scholarly journals Editorial of Special Issue “Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans”

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6345
Author(s):  
Javier Cuadrado ◽  
Miguel Á. Naya
Keyword(s):  
Computational Models ◽  
Special Issue ◽  
Additional Information ◽  
Physical Sensors ◽  
Virtual Sensing ◽  
System States

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming more and more popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors [...]

scholarly journals Virtual Sensoring of Motion Using Pontryagin’s Treatment of Hamiltonian Systems

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4603
Author(s):  
Timothy Sands
Keyword(s):  
Hamiltonian Systems ◽  
Computational Models ◽  
Estimation Methods ◽  
Linear Quadratic ◽  
Additional Information ◽  
Wave Disturbances ◽  
Rate Improvement ◽  
Control Decision ◽  
System States ◽  
And Control

To aid the development of future unmanned naval vessels, this manuscript investigates algorithm options for combining physical (noisy) sensors and computational models to provide additional information about system states, inputs, and parameters emphasizing deterministic options rather than stochastic ones. The computational model is formulated using Pontryagin’s treatment of Hamiltonian systems resulting in optimal and near-optimal results dependent upon the algorithm option chosen. Feedback is proposed to re-initialize the initial values of a reformulated two-point boundary value problem rather than using state feedback to form errors that are corrected by tuned estimators. Four algorithm options are proposed with two optional branches, and all of these are compared to three manifestations of classical estimation methods including linear-quadratic optimal. Over ten-thousand simulations were run to evaluate each proposed method’s vulnerability to variations in plant parameters amidst typically noisy state and rate sensors. The proposed methods achieved 69–72% improved state estimation, 29–33% improved rate improvement, while simultaneously achieving mathematically minimal costs of utilization in guidance, navigation, and control decision criteria. The next stage of research is indicated throughout the manuscript: investigation of the proposed methods’ efficacy amidst unknown wave disturbances.

scholarly journals MeSHHeading2vec: A new method for representing MeSH headings as feature vectors based on graph embedding algorithm

2019 ◽  
Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
Hai-Cheng Yi ◽  
Kai Zheng ◽  
Yan-Bin Wang
Keyword(s):  
Computational Models ◽  
Prediction Models ◽  
Graph Embedding ◽  
Computational Prediction ◽  
Additional Information ◽  
Great Hope ◽  
Node Classification ◽  
Relationship Network ◽  
The Relationship ◽  
Mesh Tree

AbstractMotivationEffectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify.ResultsIn this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network [email protected]

scholarly journals Specifications of Standards in Systems and Synthetic Biology

2015 ◽  
Vol 12 (2) ◽  
pp. 1-3 ◽  
Author(s):  
Falk Schreiber ◽  
Gary D. Bader ◽  
Martin Golebiewski ◽  
Michael Hucka ◽  
Benjamin Kormeier ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Information Exchange ◽  
Computational Models ◽  
Access Point ◽  
Economic Benefits ◽  
Special Issue ◽  
Community Initiative ◽  
Central Access ◽  
Oral Presentations ◽  
Modeling In Biology

Summary Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation).Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork [1] has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/.So far the different standards were published and made accessible through the standards’ web-pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.

scholarly journals More developments in computational models: introduction

2007 ◽  
Vol 17 (4) ◽  
pp. 585-586
Author(s):  
MARIBEL FERNÁNDEZ ◽  
IAN MACKIE
Keyword(s):  
Computational Models ◽  
International Workshop ◽  
Special Issue ◽  
Models Of Computation ◽  
Programming Paradigms

This second special issue devoted to ‘developments in computational models’ (the first was Volume 16 Issue 4) came out of an open call for papers following the First International Workshop on Developments in Computational Models (DCM). This took place in Lisbon, Portugal, on the 10th July 2005, and was a satellite event of ICALP 2005 focused on abstract models of computation and their associated programming paradigms.

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