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The Social Science and Engineering of Research Practice

Science Magazine

Odumosu, T.B.; Tsao, Jeffrey Y.; Crabtree, G.W.; Narayanamurti, V.

The verdict is in: the methods of science can significantly enhance the effectiveness of creative teams. Just ask employers like Google and Facebook who are applying ideas from the social sciences to improve the performance of their organizations.1 Over the last few decades, social scientists, including psychologists, sociologists and anthropologists, have made important strides in developing a scientific understanding of how creative individuals and creative communities operate.

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The Blue LED Nobel Prize: Historical context, current scientific understanding, human benefit

Annalen der Physik

Tsao, Jeffrey Y.; Han, Jung; Haitz, Roland H.; Pattison, P.M.

The authors, Jeffrey Y. Tsao, Jung Han, Roland H. Haitz, and P. Morgan Pattison, on behalf of a large and growing community of scientists and technologists working in III-N semiconductor materials, physics and devices, and of users of the applications they enable congratulate Professors Akasaki, Amano and Nakamura (AAN). The path that connects scientific understanding with tools and technologies is rarely linear. Prevailing scientific understanding often enables and unleashes new tools and technologies. But prevailing scientific understanding is imperfect, and technology researchers must often step, as did AAN, outside its confines for their breakthroughs. the importance of technology breakthroughs is particularly evident in semiconductors: in recent decades, more and more Physics Nobel Prizes have been awarded for technology breakthroughs, and of these by far the most have been for semiconductors.

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Use Case Realization Report: UCR-03.02 Refines Event

Harris, James M.

This architecturally significant use case describes how the Analyst refines an event hypothesis. The Analyst checks waveform quality (see 'Determines Waveform Data Quality' UC). For waveforms of sufficient quality, the Analyst enhances signals and suppresses noise on waveforms for relevant stations (see 'Enhances Signals' UC), adds and associates missing detections, and modifies or unassociates detections already associated with the event hypothesis (see 'Detects Signals' UC). The Analyst rejects event hypotheses that are invalid. For valid event hypotheses, the Analyst measures signal features associated with the detections (see 'Measures Signal Features' UC) and evaluates the moment tensor ('Evaluates Moment Tensor' UC). The Analyst uses these signal features to refine the location (see 'Refines Event Location' UC) and magnitude (see 'Refines Event Magnitude' UC) of the event hypothesis. The Analyst compares events to determine how similar events were constructed (see 'Compares Events' UC). The Analyst repeats these steps until satisfied with the results. Analysts may provide feedback for previous Analysts during any of these steps (see 'Provides Analyst Feedback' UC). This use case is architecturally significant because it captures the interplay between all of the Analyst activities.

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Use Case Realization Report: UCR-08.05 Views Event History

Harris, James M.

This architecturally significant use case describes how the System User observes the change history of a given event. The change history is a series of one or more saved event hypotheses. System Users view all the event hypotheses and the set of location solutions for each hypothesis. The System User views the relationship between event hypotheses including the preferred hypothesis for each processing stage. The event change history persists across work sessions for subsequent review. This use case is architecturally significant because it covers review of stored versions of event hypotheses

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Use Case Realization Report: UCR-03.02.08 Compares Events

Harris, James M.

This architecturally significant use case describes how the Analyst compares events to determine how similar events were constructed. The Analyst compares waveforms from comparison events by visually inspecting an overlay of the waveforms to determine if the events are from a similar source. The Analyst searches for comparison events or creates agglomerative hierarchical clusters of waveforms from events and determines that the events are from a similar source if the correlation coefficient is above a selected threshold. This use case is architecturally significant due to the introduction of the capability to compare events within an operational context.

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Use Case Realization Report: UCR-02.08 System Refines Event Location

Harris, James M.

This architecturally significant use case describes how the System refines event hypothesis location solutions. The System locates events by finding the event location minimizing the difference between signal detection feature measurements and signal detection feature predictions (see 'System Measures Signal Features' UC). The System references both empirical knowledge from past events and geophysical models to form the signal detection feature predictions. The System also computes an uncertainty bound for each event hypothesis location solution describing a region bounding the event hypothesis' hypocenter and origin time at a particular confidence level. The System creates a variety of location solutions for each event hypothesis. These location solutions vary from one another in either the input parameters the System uses or in the location solution components the System restrains to fixed values (e.g. depth) during event location calculations. The System computes location solutions using input parameters configured by the System Maintainer (see ‘Configures Processing Components’ UC). The Analyst has the option to override input parameters originally configured by the System Maintainer (see 'Refines Event Location' UC). This use case is architecturally significant due to the processing and memory resource consumption of 3D earth model calculations.

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Microfabrication Capabilities & Device Architectures

Bauer, Todd M.; Jones, Adam; Lentine, Anthony; Mudrick, John; Okandan, Murat; Rodrigues, Arun

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Experimental Progress in Magnetized Liner Inertial Fusion (MagLIF)

Gomez, Matthew R.; Slutz, Stephen A.; Sefkow, Adam B.; Geissel, Matthias; Harvey-Thompson, Adam J.; Peterson, K.J.; Hansen, Stephanie B.; Hahn, Kelly; Knapp, P.F.; Schmit, Paul; Ruiz, Carlos L.; Sinars, Daniel; Awe, Thomas J.; Harding, Eric H.; Jennings, Christopher A.; Smith, Ian C.; Rovang, Dean C.; Chandler, Gordon A.; Cuneo, Michael E.; Lamppa, Derek C.; Martin, Matthew R.; Mcbride, Ryan; Porter, John L.; Rochau, G.A.

Abstract not provided.

Recent progress in Magnetized Liner Inertial Fusion (MagLIF) experiments

Gomez, Matthew R.; Slutz, Stephen A.; Sefkow, Adam B.; Geissel, Matthias; Harvey-Thompson, Adam J.; Peterson, K.J.; Awe, Thomas J.; Hansen, Stephanie B.; Harding, Eric H.; Hahn, Kelly; Knapp, P.F.; Schmit, Paul; Ruiz, Carlos L.; Sinars, Daniel; Jennings, Christopher A.; Smith, Ian C.; Rovang, Dean C.; Chandler, Gordon A.; Martin, Matthew R.; Mcbride, Ryan; Porter, John L.; Rochau, G.A.

Abstract not provided.

Magnetized Liner Inertial Fusion on the Z Pulsed-Power Accelerator

Mcbride, Ryan; Sinars, Daniel; Slutz, Stephen A.; Gomez, Matthew R.; Sefkow, Adam B.; Hansen, Stephanie B.; Awe, Thomas J.; Peterson, K.J.; Knapp, P.F.; Schmit, Paul; Rovang, Dean C.; Geissel, Matthias; Vesey, Roger A.; Harvey-Thompson, Adam J.; Jennings, Christopher A.; Martin, Matthew R.; Lemke, Raymond W.; Hahn, Kelly; Harding, Eric H.; Cuneo, Michael E.; Porter, John L.; Rochau, G.A.; Stygar, William A.

Abstract not provided.

Results 47701–47800 of 99,299
Results 47701–47800 of 99,299