Biorobots, Nonlinear Dynamics and Perception

2008 ◽  
Vol 58 ◽  
pp. 143-152
Author(s):  
Paolo Arena ◽  
Davide Lombardo ◽  
Luca Patanè
Keyword(s):  
Nonlinear Dynamics ◽  
Real Time ◽  
Continuous Time ◽  
Biologically Inspired ◽  
Time Dynamics ◽  
Nonlinear Network ◽  
Biologically Inspired Robots ◽  
Novel Approach ◽  
Perceptual Control ◽  
Efficient Control

In this contribution a survey on a novel approach to locomotion and perception in biologically inspired robots is presented. The basic electronic architecture for modeling and implementing nonlinear dynamics involved in motion and perceptual control of the robot is the Cellular nonlinear network paradigm. It is shown how this continuous time lattice of neural-like circuits can generate suitable and real-time dynamics for efficient control of multi-actuators moving machines, and also to create the basis for a perceptual control of their behaviors.

scholarly journals Analysis of Real-Time Control Systems using First-Order Continuization

10.29007/8nq6 ◽  
2020 ◽  
Author(s):  
Maximilian Gaukler
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Continuous Time ◽  
Real Time Control ◽  
Control Loops ◽  
Time Dynamics ◽  
First Order ◽  
Time Control ◽  
Formal Framework ◽  
Continuous Time System

Experience Report: Real-Time control systems can be difficult to analyze due to the mixture of discrete-time and continuous-time dynamics. This difficulty is particularly pronounced if the timing is non-periodic, e.g., due to network or execution effects. Still, most control loops behave similar to a purely continuous-time system disturbed by a small discretization error, which is exploited by Bak and Johnson (2015) in the method of Continuization. This paper uncovers limitations of that work and presents an extension, First-Order Continuization, based on a new formal framework that recovers previous results and eases future development.

scholarly journals Exact real-time dynamics of single-impurity Anderson model from a single-spin hybridization-expansion

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Patryk Kubiczek ◽  
Alexey Rubtsov ◽  
Alexander Lichtenstein
Keyword(s):  
Real Time ◽  
Continuous Time ◽  
Quantum Monte Carlo ◽  
Time Dynamics ◽  
Single Spin ◽  
Impurity Model ◽  
Sign Problem ◽  
Spin Polarized ◽  
Anderson Impurity Model ◽  
Long Time

In this work we introduce a modified real-time continuous-time hybridization-expansion quantum Monte Carlo solver for a time-dependent single-orbital Anderson impurity model: CT-1/2-HYB-QMC. In the proposed method the diagrammatic expansion is performed only for one out of the two spin channels, while the resulting effective single-particle problem for the other spin is solved semi-analytically for each expansion diagram. CT-1/2-HYB-QMC alleviates the dynamical sign problem by reducing the order of sampled diagrams and makes it possible to reach twice as long time scales in comparison to the standard CT-HYB method. We illustrate the new solver by calculating an electric current through impurity in paramagnetic and spin-polarized cases.

scholarly journals The Role of Oxygen Intake and Liver Enzyme on The Dynamics of Damaged Hepatocytes: Implications to Ischaemic Liver Injury via A Mathematical Model

2020 ◽  
Author(s):  
Aditi Ghosh ◽  
Claire Onsager ◽  
Leon Arriola ◽  
Andrew Mason ◽  
William Lee ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Liver Injury ◽  
Real Time ◽  
The Body ◽  
Model Parameters ◽  
Oxygen Intake ◽  
Serum Aminotransferase ◽  
Time Dynamics ◽  
Novel Approach ◽  
Time Basis

AbstractIschaemic Hepatitis (IH) or Hypoxic Hepatitis (HH) also known as centrilobular liver cell necrosis is an acute liver injury characterized by a rapid increase in serum aminotransferase. The liver injury typically results from another underlying medical conditions like cardiac failure, respiratory failure and septic shock in which the liver becomes damaged due to deprivation of either blood or oxygen. IH is a potentially lethal condition which is often preventable if diagnosed properly. Unfortunately, mechanism that causes IH are often not well understood, making it difficult to diagnose or accurately quantify the patterns of related biomakers. In most cases, currently the only way to determine a case of IH (i.e., to diagnose it) is to rule out all other possible conditions for other liver injuries. A better understanding of the liver’s response to IH is necessary to aid in its diagnosis, measurement and improve outcomes. The goal of this study, is to identify mechanisms that can alter a few associated biomarkers for reducing density of damaged hepatocytes, and thus reduce chances of IH. To this end, we develop a mathematical model capturing dynamics of hepatocytes in the liver through the rise and fall of associated liver enzymes aspartate transaminase (AST), alanine transaminase (ALT) and lactate dehydrogenase (LDH) related to condition of IH. The model analysis provides a novel approach to predict the level of biomarkers given variations in the systemic oxygen in the body. Using IH patient data in US, novel model parameters are described and then estimated for the first time to capture real time dynamics of hepatocytes in the presence and absence of IH condition. Different scenarios of patient conditions were also analyzed and validated using empirical information. This study and its results may allow physicians to estimate the extent of liver damage in a IH patient based on their enzyme levels and receive faster treatment on real time basis.

scholarly journals Improved real-time dynamics from imaginary frequency lattice simulations

2018 ◽  
Vol 175 ◽  
pp. 07001 ◽  
Author(s):  
Jan M. Pawlowski ◽  
Alexander Rothkopf
Keyword(s):  
Inverse Problem ◽  
Real Time ◽  
Quantum Dynamics ◽  
Initial Conditions ◽  
Transport Coefficients ◽  
Bound State ◽  
Spectral Functions ◽  
Direct Evaluation ◽  
Time Dynamics ◽  
Novel Approach

The computation of real-time properties, such as transport coefficients or bound state spectra of strongly interacting quantum fields in thermal equilibrium is a pressing matter. Since the sign problem prevents a direct evaluation of these quantities, lattice data needs to be analytically continued from the Euclidean domain of the simulation to Minkowski time, in general an ill-posed inverse problem. Here we report on a novel approach to improve the determination of real-time information in the form of spectral functions by setting up a simulation prescription in imaginary frequencies. By carefully distinguishing between initial conditions and quantum dynamics one obtains access to correlation functions also outside the conventional Matsubara frequencies. In particular the range between ω0 and ω1 = 2πT, which is most relevant for the inverse problem may be more highly resolved. In combination with the fact that in imaginary frequencies the kernel of the inverse problem is not an exponential but only a rational function we observe significant improvements in the reconstruction of spectral functions, demonstrated in a simple 0+1 dimensional scalar field theory toy model.

scholarly journals The role of oxygen intake and liver enzyme on the dynamics of damaged hepatocytes: Implications to ischaemic liver injury via a mathematical model

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0230833
Author(s):  
Aditi Ghosh ◽  
Claire Onsager ◽  
Andrew Mason ◽  
Leon Arriola ◽  
William Lee ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Liver Injury ◽  
Real Time ◽  
The Body ◽  
Model Parameters ◽  
Oxygen Intake ◽  
Serum Aminotransferase ◽  
Time Dynamics ◽  
Novel Approach

Ischaemic Hepatitis (IH) or Hypoxic Hepatitis (HH) also known as centrilobular liver cell necrosis is an acute liver injury characterized by a rapid increase in serum aminotransferase. The liver injury typically results from different underlying medical conditions such as cardiac failure, respiratory failure and septic shock in which the liver becomes damaged due to deprivation of either blood or oxygen. IH is a potentially lethal condition that is often preventable if diagnosed timely. The role of mechanisms that cause IH is often not well understood, making it difficult to diagnose or accurately quantify the patterns of related biomarkers. In most patients, currently, the only way to determine a case of IH is to rule out all other possible conditions for liver injuries. A better understanding of the liver’s response to IH is necessary to aid in its diagnosis, measurement, and improve outcomes. The goal of this study is to identify mechanisms that can alter associated biomarkers for reducing the density of damaged hepatocytes, and thus reduce the chances of IH. We develop a mathematical model capturing dynamics of hepatocytes in the liver through the rise and fall of associated liver enzymes aspartate transaminase (AST), alanine transaminase (ALT) and lactate dehydrogenase (LDH) related to the condition of IH. The model analysis provides a novel approach to predict the level of biomarkers given variations in the systemic oxygen in the body. Using IH patient data in the US, novel model parameters are described and then estimated for the first time to capture real-time dynamics of hepatocytes in the presence and absence of IH condition. The results may allow physicians to estimate the extent of liver damage in an IH patient based on their enzyme levels and receive faster treatment on a real-time basis.

A novel approach to the real-time modelling of large urban drainage systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 19-24 ◽  
Author(s):  
Richard Norreys ◽  
Ian Cluckie
Keyword(s):  
Real Time ◽  
Dynamic Models ◽  
Drainage System ◽  
Radar Data ◽  
Urban Drainage ◽  
Real Time Control ◽  
Empirical Modelling ◽  
Time Control ◽  
Novel Approach ◽  
Non Linear Systems

Conventional UDS models are mechanistic which though appropriate for design purposes are less well suited to real-time control because they are slow running, difficult to calibrate, difficult to re-calibrate in real time and have trouble handling noisy data. At Salford University a novel hybrid of dynamic and empirical modelling has been developed, to combine the speed of the empirical model with the ability to simulate complex and non-linear systems of the mechanistic/dynamic models. This paper details the ‘knowledge acquisition module’ software and how it has been applied to construct a model of a large urban drainage system. The paper goes on to detail how the model has been linked with real-time radar data inputs from the MARS c-band radar.

A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment

2021 ◽  
Author(s):  
Brij B. Gupta ◽  
Krishna Yadav ◽  
Imran Razzak ◽  
Konstantinos Psannis ◽  
Arcangelo Castiglione ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Novel Approach

scholarly journals A novel approach to optimize the production cost of railway coaches of India using situational-based composite triangular and trapezoidal fuzzy LPP models

2021 ◽  
Author(s):  
Rakesh Kumar ◽  
Gaurav Dhiman ◽  
Neeraj Kumar ◽  
Rajesh Kumar Chandrawat ◽  
Varun Joshi ◽  
...  
Keyword(s):  
Comparative Study ◽  
Real Time ◽  
Production Cost ◽  
Upper Bounds ◽  
Production Costs ◽  
Cost Data ◽  
Novel Approach ◽  
Membership Grade ◽  
Minimum Costs

AbstractThis article offers a comparative study of maximizing and modelling production costs by means of composite triangular fuzzy and trapezoidal FLPP. It also outlines five different scenarios of instability and has developed realistic models to minimize production costs. Herein, the first attempt is made to examine the credibility of optimized cost via two different composite FLP models, and the results were compared with its extension, i.e., the trapezoidal FLP model. To validate the models with real-time phenomena, the Production cost data of Rail Coach Factory (RCF) Kapurthala has been taken. The lower, static, and upper bounds have been computed for each situation, and then systems of optimized FLP are constructed. The credibility of each model of composite-triangular and trapezoidal FLP concerning all situations has been obtained, and using this membership grade, the minimum and the greatest minimum costs have been illustrated. The performance of each composite-triangular FLP model was compared to trapezoidal FLP models, and the intense effects of trapezoidal on composite fuzzy LPP models are investigated.

scholarly journals Machine Learning Solutions for Bridge Scour Forecast Based on Monitoring Data

2021 ◽  
pp. 036119812110126
Author(s):  
Negin Yousefpour ◽  
Steve Downie ◽  
Steve Walker ◽  
Nathan Perkins ◽  
Hristo Dikanski
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Monitoring Data ◽  
Sensor Data ◽  
Monitoring Systems ◽  
Bridge Scour ◽  
Scour Monitoring ◽  
Novel Approach ◽  
Bayesian Inference Method ◽  
Water Level Variations

Bridge scour is a challenge throughout the U.S.A. and other countries. Despite the scale of the issue, there is still a substantial lack of robust methods for scour prediction to support reliable, risk-based management and decision making. Throughout the past decade, the use of real-time scour monitoring systems has gained increasing interest among state departments of transportation across the U.S.A. This paper introduces three distinct methodologies for scour prediction using advanced artificial intelligence (AI)/machine learning (ML) techniques based on real-time scour monitoring data. Scour monitoring data included the riverbed and river stage elevation time series at bridge piers gathered from various sources. Deep learning algorithms showed promising in prediction of bed elevation and water level variations as early as a week in advance. Ensemble neural networks proved successful in the predicting the maximum upcoming scour depth, using the observed sensor data at the onset of a scour episode, and based on bridge pier, flow and riverbed characteristics. In addition, two of the common empirical scour models were calibrated based on the observed sensor data using the Bayesian inference method, showing significant improvement in prediction accuracy. Overall, this paper introduces a novel approach for scour risk management by integrating emerging AI/ML algorithms with real-time monitoring systems for early scour forecast.

Sign in / Sign up

Export Citation Format

Share Document