gallimgg/Topic_Modeling_Assistant
Topic Modeling Assistant for large literature databases in Scopus system with zettelkasten note exporting tool for use in Obsidian
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Topic Modeling Assistant for large literature databases in Scopus system with zettelkasten note exporting tool for use in Obsidian
Data on galactic X-ray sources from rocket and balloon experiments and the UHURU satellite are reported. The outline emphasizes general discrete source models and begins with some a priori considerations about X-ray emission mechanisms and their applicability, after which contemporary data are interpreted according to these models. Topics covered include the production of X-rays by various mechanisms, source regimes, observational parameters, stellar distributions, individual stars, flare stars, supernovae and pulsars, the Crab nebula, old and young remnants, binary systems, and others.
The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.
Conference report contains compilation of papers relating to interactions between humans and machines from perspectives of telepresence and sensorimotor adaptation, measurement and evaluation of performance, and design principles and predictive models. Topics discussed include neural networks, sensory technology, display, and feedback controls. Covers state of art of remote sensing and control by humans for space or other operations.
As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.
During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.
The NASA Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) have been planned and funded by the NASA Earth Science Division. Both programs have a focus on engaging stakeholders and developing science useful for decision making. The resulting programs have funded significant scientific output and advancements in understanding how satellite remote sensing observations can be used to not just study how the Earth is changing, but also create data products that are of high utility to stakeholders and decisions makers. In this paper we focus on documenting thematic diversity of research themes and methods used, and how the CMS and ABoVE themes are related. We do this through developing a Correlated Topic Model on the 521 papers produced by the two programs and plotting the results in a network diagram. Through analysis of the themes in these papers, we document the relationships between researchers and institutions participating in CMS and ABoVE programs and the benefits from sustained engagement with stakeholders due to recurring funding. We note an absence of policy engagement in the papers and conclude that funded researchers need to be more ambitious and explicit in drawing the connection between their research and carbon policy implications in order to meet the stated goals of the CMS and ABoVE programs.
Presentation topics include: standards in a changing business model, the new National Space Policy is driving change, a new paradigm for human spaceflight, consistency across standards, the purpose of standards, danger of over-prescriptive standards, a balance is needed (between prescriptive and general standards), enabling versus inhibiting, characteristics of success-oriented standards, characteristics of success-oriented standards, and conclusions. Additional slides include NASA Procedural Requirements 8705.2B identifies human rating standards and requirements, draft health and medical standards for human rating, what's been done, government oversight models, examples of consistency from anthropometry, examples of inconsistency from air quality and appendices of government and non-governmental human factors standards.
We all have questions. About today's temperature, scores of our favorite baseball team, the Universe, and about vaccine for COVID-19. Life, physical, and natural scientists have been trying to find answers to various topics using scientific methods and experiments, while computer scientists have built language models as a tiny step towards automatically answering all of these questions across domains given a little bit of context. In this paper, we propose an architecture using state-of-the-art Natural Language Processing language models namely Topic Models and Bidirectional Encoder Representations from Transformers (BERT) that can transparently and automatically retrieve articles of relevance to questions across domains, and fetch answers to topical questions related to COVID-19 current and historical medical research literature. We demonstrate the benefits of using domain-specific supercomputers like Tensor Processing Units (TPUs), residing on cloud-based infrastructure, using which we could achieve significant gains in training and inference times, also with very minimal cost.
The topics covered include the following: (1) CO2 laser kinetics modeling; (2) gas lifetimes in pulsed CO2 lasers; (3) frequency chirp and laser pulse spectral analysis; (4) LAWS A' Design Study; and (5) discharge circuit components for LAWS. The appendices include LAWS Memos, computer modeling of pulsed CO2 lasers for lidar applications, discharge circuit considerations for pulsed CO2 lidars, and presentation made at the Code RC Review.
Agent-based socio-technical modeling of medium- and heavy-duty (MDHD) electric vehicle (EV) adoption has the potential to provide analysis, prediction, and gui. This paper describes new applications of text analysis developed through machine learning (ML) to build and understand relevant topics and their saliency in the published discourse on adoption of MDHD EVs. This work contributes to the state of the art in topic mining models by defining a new metric of topic ranking (START) that quantifies the importance of predefined topics within the corpus using weighted results for predefined topics from two topic modeling approaches: Latent Dirichlet Allocation (LDA) and BERTopic. The START metric is then demonstrated in practice to model how academia and industry view the EV adoption process based on the respective texts published by these groups. Results show that academic literature places more emphasis on categories of interests such as norms/attitudes and adopter knowledge, while trade journals tend to emphasize long-term cost more than academia. The two bodies of literature agree on the importance of policy and incentives in MDHD EV adoption. Together these results illustrate the potential to use ML-based text analysis to populate the characteristics of agent-based socio-technical models.
Two topics in topology, the comparison of plane curves and faces on geometric models, are discussed. With regard to the first problem, a curve is defined to be a locus of points without any underlying parameterization. A metric on a class of plane curves is defined, a finite computation of this metric is given for the case of piecewise linear curves, and it is shown how to approximate curves that have bounded curvature by piecewise linear curves. In this way a bound on the distance between two curves can be computed. With regard to the second problem, the questions to be discussed are under what circumstances do geometrical faces make sense; how can they be explicity defined; and when are these geometrical faces homeomorphic to the realization of the abstract (topological) face.
The topics for the three lectures for the Canadian Summer School are Lagrangian Models, numerical transport schemes, and chemical and transport models. In the first lecture I will explain the basic components of the Lagrangian model (a trajectory code and a photochemical code), the difficulties in using such a model (initialization) and show some applications in interpretation of aircraft and satellite data. If time permits I will show some results concerning inverse modeling which is being used to evaluate sources of tropospheric pollutants. In the second lecture I will discuss one of the core components of any grid point model, the numerical transport scheme. I will explain the basics of shock capturing schemes, and performance criteria. I will include an example of the importance of horizontal resolution to polar processes. We have learned from NASA's global modeling initiative that horizontal resolution matters for predictions of the future evolution of the ozone hole. The numerical scheme will be evaluated using performance metrics based on satellite observations of long-lived tracers. The final lecture will discuss the evolution of chemical transport models over the last decade. Some of the problems with assimilated winds will be demonstrated, using satellite data to evaluate the simulations.
The topics discussed include the following: verification of cloud prediction from the PSU/NCAR mesoscale model; results form MAPS/NGM verification comparisons and MAPS observation sensitivity tests to ACARS and profiler data; systematic errors and mesoscale verification for a mesoscale model; and the COMPARE Project and the CME.
The topics are presented in viewgraph form and include the following: nuclear thermal propulsion (NTP) & detailed nuclear engine modeling; modeling and engineering simulation of nuclear thermal rocket systems; nuclear thermal rocket simulation system; INSPI-NTVR core axial flow profiles; INSPI-NTRV core axial flow profiles; specific impulse vs. chamber pressure; turbine pressure ratio vs. chamber pressure; NERVA core axial flow profiles; P&W XNR2000 core axial flow profiles; pump pressure rise vs. chamber pressure; streamline of jet-induced flow in cylindrical chamber; flow pattern of a jet-induced flow in a chamber; and radiative heat transfer models.
The topics discussed include the following: perspectives on planetary boundary layer (PBL) measurements; current problems of PBL parameterization in mesoscale models; and convective cloud-PBL interactions.
The topics are presented in viewgraph form and include the following: particle bed reactor (PBR) core cross section; PBR bleed cycle; fuel and moderator flow paths; PBR modeling requirements; characteristics of PBR and nuclear thermal propulsion (NTP) modeling; challenges for PBR and NTP modeling; thermal hydraulic computer codes; capabilities for PBR/reactor application; thermal/hydralic codes; limitations; physical correlations; comparison of predicted friction factor and experimental data; frit pressure drop testing; cold frit mask factor; decay heat flow rate; startup transient simulation; and philosophy of systems modeling.
The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.