scholarly journals Validation of a priori CME arrival predictions made using real‐time heliospheric imager observations

Space Weather ◽  
2015 ◽  
Vol 13 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Kimberley Tucker‐Hood ◽  
Chris Scott ◽  
Mathew Owens ◽  
David Jackson ◽  
Luke Barnard ◽  
...  
Keyword(s):  
Real Time ◽  
A Priori ◽  
Heliospheric Imager

scholarly journals Monitoring distributed computing beyond the traditional time-series histogram

2020 ◽  
Vol 245 ◽  
pp. 03036
Author(s):  
M S Doidge ◽  
P. A. Love ◽  
J Thornton
Keyword(s):  
Time Series ◽  
Distributed Computing ◽  
Real Time ◽  
A Priori ◽  
Time Data ◽  
Use Of Time ◽  
Computing Services ◽  
Monitoring Tools ◽  
Novel Approach ◽  
Current Monitoring

In this work we describe a novel approach to monitor the operation of distributed computing services. Current monitoring tools are dominated by the use of time-series histograms showing the evolution of various metrics. These can quickly overwhelm or confuse the viewer due to the large number of similar looking graphs. We propose a supplementary approach through the sonification of real-time data streamed directly from a variety of distributed computing services. The real-time nature of this method allows operations staff to quickly detect problems and identify that a problem is still ongoing, avoiding the case of investigating an issue a-priori when it may already have been resolved. In this paper we present details of the system architecture and provide a recipe for deployment suitable for both site and experiment teams.

MISSION-ADAPTABLE ROUTE PLANNING IN UNCERTAIN AND ADVERSARIAL ENVIRONMENT

2006 ◽  
Vol 15 (05) ◽  
pp. 803-821 ◽  
Author(s):  
PING YAN ◽  
MINGYUE DING ◽  
CHANGWEN ZHENG
Keyword(s):  
Real Time ◽  
A Priori ◽  
Route Planning ◽  
Optimal Solution ◽  
Dijkstra Algorithm ◽  
Solution Quality ◽  
Model Complex ◽  
Local Methods ◽  
Domain Specific Knowledge ◽  
Planning Algorithm

In this paper, the route-planning problems of Unmanned Aerial Vehicle (UAV) in uncertain and adversarial environment are addressed, including not only single-mission route planning in known a priori environment, but also the route replanning in partially known and mission-changeable environments. A mission-adaptable hybrid route-planning algorithm based on flight roadmap is proposed, which combines existing global and local methods (Dijkstra algorithm, SAS and D*) into a two-level framework. The environment information and constraints for UAV are integrated into the procedure of building flight roadmap and searching for routes. The route-planning algorithm utilizes domain-specific knowledge and operates in real time with near-optimal solution quality, which is important to uncertain and adversarial environment. Other planners do not provide all of the functionality, namely real-time planning and replanning, near-optimal solution quality, and the ability to model complex 3D constraints.

Implementation of a new real time seismicity detector for the Mayotte crisis

2021 ◽  
Author(s):  
Jean-Marie Saurel ◽  
Lise Retailleau ◽  
Weiqiang Zhu ◽  
Simon Issartel ◽  
Claudio Satriano ◽  
...  
Keyword(s):  
Real Time ◽  
Volcanic Activity ◽  
A Priori ◽  
Processing System ◽  
Activity Level ◽  
Phase Identification ◽  
Real Time Processing ◽  
S Waves ◽  
Hypocentral Location ◽  
New Processing

<p>Seismology is one of the main techniques used to monitor volcanic activity worldwide. Seismicity analysis through several seismic sensor deployments has been used to monitor Mayotte volcano crisis since its beginning in May 2018. Because volcanic activity can evolve rapidly, efficient and accurate seismicity detectors are crucial to assess in real-time the activity level of the volcano and, if needed, to issue timely warnings.</p><p> </p><p><span>Traditional real-time seismic processing software, such as EarthWorm or SeisComP, use phase onset pickers followed by a phase association algorithm to declare an event and proceed with its location. Real-time phase pickers usually cannot identify whether the detected phase is a P or S arrival and this decision or assumption is made by the associator. The lack of S arrival has an obvious impact on the hypocentral location quality. S-phases can also help detection on small earthquakes where weak P-phases can be missed.</span></p><p> </p><p><span>We implemented the deep neural network-based method PhaseNet to identify in real-time seismic P and S waves on 3-component seismometers deployed on Mayotte island. We also built an interface to subsequently process PhaseNet results and send pick objects to EarthWorm. We use EarthWorm binder_ew associator module specifically tuned for PhaseNet </span><span><em>a priori</em></span><span> phase identification to detect and locate the events, which are finally archived in a SeisComP database. We implemented this innovative real-time processing system for the REVOSIMA (Reseau de surveillance Volcanologique et Sismologique de Mayotte) hosted at OVPF (Observatoire Volcanologique du Piton de la Fournaise). We assess the robustness of the algorithm by comparing the results to existing automatic and manually detected seismicity catalogs.</span></p><p> </p><p>We show that the existing SeisComP automatic system is outperformed by our new algorithm, both in number of earthquake detections and location reliability. Our implementation also detects more events than the daily manual data screening. While this promising new processing system was first applied to study the Mayotte seismicity, it can be used in any seismic active zone, of volcanic or tectonic origin. Indeed, it will be installed at Martinique volcanic and seismic observatory later this year.</p>

scholarly journals Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems

Micromachines ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 386
Author(s):  
Olatunji Mumini Omisore ◽  
Shipeng Han ◽  
Yousef Al-Handarish ◽  
Wenjing Du ◽  
Wenke Duan ◽  
...  
Keyword(s):  
Real Time ◽  
A Priori ◽  
Tumor Resection ◽  
Computational Effort ◽  
Robotic Systems ◽  
Kinematics And Dynamics ◽  
Target Point ◽  
Real Time Control ◽  
Control Models ◽  
Constraints Model

Success of the da Vinci surgical robot in the last decade has motivated the development of flexible access robots to assist clinical experts during single-port interventions of core intrabody organs. Prototypes of flexible robots have been proposed to enhance surgical tasks, such as suturing, tumor resection, and radiosurgery in human abdominal areas; nonetheless, precise constraint control models are still needed for flexible pathway navigation. In this paper, the design of a flexible snake-like robot is presented, along with the constraints model that was proposed for kinematics and dynamics control, motion trajectory planning, and obstacle avoidance during motion. Simulation of the robot and implementation of the proposed control models were done in Matlab. Several points on different circular paths were used for evaluation, and the results obtained show the model had a mean kinematic error of 0.37 ± 0.36 mm with very fast kinematics and dynamics resolution times. Furthermore, the robot’s movement was geometrically and parametrically continuous for three different trajectory cases on a circular pathway. In addition, procedures for dynamic constraint and obstacle collision detection were also proposed and validated. In the latter, a collision-avoidance scheme was kept optimal by keeping a safe distance between the robot’s links and obstacles in the workspace. Analyses of the results showed the control system was optimal in determining the necessary joint angles to reach a given target point, and motion profiles with a smooth trajectory was guaranteed, while collision with obstacles were detected a priori and avoided in close to real-time. Furthermore, the complexity and computational effort of the algorithmic models were negligibly small. Thus, the model can be used to enhance the real-time control of flexible robotic systems.

scholarly journals Determining Solution Space Characteristics for Real-Time Strategy Games and Characterizing Winning Strategies

2011 ◽  
Vol 2011 ◽  
pp. 1-17
Author(s):  
Kurt Weissgerber ◽  
Gary B. Lamont ◽  
Brett J. Borghetti ◽  
Gilbert L. Peterson
Keyword(s):  
Real Time ◽  
A Priori ◽  
Solution Space ◽  
Complex Problem ◽  
Classification Model ◽  
Landscape Characteristics ◽  
Specific Complex ◽  
Winning Strategies ◽  
Strategic Agents ◽  
Rts Game

The underlying goal of a competing agent in a discrete real-time strategy (RTS) game is to defeat an adversary. Strategic agents or participants must define an a priori plan to maneuver their resources in order to destroy the adversary and the adversary's resources as well as secure physical regions of the environment. This a priori plan can be generated by leveraging collected historical knowledge about the environment. This knowledge is then employed in the generation of a classification model for real-time decision-making in the RTS domain. The best way to generate a classification model for a complex problem domain depends on the characteristics of the solution space. An experimental method to determine solution space (search landscape) characteristics is through analysis of historical algorithm performance for solving the specific problem. We select a deterministic search technique and a stochastic search method for a priori classification model generation. These approaches are designed, implemented, and tested for a specific complex RTS game, Bos Wars. Their performance allows us to draw various conclusions about applying a competing agent in complex search landscapes associated with RTS games.

scholarly journals Real-time detection and resolution of atom bumping in crystallographic models

2017 ◽  
Vol 73 (5) ◽  
pp. 414-422 ◽  
Author(s):  
Yu Liu
Keyword(s):  
Crystal Structure ◽  
Real Time ◽  
Structure Determination ◽  
A Priori ◽  
Unit Cell ◽  
Evaluation Function ◽  
Coordination Numbers ◽  
Fundamental Significance ◽  
Bounding Boxes ◽  
Space Method

A basic principle in crystal structure determination is that there should be proper distances between adjacent atoms. Therefore, detection of atom bumping is of fundamental significance in structure determination, especially in the direct-space method where crystallographic models are just randomly generated. Presented in this article is an algorithm that detects atom bonding in a unit cell based on the sweep and prune algorithm of axis-aligned bounding boxes and running in theO(n log n) time bound, wherenis the total number of atoms in the unit cell. This algorithm only needs the positions of individual atoms in the unit cell and does not require any prior knowledge of existing bonds, and is thus suitable for modelling of inorganic crystals where the bonding relations are often unknowna priori. With this algorithm, computation routines requiring bonding information,e.g.anti-bumping and computation of coordination numbers and valences, can be performed efficiently. As an example application, an evaluation function for atom bumping is proposed, which can be used for real-time elimination of crystallographic models with unreasonably short bonds during the procedure of global optimization in the direct-space method.

Impact of Travel Time Models on Quality of Real-Time Routing Instructions

2003 ◽  
Vol 1857 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Elise Miller-Hooks ◽  
Baiyu Yang
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Communication Systems ◽  
Service Providers ◽  
A Priori ◽  
Information Service ◽  
Small Neighborhood ◽  
Transportation Systems ◽  
Travel Times ◽  
Real Time Information

Mobile communication systems coupled with intelligent transportation systems technologies can permit information service providers to supply real-time routing instructions to suitably equipped vehicles as real-time travel times are received. Simply considering current conditions in updating routing decisions, however, may lead to suboptimal path choices, because future travel conditions likely will differ from that currently observed. Even with perfect and continuously updated information about current conditions, future travel times can be known a priori with uncertainty at best. Further, in congested transportation systems, conditions vary over time as recurrent congestion may change with a foreseeable pattern during peak driving hours. It is postulated that better, more robust routing instructions can be provided by explicitly accounting for this inherent stochastic and dynamic nature of future travel conditions in generating the routing instructions. It is further hypothesized that nearly equally good routing instructions can be provided by collecting real-time information from only a small neighborhood within the transportation system as from the entire system. Extensive numerical experiments were conducted to assess the validity of these two hypotheses.

scholarly journals Effects of Emotional Stimulations on the Online Operation of a P300-Based Brain–Computer Interface

2021 ◽  
Vol 15 ◽  
Author(s):  
Minju Kim ◽  
Jongsu Kim ◽  
Dojin Heo ◽  
Yunjoo Choi ◽  
Taejun Lee ◽  
...  
Keyword(s):  
Real Time ◽  
A Priori ◽  
Event Related Potentials ◽  
Auditory Stimuli ◽  
Emotional States ◽  
Emotional Stimuli ◽  
Alpha Asymmetry ◽  
Significant Difference ◽  
Related Potentials ◽  
Electric Light

Using P300-based brain–computer interfaces (BCIs) in daily life should take into account the user’s emotional state because various emotional conditions are likely to influence event-related potentials (ERPs) and consequently the performance of P300-based BCIs. This study aimed at investigating whether external emotional stimuli affect the performance of a P300-based BCI, particularly built for controlling home appliances. We presented a set of emotional auditory stimuli to subjects, which had been selected for each subject based on individual valence scores evaluated a priori, while they were controlling an electric light device using a P300-based BCI. There were four conditions regarding the auditory stimuli, including high valence, low valence, noise, and no sound. As a result, subjects controlled the electric light device using the BCI in real time with a mean accuracy of 88.14%. The overall accuracy and P300 features over most EEG channels did not show a significant difference between the four auditory conditions (p > 0.05). When we measured emotional states using frontal alpha asymmetry (FAA) and compared FAA across the auditory conditions, we also found no significant difference (p > 0.05). Our results suggest that there is no clear evidence to support a hypothesis that external emotional stimuli influence the P300-based BCI performance or the P300 features while people are controlling devices using the BCI in real time. This study may provide useful information for those who are concerned with the implementation of a P300-based BCI in practice.

scholarly journals REINFORCEMENT LEARNING HELPS SLAM: LEARNING TO BUILD MAPS

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 329-335
Author(s):  
N. Botteghi ◽  
B. Sirmacek ◽  
R. Schulte ◽  
M. Poel ◽  
C. Brune
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
A Priori ◽  
Simultaneous Localization And Mapping ◽  
Indoor Environments ◽  
Robot Localization ◽  
Robust Solution ◽  
Localization And Mapping ◽  
Reward Functions ◽  
Slam Algorithm

Abstract. In this research, we investigate the use of Reinforcement Learning (RL) for an effective and robust solution for exploring unknown and indoor environments and reconstructing their maps. We benefit from a Simultaneous Localization and Mapping (SLAM) algorithm for real-time robot localization and mapping. Three different reward functions are compared and tested in different environments with growing complexity. The performances of the three different RL-based path planners are assessed not only on the training environments, but also on an a priori unseen environment to test the generalization properties of the policies. The results indicate that RL-based planners trained to maximize the coverage of the map are able to consistently explore and construct the maps of different indoor environments.

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