Matching Items (7)

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Using Language Generation to Create Weather Forecasts

Description

The face of computing is constantly changing. Wearable computers in the form of glasses or watches are becoming more and more common. These devices have very small screens (measured in

The face of computing is constantly changing. Wearable computers in the form of glasses or watches are becoming more and more common. These devices have very small screens (measured in millimeters), and users often interact with them through voice input and audio feedback. Weather is one of the most regularly checked app category on smart devices, but weather results on these devices are often limited to raw data, canned responses, or sentence templates with numbers plugged in. The goal for this project was to build a system that could generate weather forecast text, which could then be read to a user through text-to-speech. By using methods in language generation, the system can generate weather forecast text in millions of different ways. This is all computed locally, and it covers every possible weather case. In order to generate natural weather forecast texts, the system retrieved raw weather data from a weather API and created the text through six methods: content determination, document structuring, sentence aggregation, lexical choice, referring expression generation, and text realization. Content determination is the process of deciding on what information to include in a computer generated text. The document structuring phase deals with the order and structure of the information. Sentence aggregation is the merging of similar sentences to improve readability and to reduce redundancy. Lexical choice is the process of putting words to concepts. Referring expression generation is the process of identifying objects, regions, time periods, and locations within a text. Finally text realization involves creating sentences with proper syntax, morphology, and orthography. Through these six stages, a system was developed that could generate unique weather forecast text from raw data accurately and efficiently. It was built for iOS devices with Apple's new programming language, Swift, and it will be ported to the Apple Watch when the API is fully opened to developers.

Contributors

Agent

Created

Date Created
  • 2015-05

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LoRa Weather Station

Description

Communication between the physical and digital world via software, embedded sensors and network connectivity is referred to by the term, the "Internet of Things" (IoT) [1]. The IoT transforms natural

Communication between the physical and digital world via software, embedded sensors and network connectivity is referred to by the term, the "Internet of Things" (IoT) [1]. The IoT transforms natural objects into "smart devices" to improve accuracy, reduce human intervention, and provide real-time data [1]. Smart weather stations that upload information, including temperature and humidity, to the Internet are already available. However, these products are often expensive and programmed only for single-purpose use. The LoRa Weather Station is a low cost, low power and low maintenance IoT solution that combines Microchip Technology's LoRa RN2903 module along with Mikroelektronika's Weather Click sensor. This report discusses how the LoRa Weather Station was created, primarily focusing on the LoRa gateway setup by a Raspberry Pi local web server. This project was completed by four electrical engineering students in the EEE 488 and 489 Senior Design courses at Arizona State University from Fall 2016 to Spring 2017. Total expenses for the project were $717.84, including the LoRa gateway which amounted to $104 (see Appendix C for the Bill of Materials).

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Agent

Created

Date Created
  • 2016-12

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Visualizing Lagrangian Coherent Structures from Realistic Flow Data

Description

The goal of this project was to examine the separatricies that define regions of distinct flow behaviors in realistic time-dependent dynamical systems. In particular, we adapted previously available methods for

The goal of this project was to examine the separatricies that define regions of distinct flow behaviors in realistic time-dependent dynamical systems. In particular, we adapted previously available methods for computing the Finite-Time Lyapunov Exponent (FTLE) to a set of measured wind velocity data in order to visualize the separatricies as ridges of the FTLE field in a section of the atmosphere. This visualization required a number of alterations to the original methods, including interpolation techniques and two different adaptive refinement schemes for producing more detailed results. Overall, there were two computations performed with the wind velocity data: once along a single spherical surface, on which the separatricies could be visualized as material lines, and then along a three-dimensional section of the atmosphere, for which the separatricies were material surfaces. The resulting figures provide an image of the Antarctic polar vortex from the wind velocity data, which is consistent with other data gathered on the same date.

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Created

Date Created
  • 2014-05

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Today the Weather is...: Educational Tools for Weather Map Reading and Weather Forecasting

Description

Meteorology is an uncommon term rarely resonating through elementary classrooms. However, it is a concept found in both fourth and sixth grade Arizona science standards. As issues involving the environment

Meteorology is an uncommon term rarely resonating through elementary classrooms. However, it is a concept found in both fourth and sixth grade Arizona science standards. As issues involving the environment are becoming more pertinent, it is important to study and understand atmospheric processes along with fulfilling the standards for each grade level. This thesis project teaches the practical skills of weather map reading and weather forecasting through the creation and execution of an after school lesson with the aide of seven teen assistants.

Contributors

Agent

Created

Date Created
  • 2012-12

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Lagrangian Skeletons in Hurricane Katrina

Description

This thesis shows analyses of mixing and transport patterns associated with Hurricane Katrina as it hit the United States in August of 2005. Specifically, by applying atmospheric velocity information from

This thesis shows analyses of mixing and transport patterns associated with Hurricane Katrina as it hit the United States in August of 2005. Specifically, by applying atmospheric velocity information from the Weather Research and Forecasting System, finite-time Lyapunov exponents have been computed and the Lagrangian Coherent Structures have been identified. The chaotic dynamics of material transport induced by the hurricane are results from these structures within the flow. Boundaries of the coherent structures are highlighted by the FTLE field. Individual particle transport within the hurricane is affected by the location of these boundaries. In addition to idealized fluid particles, we also studied inertial particles which have finite size and inertia. Basing on established Maxey-Riley equations of the dynamics of particles of finite size, we obtain a reduced equation governing the position process. Using methods derived from computer graphics, we identify maximizers of the FTLE field. Following and applying these ideas, we analyze the dynamics of inertial particle transport within Hurricane Katrina, through comparison of trajectories of dierent sized particles and by pinpointing the location of the Lagrangian Coherent Structures.

Contributors

Agent

Created

Date Created
  • 2012-12

Exoplanet meteorology: characterizing the atmospheres of directly imaged sub-stellar objects

Description

The field of exoplanet science has matured over the past two decades with over 3500 confirmed exoplanets. However, many fundamental questions regarding the composition, and formation mechanism remain unanswered. Atmospheres

The field of exoplanet science has matured over the past two decades with over 3500 confirmed exoplanets. However, many fundamental questions regarding the composition, and formation mechanism remain unanswered. Atmospheres are a window into the properties of a planet, and spectroscopic studies can help resolve many of these questions. For the first part of my dissertation, I participated in two studies of the atmospheres of brown dwarfs to search for weather variations. To understand the evolution of weather on brown dwarfs we conducted a multi-epoch study monitoring four cool brown dwarfs to search for photometric variability. These cool brown dwarfs are predicted to have salt and sulfide clouds condensing in their upper atmosphere and we detected one high amplitude variable. Combining observations for all T5 and later brown dwarfs we note a possible correlation between variability and cloud opacity.

For the second half of my thesis, I focused on characterizing the atmospheres of directly imaged exoplanets. In the first study Hubble Space Telescope data on HR8799, in wavelengths unobservable from the ground, provide constraints on the presence of clouds in the outer planets. Next, I present research done in collaboration with the Gemini Planet Imager Exoplanet Survey (GPIES) team including an exploration of the instrument contrast against environmental parameters, and an examination of the environment of the planet in the HD 106906 system. By analyzing archival HST data and examining the near-infrared colors of HD 106906b, we conclude that the companion shows weak evidence of a circumplanetary dust disk or cloud. Finally, I measure the properties of the low mass directly imaged planet 51 Eridani b. We combined published J, H spectra with updated LP photometry, new K1, K2 spectra, and MS photometry. The new data confirms that the planet has redder than similar spectral type objects, which might be due to the planet still transitioning from to L-to-T. Model atmospheres indicate a cooler effective temperature best fit by a patchy cloud atmosphere making 51 Eri b an excellent candidate for future variability studies with the James Webb Space Telescope.

Contributors

Agent

Created

Date Created
  • 2017

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Weather Habits of the Public

Description

Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month

Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month of measurable precipitation days per year (WRCC). With that, it is important to know the public’s understanding as well as their general trend of likeness towards the weather forecasts they receive. A questionnaire was distributed to 426 people in the state of Arizona to review what they understand from the forecasts and what they would like to see on social media and television.

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Agent

Created

Date Created
  • 2019-05