Short-Term and Long-Term Behavior of EPS Geofoam

2018 ◽  
Vol 47 (6) ◽  
pp. 20170207 ◽  
Author(s):  
Vinil Kumar Gade ◽  
S. M. Dasaka
Keyword(s):  
Short Term ◽  
Eps Geofoam ◽  
Long Term Behavior

scholarly journals (M,β)-Stability of Positive Linear Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Octavian Pastravanu ◽  
Mihaela-Hanako Matcovschi
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Transient Behavior ◽  
Short Term ◽  
Time Dynamics ◽  
The Right ◽  
Long Term Behavior ◽  
Stability Concept

The main purpose of this work is to show that the Perron-Frobenius eigenstructure of a positive linear system is involved not only in the characterization of long-term behavior (for which well-known results are available) but also in the characterization of short-term or transient behavior. We address the analysis of the short-term behavior by the help of the “(M,β)-stability” concept introduced in literature for general classes of dynamics. Our paper exploits this concept relative to Hölder vectorp-norms,1≤p≤∞, adequately weighted by scaling operators, focusing on positive linear systems. Given an asymptotically stable positive linear system, for each1≤p≤∞, we prove the existence of a scaling operator (built from the right and left Perron-Frobenius eigenvectors, with concrete expressions depending onp) that ensures the best possible values for the parametersMandβ, corresponding to an “ideal” short-term (transient) behavior. We provide results that cover both discrete- and continuous-time dynamics. Our analysis also captures the differences between the cases where the system dynamics is defined by matrices irreducible and reducible, respectively. The theoretical developments are applied to the practical study of the short-term behavior for two positive linear systems already discussed in literature by other authors.

scholarly journals Learning from Interventions Using Hierarchical Policies for Safe Learning

2020 ◽  
Vol 34 (06) ◽  
pp. 10352-10360
Author(s):  
Jing Bi ◽  
Vikas Dhiman ◽  
Tianyou Xiao ◽  
Chenliang Xu
Keyword(s):  
Reaction Time ◽  
State Of The Art ◽  
The State ◽  
Policy Framework ◽  
Asymptotic Performance ◽  
Short Term ◽  
Learning From Demonstrations ◽  
Hierarchical Levels ◽  
Long Term Behavior

Learning from Demonstrations (LfD) via Behavior Cloning (BC) works well on multiple complex tasks. However, a limitation of the typical LfD approach is that it requires expert demonstrations for all scenarios, including those in which the algorithm is already well-trained. The recently proposed Learning from Interventions (LfI) overcomes this limitation by using an expert overseer. The expert overseer only intervenes when it suspects that an unsafe action is about to be taken. Although LfI significantly improves over LfD, the state-of-the-art LfI fails to account for delay caused by the expert's reaction time and only learns short-term behavior. We address these limitations by 1) interpolating the expert's interventions back in time, and 2) by splitting the policy into two hierarchical levels, one that generates sub-goals for the future and another that generates actions to reach those desired sub-goals. This sub-goal prediction forces the algorithm to learn long-term behavior while also being robust to the expert's reaction time. Our experiments show that LfI using sub-goals in a hierarchical policy framework trains faster and achieves better asymptotic performance than typical LfD.

Experimental study of the short-term and long-term behavior of perfobond connectors

2018 ◽  
Vol 150 ◽  
pp. 462-474 ◽  
Author(s):  
Jing Zhang ◽  
Xiamin Hu ◽  
Liya Kou ◽  
Bing Zhang ◽  
Yuchen Jiang ◽  
...  
Keyword(s):  
Experimental Study ◽  
Short Term ◽  
Long Term Behavior

scholarly journals PENGARUH NPF, BOPO, GDP DAN SBIS TERHADAP PERTUMBUHAN ASET PERBANKAN SYARIAH DI INDONESIA

Media Ekonomi ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 9
Author(s):  
Nadhiera Ahya Dhiba ◽  
Lavlimatria Esya
Keyword(s):  
Significant Relationship ◽  
Operating Cost ◽  
Secondary Data ◽  
Islamic Banking ◽  
Short Term ◽  
Operating Income ◽  
Long Run ◽  
Short And Long Term ◽  
Long Term Behavior

<em>This study aims to analyze the factors that influence the growth of Islamic banking assets in Indonesia in the short and long term. <em>This study uses monthly secondary data from 2012 to 2016. The analytical model used is the Error Correction Model (ECM). The advantages of this model can explain short-term and long-term behavior. <em>The results showed the Non-Performing Financing (NPF) variable in the short term had a negative and significant relationship while in the long run it had a negative and not significant relationship to the growth of Islamic banking assets in Indonesia. The Gross Domestic Product (GDP) variable in the short and long term has a positive and not significant relationship to the growth of Islamic banking assets in Indonesia. Operating Cost Variable to Operating Income (BOPO) in the short and long term has a positive and not significant relationship to the growth of Islamic banking assets in Indonesia. Indonesian Islamic Bank Certificate Variables (SBIS) in the short term have a positive and significant relationship while in the long run have a positive and not significant relationship to the growth of Islamic banking assets in Indonesia.</em></em></em>

scholarly journals Creep-Rupture Reliability Analysis

1985 ◽  
Vol 107 (3) ◽  
pp. 339-346 ◽  
Author(s):  
A. Peralta-Duran ◽  
P. H. Wirsching
Keyword(s):  
Master Curve ◽  
State Of The Art ◽  
Creep Rupture ◽  
Probabilistic Design ◽  
Modeling Error ◽  
Short Term ◽  
Rupture Data ◽  
Reliability Methods ◽  
Long Term Behavior

A probablistic approach to the correlation and extrapolation of creep–rupture data is presented. Time–temperature parameters (TTP) are used to correlate the data, and an analytical expression for the master curve is developed. The expression provides a simple model for the statistical distribution of strength and fits neatly into a probabilistic design format. The analysis focuses on the Larson–Miller and on the Manson–Haferd parameters, but it can be applied to any of the TTP’s. A method is developed for evaluating material dependent constants for TTP’s. It is shown that “optimized” constants can provide a significant improvement in the correlation of the data, thereby reducing modeling error. Attempts were made to quantify the performance of the proposed method in predicting long-term behavior. Bias and uncertainty in predicting long-term behavior from short-term tests were derived for several sets of data. Examples are presented which illustrate the theory and demonstrate the application of state-of-the-art reliability methods to the design of components under creep.

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