmitting sounds to a remote physician. Since the astronaut caregivers are non-physiCians, this capability may be worth the additional expense and effort needed to certify the digital stethoscope for flight.

Rasbury, Jack↗

Relationships Between Seed Weight, Germination Potential and Biochemical Reserves of Maritime Pine in Morocco: Elements for Tree Seedlings Improvement

Selection of quality seeds in breeding programs can significantly improve seedling productivity. Germination and biochemical analyses on seeds from ten natural populations of maritime pine (Pinus pinaster Ait.) in Morocco reveals significant differences among populations in seed weight, germination characters and protein content in both dry seeds and megagametophytes. During germination, the mobilization of protein content in megagametophyte is significantly different among populations than sugar content. A strong positive correlation between the germination capacity and the protein content in both dry seeds and megagametophytes indicates that the best populations in term of germination capacity may also be the richest in protein content. The present study finds that seed weight is not a good indicator for quality seed selection, nor is it recommended to increase the degree of germinability. Our results suggest that the pine population in southern Morocco might have adapted to drought conditions as it is characterized by heavy seed weight and lower speed of protein content mobilization in megagametophyte compared to northern populations growing in temperate climate.

Wahid, Nadya↗

Evaluating Cloud Computing in the Proposed NASA DESDynI Ground Data System

The proposed NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission would be a first-of-breed endeavor that would fundamentally change the paradigm by which Earth Science data systems at NASA are built. DESDynI is evaluating a distributed architecture where expert science nodes around the country all engage in some form of mission processing and data archiving. This is compared to the traditional NASA Earth Science missions where the science processing is typically centralized. What's more, DESDynI is poised to profoundly increase the amount of data collection and processing well into the 5 terabyte/day and tens of thousands of job range, both of which comprise a tremendous challenge to DESDynI's proposed distributed data system architecture. In this paper, we report on a set of architectural trade studies and benchmarks meant to inform the DESDynI mission and the broader community of the impacts of these unprecedented requirements. In particular, we evaluate the benefits of cloud computing and its integration with our existing NASA ground data system software called Apache Object Oriented Data Technology (OODT). The preliminary conclusions of our study suggest that the use of the cloud and OODT together synergistically form an effective, efficient and extensible combination that could meet the challenges of NASA science missions requiring DESDynI-like data collection and processing volumes at reduced costs.

Benchmark↗

Real-Time Wireless Data Acquisition System

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Valencia, Emilio J.↗

Decline of Monarch Butterflies Overwintering in Mexico- Is the Migratory Phenomenon at Risk?

1.During the 2009-2010 overwintering season and following a 15-year downward trend, the total area in Mexico occupied by the eastern North American population of overwintering monarch butterflies reached an all-time low. Despite an increase, it remained low in 2010-2011. 2. Although the data set is small, the decline in abundance is statistically significant using both linear and exponential regression models. 3. Three factors appear to have contributed to reduce monarch abundance: degradation of the forest in the overwintering areas; the loss of breeding habitat in the United States due to the expansion ofGM herbicide-resistant crops, with consequent loss of milkweed host plants, as well as continued land development; and severe weather. 4. This decline calls into question the long-term survival of the monarchs' migratory phenomenon

Habitat↗

Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground‐based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010‐2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

Morin, Cory↗

Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.

Morin, Cory↗

Investigating the Simulink Auto-Coding Process

Model based program design is the most clear and direct way to develop algorithms and programs for interfacing with hardware. While coding "by hand" results in a more tailored product, the ever-growing size and complexity of modern-day applications can cause the project work load to quickly become unreasonable for one programmer. This has generally been addressed by splitting the product into separate modules to allow multiple developers to work in parallel on the same project, however this introduces new potentials for errors in the process. The fluidity, reliability and robustness of the code relies on the abilities of the programmers to communicate their methods to one another; furthermore, multiple programmers invites multiple potentially differing coding styles into the same product, which can cause a loss of readability or even module incompatibility. Fortunately, Mathworks has implemented an auto-coding feature that allows programmers to design their algorithms through the use of models and diagrams in the graphical programming environment Simulink, allowing the designer to visually determine what the hardware is to do. From here, the auto-coding feature handles converting the project into another programming language. This type of approach allows the designer to clearly see how the software will be directing the hardware without the need to try and interpret large amounts of code. In addition, it speeds up the programming process, minimizing the amount of man-hours spent on a single project, thus reducing the chance of human error as well as project turnover time. One such project that has benefited from the auto-coding procedure is Ramses, a portion of the GNC flight software on-board Orion that has been implemented primarily in Simulink. Currently, however, auto-coding Ramses into C++ requires 5 hours of code generation time. This causes issues if the tool ever needs to be debugged, as this code generation will need to occur with each edit to any part of the program; additionally, this is lost time that could be spent testing and analyzing the code. This is one of the more prominent issues with the auto-coding process, and while much information is available with regard to optimizing Simulink designs to produce efficient and reliable C++ code, not much research has been made public on how to reduce the code generation time. It is of interest to develop some insight as to what causes code generation times to be so significant, and determine if there are architecture guidelines or a desirable auto-coding configuration set to assist in streamlining this step of the design process for particular applications. To address the issue at hand, the Simulink coder was studied at a foundational level. For each different component type made available by the software, the features, auto-code generation time, and the format of the generated code were analyzed and documented. Tools were developed and documented to expedite these studies, particularly in the area of automating sequential builds to ensure accurate data was obtained. Next, the Ramses model was examined in an attempt to determine the composition and the types of technologies used in the model. This enabled the development of a model that uses similar technologies, but takes a fraction of the time to auto-code to reduce the turnaround time for experimentation. Lastly, the model was used to run a wide array of experiments and collect data to obtain knowledge about where to search for bottlenecks in the Ramses model. The resulting contributions of the overall effort consist of an experimental model for further investigation into the subject, as well as several automation tools to assist in analyzing the model, and a reference document offering insight to the auto-coding process, including documentation of the tools used in the model analysis, data illustrating some potential problem areas in the auto-coding process, and recommendations on areas or practices in the current Ramses model that should be further investigated. Several skills were required to be built up over the course of the internship project. First and foremost, my Simulink skills have improved drastically, as much of my experience had been modeling electronic circuits as opposed to software models. Furthermore, I am now comfortable working with the Simulink Auto-coder, a tool I had never used until this summer; this tool also tested my critical thinking and C++ knowledge as I had to interpret the C++ code it was generating and attempt to understand how the Simulink model affected the generated code. I had come into the internship with a solid understanding of Matlab code, but had done very little in using it to automate tasks, particularly Simulink tasks; along the same lines, I had rarely used shell script to automate and interface with programs, which I gained a fair amount of experience with this summer, including how to use regular expression. Lastly, soft-skills are an area everyone can continuously improve on; having never worked with NASA engineers, which to me seem to be a completely different breed than what I am used to (commercial electronic engineers), I learned to utilize the wealth of knowledge present at JSC. I wish I had come into the internship knowing exactly how helpful everyone in my branch would be, as I would have picked up on this sooner. I hope that having gained such a strong foundation in Simulink over this summer will open the opportunity to return to work on this project, or potentially other opportunities within the division. The idea of leaving a project I devoted ten weeks to is a hard one to cope with, so having the chance to pick up where I left off sounds appealing; alternatively, I am interested to see if there are any opening in the future that would allow me to work on a project that is more in-line with my research in estimation algorithms. Regardless, this summer has been a milestone in my professional career, and I hope this has started a long-term relationship between JSC and myself. I really enjoy the thought of building on my experience here over future summers while I work to complete my PhD at Missouri University of Science and Technology.

Gualdoni, Matthew J.↗