GRACE-FO accelerometer data recovery within ITSG-Grace2018 data processing

2020 ◽  
Author(s):  
Saniya Behzadpour ◽  
Torsten Mayer-Gürr ◽  
Andreas Kvas ◽  
Sandro Krauss ◽  
Sebastian Strasser ◽  
...  
Keyword(s):  
Gravitational Force ◽  
State Of The Art ◽  
Data Recovery ◽  
Force Model ◽  
Accelerometer Data ◽  
New Approach ◽  
Gravitational Forces ◽  
Gravity Field Recovery ◽  
Novel Approach ◽  
Gravity Recovery

<p>In GRACE-FO (Gravity Recovery and Climate Experiment Follow-on) mission, similar to its predecessor GRACE, the twin satellites are equipped with three-axis accelerometers, measuring the non-gravitational forces. After one month in orbit, the GRACE-D accelerometer data degraded and its measurements were replaced by synthetic accelerometer data, the so-called transplant data, officially generated by the Jet Propulsion Laboratory (JPL). The transplant data was derived from the GRACE-C accelerometer measurements, by applying a time and attitude corrections and adding model-based residual accelerations due to thruster firings on GRACE-D.</p><p>For the ITSG-Grace2018 GRACE-FO release, the gravity field recovery is based on the use of in-house Level-1B accelerometer data (ACT1B) using the provided Level-1A data products. In this work, we present a novel approach to recover the ACT1B data by (a) implementing the state-of-the-art non-gravitational force models and (b) applying additional force model corrections.</p><p>The preliminary results show the improved ACT1B data not only contributed to a noise reduction but also improved the estimates of the C20 and C30 coefficients. We show that the offset between SLR (Satellite Laser Ranging) and GRACE-FO derived C20 and C30 time series can be reduced remarkably by the use of the new accelerometer product, demonstrating the merit of this new approach.</p>

scholarly journals Controlling Liquid Slosh by Applying Optimal Operating-Speed-Dependent Motion Profiles

Robotics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 18 ◽  
Author(s):  
Clemens Troll ◽  
Sven Tietze ◽  
Jens-Peter Majschak
Keyword(s):  
Process Model ◽  
State Of The Art ◽  
Operating Speed ◽  
Residual Vibration ◽  
Optimal Motion ◽  
New Approach ◽  
Liquid Slosh ◽  
Novel Approach ◽  
Characteristic Map ◽  
Continuous Range

In this paper, an investigation is presented that demonstrates the application of a new approach for enabling the reduction of liquid slosh by implementing optimized motion profiles over a continuous range of operating speeds. Liquid slosh occurs in the packaging process of beverages. Starting by creating a dynamic process model, optimal control theory is applied for calculating optimal motion profiles that minimize residual vibration. Subsequently, the difficulty of operating speed dependency of the herewith synthesized motion profiles is examined. An approach in which the optimal motion profiles are consolidated into a characteristic map of motion specifications, which can be executed by a programmable logic controller in real time, is discussed. Eventually, the success of this novel approach is demonstrated by the comparison with state-of-the-art motion profiles and conventional motion implementation.

scholarly journals Integrated sensor analysis for GRACE – development and validation

2003 ◽  
Vol 1 ◽  
pp. 57-63 ◽  
Author(s):  
B. Frommknecht ◽  
H. Oberndorfer ◽  
F. Flechtner ◽  
R. Schmidt
Keyword(s):  
Closed Loop ◽  
Feedback System ◽  
Test Mass ◽  
Practical Implementation ◽  
Accelerometer Data ◽  
Integrated Sensor ◽  
Gravitational Forces ◽  
Sensor Analysis ◽  
Development And Validation ◽  
Gravity Recovery

Abstract. The focus of this article is on the accelerometer on board the two GRACE (Gravity Recovery and Climate Experiment) satellites. In a first analysis the accelerometer system is studied. The behavior of the test mass and its capacitive feedback system is simulated in the time and the frequency domain for one degree of freedom. Only linear accelerations are considered so far. The second part of the analysis is about the practical implementation of the simulation model: Non-gravitational forces were derived from the GFZ (GeoForschungsZentrum) EPOS (Earth Parameter and Orbit System) software. In a closed loop the accelerometer measurements derived from these data in connection with simulated tracking data have been used for orbit recovery including the estimation of biases and scale factors for the accelerometer data. Details and results of this procedure are presented.Key words. GRACE – sensor analysis – accelerometer

scholarly journals Syntax-Guided Quantifier Instantiation

2021 ◽  
pp. 145-163
Author(s):  
Aina Niemetz ◽  
Mathias Preiner ◽  
Andrew Reynolds ◽  
Clark Barrett ◽  
Cesare Tinelli
Keyword(s):  
State Of The Art ◽  
Satisfiability Modulo Theories ◽  
Floating Point ◽  
New Approach ◽  
Smt Solver ◽  
Floating Point Arithmetic ◽  
Novel Approach ◽  
Non Linear ◽  
Quantifier Instantiation ◽  
Point Arithmetic

AbstractThis paper presents a novel approach for quantifier instantiation in Satisfiability Modulo Theories (SMT) that leverages syntax-guided synthesis (SyGuS) to choose instantiation terms. It targets quantified constraints over background theories such as (non)linear integer, reals and floating-point arithmetic, bit-vectors, and their combinations. Unlike previous approaches for quantifier instantiation in these domains which rely on theory-specific strategies, the new approach can be applied to any (combined) theory, when provided with a grammar for instantiation terms for all sorts in the theory. We implement syntax-guided instantiation in the SMT solver CVC4, leveraging its support for enumerative SyGuS. Our experiments demonstrate the versatility of the approach, showing that it is competitive with or exceeds the performance of state-of-the-art solvers on a range of background theories.

scholarly journals Deep Learning for Transient Image Reconstruction from ToF Data

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1962
Author(s):  
Enrico Buratto ◽  
Adriano Simonetto ◽  
Gianluca Agresti ◽  
Henrik Schäfer ◽  
Pietro Zanuttigh
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Light Response ◽  
Real Data ◽  
Depth Image ◽  
Learning Approach ◽  
Multiple Reflections ◽  
Noisy Input ◽  
Novel Approach ◽  
Incoming Light

In this work, we propose a novel approach for correcting multi-path interference (MPI) in Time-of-Flight (ToF) cameras by estimating the direct and global components of the incoming light. MPI is an error source linked to the multiple reflections of light inside a scene; each sensor pixel receives information coming from different light paths which generally leads to an overestimation of the depth. We introduce a novel deep learning approach, which estimates the structure of the time-dependent scene impulse response and from it recovers a depth image with a reduced amount of MPI. The model consists of two main blocks: a predictive model that learns a compact encoded representation of the backscattering vector from the noisy input data and a fixed backscattering model which translates the encoded representation into the high dimensional light response. Experimental results on real data show the effectiveness of the proposed approach, which reaches state-of-the-art performances.

scholarly journals The discovery of biological subphenotypes in ARDS: a novel approach to targeted medicine?

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Karin Wildi ◽  
Samantha Livingstone ◽  
Chiara Palmieri ◽  
Gianluigi LiBassi ◽  
Jacky Suen ◽  
...  
Keyword(s):  
Age Groups ◽  
Geographical Location ◽  
High Morbidity ◽  
Shock State ◽  
Pharmacological Agents ◽  
New Approach ◽  
Novel Approach ◽  
Active Research ◽  
Targeted Medicine ◽  
Core Features

AbstractThe acute respiratory distress syndrome (ARDS) is a severe lung disorder with a high morbidity and mortality which affects all age groups. Despite active research with intense, ongoing attempts in developing pharmacological agents to treat ARDS, its mortality rate remains unaltered high and treatment is still only supportive. Over the years, there have been many attempts to identify meaningful subgroups likely to react differently to treatment among the heterogenous ARDS population, most of them unsuccessful. Only recently, analysis of large ARDS cohorts from randomized controlled trials have identified the presence of distinct biological subphenotypes among ARDS patients: a hypoinflammatory (or uninflamed; named P1) and a hyperinflammatory (or reactive; named P2) subphenotype have been proposed and corroborated with existing retrospective data. The hyperinflammatory subphenotyope was clearly associated with shock state, metabolic acidosis, and worse clinical outcomes. Core features of the respective subphenotypes were identified consistently in all assessed cohorts, independently of the studied population, the geographical location, the study design, or the analysis method. Additionally and clinically even more relevant treatment efficacies, as assessed retrospectively, appeared to be highly dependent on the respective subphenotype. This discovery launches a promising new approach to targeted medicine in ARDS. Even though it is now widely accepted that each ARDS subphenotype has distinct functional, biological, and mechanistic differences, there are crucial gaps in our knowledge, hindering the translation to bedside application. First of all, the underlying driving biological factors are still largely unknown, and secondly, there is currently no option for fast and easy identification of ARDS subphenotypes. This narrative review aims to summarize the evidence in biological subphenotyping in ARDS and tries to point out the current issues that will need addressing before translation of biological subohenotypes into clinical practice will be possible.

scholarly journals A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network

2021 ◽  
Vol 11 (9) ◽  
pp. 4241
Author(s):  
Jiahua Wu ◽  
Hyo Jong Lee
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
State Of The Art ◽  
Estimation Method ◽  
Bottom Up ◽  
Center Point ◽  
Novel Approach ◽  
Body Joints

In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, we propose a novel approach called Partition Pose Representation (PPR) which integrates the instance of a person and its body joints based on joint offset. PPR leverages information about the center of the human body and the offsets between that center point and the positions of the body’s joints to encode human poses accurately. To enhance the relationships between body joints, we divide the human body into five parts, and then, we generate a sub-PPR for each part. Based on this PPR, the PCP Network can detect people and their body joints simultaneously, then group all body joints according to joint offset. Moreover, an improved l1 loss is designed to more accurately measure joint offset. Using the COCO keypoints and CrowdPose datasets for testing, it was found that the performance of the proposed method is on par with that of existing state-of-the-art bottom-up methods in terms of accuracy and speed.

scholarly journals Unimodular vs nilpotent superfield approach to pure dS supergravity

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sukruti Bansal ◽  
Silvia Nagy ◽  
Antonio Padilla ◽  
Ivonne Zavala
Keyword(s):  
String Theory ◽  
General Framework ◽  
Recent Progress ◽  
High Energy ◽  
De Sitter Spacetime ◽  
De Sitter ◽  
New Approach ◽  
Sitter Spacetime ◽  
Novel Approach ◽  
De Sitter Vacua

Abstract Recent progress in understanding de Sitter spacetime in supergravity and string theory has led to the development of a four dimensional supergravity with spontaneously broken supersymmetry allowing for de Sitter vacua, also called de Sitter supergravity. One approach makes use of constrained (nilpotent) superfields, while an alternative one couples supergravity to a locally supersymmetric generalization of the Volkov-Akulov goldstino action. These two approaches have been shown to give rise to the same 4D action. A novel approach to de Sitter vacua in supergravity involves the generalisation of unimodular gravity to supergravity using a super-Stückelberg mechanism. In this paper, we make a connection between this new approach and the previous two which are in the context of nilpotent superfields and the goldstino brane. We show that upon appropriate field redefinitions, the 4D actions match up to the cubic order in the fields. This points at the possible existence of a more general framework to obtain de Sitter spacetimes from high-energy theories.

scholarly journals Crowd Evacuation Guidance Based on Combined Action Reinforcement Learning

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Yiran Xue ◽  
Rui Wu ◽  
Jiafeng Liu ◽  
Xianglong Tang
Keyword(s):  
Reinforcement Learning ◽  
Guidance System ◽  
Force Model ◽  
Interactive Simulation ◽  
Social Force ◽  
Novel Approach ◽  
Learning Agent ◽  
Network Output ◽  
Combined Action ◽  
Crowd Evacuation

Existing crowd evacuation guidance systems require the manual design of models and input parameters, incurring a significant workload and a potential for errors. This paper proposed an end-to-end intelligent evacuation guidance method based on deep reinforcement learning, and designed an interactive simulation environment based on the social force model. The agent could automatically learn a scene model and path planning strategy with only scene images as input, and directly output dynamic signage information. Aiming to solve the “dimension disaster” phenomenon of the deep Q network (DQN) algorithm in crowd evacuation, this paper proposed a combined action-space DQN (CA-DQN) algorithm that grouped Q network output layer nodes according to action dimensions, which significantly reduced the network complexity and improved system practicality in complex scenes. In this paper, the evacuation guidance system is defined as a reinforcement learning agent and implemented by the CA-DQN method, which provides a novel approach for the evacuation guidance problem. The experiments demonstrate that the proposed method is superior to the static guidance method, and on par with the manually designed model method.

scholarly journals Compiling Life-Oriented Moral Education Textbooks for Elementary Schools in China: The Mimetic Approach in Morality and Law

2021 ◽  
pp. 209653112098296
Author(s):  
Yan Tang
Keyword(s):  
Elementary Schools ◽  
Moral Education ◽  
Life Events ◽  
Theoretical Perspective ◽  
Building Blocks ◽  
Learning Activities ◽  
Design Approach ◽  
New Approach ◽  
Novel Approach

Purpose: This study explores a novel approach to compiling life-oriented moral textbooks for elementary schools in China, specifically focusing on Morality and Law. Design/Approach/Methods: Adopting Aristotle’s Poetics as its theoretical perspective, this study illustrates and analyzes the mimetic approach used in compiling the life-oriented moral education textbook, Morality and Law. Findings: The mimetic approach involves imitating children's real activities, thoughts, and feelings in textbooks. The mimetic approach to compiling life-oriented moral textbooks comprises three strategies: constructing children's life events as building blocks for textbook compilation, designing an intricate textual device exposing the wholeness of children's life actions, and designing inward learning activities leading to children's inner worlds. Originality/Value: From the perspective of Aristotle's Poetics, the approach to compilation in Morality and Law can be defined as mimetic. And the compilation activity in the life-oriented moral education textbook also can be described as a processes of mimesis. So this article presents a new approach to compile moral education textbooks, and  an innovative way to understand the nature of one compiling activity.

A new approach based on graph matching and evolutionary approach for sport scheduling problem

2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur
Keyword(s):  
Graph Matching ◽  
State Of The Art ◽  
Travel Cost ◽  
Round Robin ◽  
New Approach ◽  
Traveling Tournament Problem ◽  
Significant Interest ◽  
National League ◽  
Better Than

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.

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