Long range science scheduling for the Hubble Space Telescope

Observations with NASA's Hubble Space Telescope (HST) are scheduled with the assistance of a long-range scheduling system (SPIKE) that was developed using artificial intelligence techniques. In earlier papers, the system architecture and the constraint representation and propagation mechanisms were described. The development of high-level automated scheduling tools, including tools based on constraint satisfaction techniques and neural networks is described. The performance of these tools in scheduling HST observations is discussed

Artificial intelligence approaches to astronomical observation scheduling

Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope

Geology and Ore Deposits of the Golden Era and Goldfinch Mines, Argenta Mining District, Montana.

This report includes the results of geological investigation of a small area in the northern part of the Argenta mining district. Approximately two square miles were mapped. The underground working of the three mines only were accessible: the Goldfinch. Golden Era, and Mayday mines

Convectively driven shear and decreased heat flux

We report on direct numerical simulations of two-dimensional, horizontally periodic Rayleigh-B\'enard convection, focusing on its ability to drive large-scale horizontal flow that is vertically sheared. For the Prandtl numbers ($Pr$) between 1 and 10 simulated here, this large-scale shear can be induced by raising the Rayleigh number ($Ra$) sufficiently, and we explore the resulting convection for $Ra$ up to $10^{10}$. When present in our simulations, the sheared mean flow accounts for a large fraction of the total kinetic energy, and this fraction tends towards unity as $Ra\to\infty$. The shear helps disperse convective structures, and it reduces vertical heat flux; in parameter regimes where one state with large-scale shear and one without are both stable, the Nusselt number of the state with shear is smaller and grows more slowly with $Ra$. When the large-scale shear is present with $Pr\lesssim2$, the convection undergoes strong global oscillations on long timescales, and heat transport occurs in bursts. Nusselt numbers, time-averaged over these bursts, vary non-monotonically with $Ra$ for $Pr=1$. When the shear is present with $Pr\gtrsim3$, the flow does not burst, and convective heat transport is sustained at all times. Nusselt numbers then grow roughly as powers of $Ra$, but the growth rates are slower than any previously reported for Rayleigh-B\'enard convection without large-scale shear. We find the Nusselt numbers grow proportionally to $Ra^{0.077}$ when $Pr=3$ and to $Ra^{0.19}$ when $Pr=10$. Analogies with tokamak plasmas are described.Comment: 25 pages, 12 figures, 5 video

Expert systems tools for Hubble Space Telescope observation scheduling

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation

Spike: Artificial intelligence scheduling for Hubble space telescope

Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains

Teenager's doing history out-of-school: An intrinsic case study of situated learning in history.

This intrinsic case study documents a community-based history expedition implemented as a project-based, voluntary, out-of-school history activity. The expedition's development was informed by the National Education Association's concept of the intensive study of history, its structure by the history seminary, and its spirit by Webb's account of seminar as history expedition. Specific study objectives included documentation of the planning, implementation, operation, and outcomes of the expedition, as well as the viability of the history expedition as a vehicle for engaging teenagers in the practice of history. Finally, the study examined whether a history expedition might serve as a curriculum of identity. Constructivist philosophy and situated learning theory grounded the analysis and interpretation of the study. Undertaken in North Central Texas, the study followed the experiences of six teenagers engaged as historians who were given one year to research and write a historical monograph. The monograph concerned the last horse cavalry regiment deployed overseas as a mounted combat unit by the U.S. Army during World War II. The study yielded qualitative data in the form of researcher observations, participant interviews, artifacts of participant writing, and participant speeches. In addition, the study includes evaluations of the historical monograph by subject matter experts. The data indicate that participants and audience describe the history expedition as a highly motivational experience which empowered participants to think critically, write historically, and create an original product valuable to the regiment's veterans, the veterans' families, the State of Texas, and military historians. The study supports the contention of the National Education Association that the intensive study of history can be beneficial both to expedition participants and to their community. The assertion that engaging teenagers as researchers within a discipline serves as a curriculum of identity was supported in the study as well. The study underscored the importance of oral history as a gateway for learning about modern history

Development of an expert data reduction assistant

We propose the development of an expert system tool for the management and reduction of complex data sets. The proposed work is an extension of a successful prototype system for the calibration of CCD images developed by Dr. Johnston in 1987. The reduction of complex multi-parameter data sets presents severe challenges to a scientist. Not only must a particular data analysis system be mastered, (e.g. IRAF/SDAS/MIDAS), large amounts of data can require many days of tedious work and supervision by the scientist for even the most straightforward reductions. The proposed Expert Data Reduction Assistant will help the scientist overcome these obstacles by developing a reduction plan based on the data at hand and producing a script for the reduction of the data in a target common language

Developmental Validation of Short Tandem Repeat Reagent Kit for Forensic DNA Profiling of Canine Biological Material

Aim To develop a reagent kit that enables multiplex polymerase chain reaction (PCR) amplification of 18 short tandem repeats (STR) and the canine sex-determining Zinc Finger marker. Methods Validation studies to determine the robustness and reliability in forensic DNA typing of this multiplex assay included sensitivity testing, reproducibility studies, intra- and inter-locus color balance studies, annealing temperature and cycle number studies, peak height ratio determination, characterization of artifacts such as stutter percentages and dye blobs, mixture analyses, species- specificity, case type samples analyses and population studies. Results The kit robustly amplified domesticated dog samples and consistently generated full 19-locus profiles from as little as 125 pg of dog DNA. In addition, wolf DNA samples could be analyzed with the kit. Conclusion The kit, which produces robust, reliable, and reproducible results, will be made available for the forensic research community after modifications based on this study’s evaluation to comply with the quality standards expected for forensic casework

Developmental Validation of Short Tandem Repeat Reagent Kit for Forensic DNA Profiling of Canine Biological Material

Aim To develop a reagent kit that enables multiplex polymerase chain reaction (PCR) amplification of 18 short tandem repeats (STR) and the canine sex-determining Zinc Finger marker. Methods Validation studies to determine the robustness and reliability in forensic DNA typing of this multiplex assay included sensitivity testing, reproducibility studies, intra- and inter-locus color balance studies, annealing temperature and cycle number studies, peak height ratio determination, characterization of artifacts such as stutter percentages and dye blobs, mixture analyses, species- specificity, case type samples analyses and population studies. Results The kit robustly amplified domesticated dog samples and consistently generated full 19-locus profiles from as little as 125 pg of dog DNA. In addition, wolf DNA samples could be analyzed with the kit. Conclusion The kit, which produces robust, reliable, and reproducible results, will be made available for the forensic research community after modifications based on this study’s evaluation to comply with the quality standards expected for forensic casework