8,428 research outputs found
Dynamic autonomous intelligent control of an asteroid lander
One of the future flagship missions of the European Space Agency (ESA) is the asteroid sample return mission Marco-Polo. Although there have been a number of past missions to asteroids, a sample has never been successfully returned. The return of asteroid regolith to the Earth's surface introduces new technical challenges. This paper develops attitude control algorithms for the descent phase onto an asteroid in micro-gravity conditions and draws a comparison between the algorithms considered. Two studies are also performed regarding the Fault Detection Isolation and Recovery (FDIR) of the control laws considered. The potential of using Direct Adaptive Control (DAC) as a controller for the surface sampling process is also investigated. Use of a DAC controller incorporates increased levels of robustness by allowing realtime variation of control gains. This leads to better response to uncertainties encountered during missions
Using Variable Dwell Time to Accelerate Gaze-Based Web Browsing with Two-Step Selection
In order to avoid the "Midas Touch" problem, gaze-based interfaces for
selection often introduce a dwell time: a fixed amount of time the user must
fixate upon an object before it is selected. Past interfaces have used a
uniform dwell time across all objects. Here, we propose a gaze-based browser
using a two-step selection policy with variable dwell time. In the first step,
a command, e.g. "back" or "select", is chosen from a menu using a dwell time
that is constant across the different commands. In the second step, if the
"select" command is chosen, the user selects a hyperlink using a dwell time
that varies between different hyperlinks. We assign shorter dwell times to more
likely hyperlinks and longer dwell times to less likely hyperlinks. In order to
infer the likelihood each hyperlink will be selected, we have developed a
probabilistic model of natural gaze behavior while surfing the web. We have
evaluated a number of heuristic and probabilistic methods for varying the dwell
times using both simulation and experiment. Our results demonstrate that
varying dwell time improves the user experience in comparison with fixed dwell
time, resulting in fewer errors and increased speed. While all of the methods
for varying dwell time resulted in improved performance, the probabilistic
models yielded much greater gains than the simple heuristics. The best
performing model reduces error rate by 50% compared to 100ms uniform dwell time
while maintaining a similar response time. It reduces response time by 60%
compared to 300ms uniform dwell time while maintaining a similar error rate.Comment: This is an Accepted Manuscript of an article published by Taylor &
Francis in the International Journal of Human-Computer Interaction on 30
March, 2018, available online:
http://www.tandfonline.com/10.1080/10447318.2018.1452351 . For an eprint of
the final published article, please access:
https://www.tandfonline.com/eprint/T9d4cNwwRUqXPPiZYm8Z/ful
McRunjob: A High Energy Physics Workflow Planner for Grid Production Processing
McRunjob is a powerful grid workflow manager used to manage the generation of
large numbers of production processing jobs in High Energy Physics. In use at
both the DZero and CMS experiments, McRunjob has been used to manage large
Monte Carlo production processing since 1999 and is being extended to uses in
regular production processing for analysis and reconstruction. Described at
CHEP 2001, McRunjob converts core metadata into jobs submittable in a variety
of environments. The powerful core metadata description language includes
methods for converting the metadata into persistent forms, job descriptions,
multi-step workflows, and data provenance information. The language features
allow for structure in the metadata by including full expressions, namespaces,
functional dependencies, site specific parameters in a grid environment, and
ontological definitions. It also has simple control structures for
parallelization of large jobs. McRunjob features a modular design which allows
for easy expansion to new job description languages or new application level
tasks.Comment: CHEP 2003 serial number TUCT00
Is there a Jordan geometry underlying quantum physics?
There have been several propositions for a geometric and essentially
non-linear formulation of quantum mechanics. From a purely mathematical point
of view, the point of view of Jordan algebra theory might give new strength to
such approaches: there is a ``Jordan geometry'' belonging to the Jordan part of
the algebra of observables, in the same way as Lie groups belong to the Lie
part. Both the Lie geometry and the Jordan geometry are well-adapted to
describe certain features of quantum theory. We concentrate here on the
mathematical description of the Jordan geometry and raise some questions
concerning possible relations with foundational issues of quantum theory.Comment: 30 page
Intrinsically Motivated Learning of Visual Motion Perception and Smooth Pursuit
We extend the framework of efficient coding, which has been used to model the
development of sensory processing in isolation, to model the development of the
perception/action cycle. Our extension combines sparse coding and reinforcement
learning so that sensory processing and behavior co-develop to optimize a
shared intrinsic motivational signal: the fidelity of the neural encoding of
the sensory input under resource constraints. Applying this framework to a
model system consisting of an active eye behaving in a time varying
environment, we find that this generic principle leads to the simultaneous
development of both smooth pursuit behavior and model neurons whose properties
are similar to those of primary visual cortical neurons selective for different
directions of visual motion. We suggest that this general principle may form
the basis for a unified and integrated explanation of many perception/action
loops.Comment: 6 pages, 5 figure
Decision-making in the Foster Care System
This study documented and analyzed the processes of mental health treatment decision-making, in the context of family support teams, within the foster care system. The research questions explored engagement, perceptions, and self-rated empowerment among family support teams that serve adolescent foster youth with mental health concerns. The sample consisted of 23 participants from core support teams and 36 other adolescent and adult team members who were involved in the study. Data collection methods included observations at family support team meetings and court hearings, 34 semi-structured individual interviews, a self-rated empowerment scale, and informal conversations in the field. Analysis of non-survey data included qualitative content analyses of meetings and grounded theory methods of analysis for the interviews. Three analytic categories were found in the data: the inter-related processes of decision-making, power, and mesosystem factors that support or hinder decisionmaking. The inter-related processes of decision-making was chosen as a conceptual label to capture the complexity of arriving at decisions. The second category was named power. Power was conceptualized as the ability to influence, or get another person to do something; also the ability to access and use resources. Power was further distinguished by the subcategories: qualities and responses to power. Mesosystem factors in this study were the factors within the Children’s Division and Court System that encourage or impede the youth and family support team’s deliberations. Mesosystem factors as a category was further differentiated into three subcategories: role, transparency, and standardization of practices and procedures. Three family support team exemplars are presented to illustrate these categories. The results of the study pointed to: a) a need to educate stakeholders about how to more fully engage in collaborative decision making and b) a need to provide more opportunities for problem-solving and open dialogue among the youth and their respective teams
Second-order and Fluctuation-induced First-order Phase Transitions with Functional Renormalization Group Equations
We investigate phase transitions in scalar field theories using the
functional renormalization group (RG) equation. We analyze a system with
U(2)xU(2) symmetry, in which there is a parameter that controls the
strength of the first-order phase transition driven by fluctuations. In the
limit of \lambda_2\to0\epsilon$-expansion results. We compare results from the expansion and from
the full numerical calculation and find that the fourth-order expansion is only
of qualitative use and that the sixth-order expansion improves the quantitative
agreement.Comment: 15 pages, 10 figures, major revision; discussions on O(N) models
reduced, a summary section added after Introduction, references added; to
appear in PR
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