scholarly journals Hierarchical semantic composition of biosimulation models using bond graphs

2021 ◽  
Author(s):  
Niloofar Shahidi ◽  
Michael Pan ◽  
Soroush Safaei ◽  
Kenneth Tran ◽  
Edmund J. Crampin ◽  
...  
Keyword(s):  
Computational Models ◽  
Reference Model ◽  
Model Development ◽  
Circulatory System ◽  
Model Composition ◽  
Bond Graphs ◽  
Arterial Circulation ◽  
Systems Modelling ◽  
Underlying Processes ◽  
Physiological Systems

AbstractSimulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition.Author summaryBiological and physiological systems usually involve multiple underlying processes, mechanisms, structures, and phenomena, referred to here as sub-systems. Modelling the whole system every time from scratch requires a huge amount of effort. An alternative is to model each sub-system in a modular fashion, i.e., containing meaningful interfaces for connecting to other modules. Such modules are readily combined to produce a whole-system model. For the combined model to be consistent, modules must be described using the same modelling scheme. One way to achieve this is to use energy-based models that are consistent with the conservation laws of physics. Here, we present an approach that achieves this using bond graphs, which allows modules to be combined faster and more efficiently. First, physically plausible modules are generated using a small number of template modules. Then a meaningful interface is added to each module to automate connection. This approach is illustrated by applying this method to an existing model of the circulatory system and verifying the results against the reference model.

scholarly journals Hierarchical semantic composition of biosimulation models using bond graphs

2021 ◽  
Vol 17 (5) ◽  
pp. e1008859
Author(s):  
Niloofar Shahidi ◽  
Michael Pan ◽  
Soroush Safaei ◽  
Kenneth Tran ◽  
Edmund J. Crampin ◽  
...  
Keyword(s):  
Computational Models ◽  
Model Development ◽  
Bond Graph ◽  
Composite Model ◽  
Model Composition ◽  
Bond Graphs ◽  
Arterial Circulation ◽  
General Methodology ◽  
Major Benefit ◽  
Physiological Systems

Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition.

Assessment of Machine Learning-Based Audiovisual Quality Predictors

2021 ◽  
Vol 17 (2) ◽  
pp. 1-22
Author(s):  
Mythili K. ◽  
Manish Narwaria
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Quality Assessment ◽  
Computational Models ◽  
Model Development ◽  
Multimedia Communication ◽  
Current Approach ◽  
Learning Ability ◽  
Data Uncertainty ◽  
Attractive Alternative

Quality assessment of audiovisual (AV) signals is important from the perspective of system design, optimization, and management of a modern multimedia communication system. However, automatic prediction of AV quality via the use of computational models remains challenging. In this context, machine learning (ML) appears to be an attractive alternative to the traditional approaches. This is especially when such assessment needs to be made in no-reference (i.e., the original signal is unavailable) fashion. While development of ML-based quality predictors is desirable, we argue that proper assessment and validation of such predictors is also crucial before they can be deployed in practice. To this end, we raise some fundamental questions about the current approach of ML-based model development for AV quality assessment and signal processing for multimedia communication in general. We also identify specific limitations associated with the current validation strategy which have implications on analysis and comparison of ML-based quality predictors. These include a lack of consideration of: (a) data uncertainty, (b) domain knowledge, (c) explicit learning ability of the trained model, and (d) interpretability of the resultant model. Therefore, the primary goal of this article is to shed some light into mentioned factors. Our analysis and proposed recommendations are of particular importance in the light of significant interests in ML methods for multimedia signal processing (specifically in cases where human-labeled data is used), and a lack of discussion of mentioned issues in existing literature.

scholarly journals Business processes within enterprises providing public services: reference model development

2021 ◽  
Vol 284 ◽  
pp. 07027
Author(s):  
Olga Voronova ◽  
Viktoria Sadakova ◽  
Viktoria Sheleyko ◽  
Irina Ilyina
Keyword(s):  
Real Estate ◽  
Public Services ◽  
Business Processes ◽  
Reference Model ◽  
Model Development ◽  
Real Estate Market ◽  
State Regulation ◽  
Public Institutions ◽  
The Real Estate ◽  
The Real Estate Market

This study focuses on the development of a reference model of business processes within enterprises providing public services in the field of real estate. The study revealed key features of process approach in the system of state regulation of the real estate market, considered organizational foundations of activities and technological processes of public institutions, and modelled the main business processes of public regulation enterprise at the top detail level. Based on a detailed representation of the main, managing and supporting business processes, the reference model was developed.

scholarly journals Simplified Building Thermal Model Development and Parameters Evaluation Using a Stochastic Approach

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2899
Author(s):  
Abhinandana Boodi ◽  
Karim Beddiar ◽  
Yassine Amirat ◽  
Mohamed Benbouzid
Keyword(s):  
Reference Model ◽  
Model Development ◽  
Network Models ◽  
Real Data ◽  
Stochastic Approach ◽  
Simplified Model ◽  
Model Parameters ◽  
Order Model ◽  
Parameter Values ◽  
Low Order

This paper proposes an approach to develop building dynamic thermal models that are of paramount importance for controller application. In this context, controller requires a low-order, computationally efficient, and accurate models to achieve higher performance. An efficient building model is developed by having proper structural knowledge of low-order model and identifying its parameter values. Simplified low-order systems can be developed using thermal network models using thermal resistances and capacitances. In order to determine the low-order model parameter values, a specific approach is proposed using a stochastic particle swarm optimization. This method provides a significant approximation of the parameters when compared to the reference model whilst allowing low-order model to achieve 40% to 50% computational efficiency than the reference one. Additionally, extensive simulations are carried to evaluate the proposed simplified model with solar radiation and identified model parameters. The developed simplified model is afterward validated with real data from a case study building where the achieved results clearly show a high degree of accuracy compared to the actual data.

scholarly journals The minimalist grammar of action

2012 ◽  
Vol 367 (1585) ◽  
pp. 103-117 ◽  
Author(s):  
Katerina Pastra ◽  
Yiannis Aloimonos
Keyword(s):  
Computational Models ◽  
Reference Model ◽  
Action Learning ◽  
Human Action ◽  
Human Cognition ◽  
Neural Basis ◽  
Biologically Inspired ◽  
Language Structure ◽  
Minimalist Grammar ◽  
Temporal Sequences

Language and action have been found to share a common neural basis and in particular a common ‘syntax’, an analogous hierarchical and compositional organization. While language structure analysis has led to the formulation of different grammatical formalisms and associated discriminative or generative computational models, the structure of action is still elusive and so are the related computational models. However, structuring action has important implications on action learning and generalization, in both human cognition research and computation. In this study, we present a biologically inspired generative grammar of action, which employs the structure-building operations and principles of Chomsky's Minimalist Programme as a reference model. In this grammar, action terminals combine hierarchically into temporal sequences of actions of increasing complexity; the actions are bound with the involved tools and affected objects and are governed by certain goals. We show, how the tool role and the affected-object role of an entity within an action drives the derivation of the action syntax in this grammar and controls recursion, merge and move, the latter being mechanisms that manifest themselves not only in human language, but in human action too.

CubeSat Model-Based Systems Engineering (MBSE) Reference Model - Development and Distribution - Interim Status

2016 ◽  
Author(s):  
David Kaslow ◽  
Bradley Ayres ◽  
Philip T. Cahill ◽  
Michael J. Chonoles ◽  
Laura Hart ◽  
...  
Keyword(s):  
Systems Engineering ◽  
Reference Model ◽  
Model Development ◽  
Model Based ◽  
Model Based Systems Engineering

scholarly journals An evaluation of ozone dry deposition in global scale chemistry climate models

2015 ◽  
Vol 15 (11) ◽  
pp. 6419-6436 ◽  
Author(s):  
C. Hardacre ◽  
O. Wild ◽  
L. Emberson
Keyword(s):  
Dry Deposition ◽  
Climate Models ◽  
Model Development ◽  
Critical Evaluation ◽  
Global Scale ◽  
Systematic Bias ◽  
Deposition Fluxes ◽  
In Series ◽  
Underlying Processes ◽  
Earth System Models

Abstract. Dry deposition to the Earth's surface is an important process from both an atmospheric and biospheric perspective. Dry deposition controls the atmospheric abundance of many compounds as well as their input to vegetative surfaces, thus linking the atmosphere and biosphere. In many atmospheric and Earth system models it is represented using "resistance in series" schemes developed in the 1980s. These methods have remained relatively unchanged since their development and do not take into account more recent understanding of the underlying processes that have been gained through field and laboratory based studies. In this study we compare dry deposition of ozone across 15 models which contributed to the TF HTAP model intercomparison to identify where differences occur. We compare modelled dry deposition of ozone to measurements made at a variety of locations in Europe and North America, noting differences of up to a factor of two but no clear systematic bias over the sites examined. We identify a number of measures that are needed to provide a more critical evaluation of dry deposition fluxes and advance model development.

scholarly journals Addressing current challenges in cancer immunotherapy with mathematical and computational modelling

2017 ◽  
Vol 14 (131) ◽  
pp. 20170150 ◽  
Author(s):  
Anna Konstorum ◽  
Anthony T. Vella ◽  
Adam J. Adler ◽  
Reinhard C. Laubenbacher
Keyword(s):  
Immune Response ◽  
Numerical Analysis ◽  
Cancer Immunotherapy ◽  
Computational Models ◽  
Model Development ◽  
Computational Modelling ◽  
Tumour Microenvironment ◽  
Biological Information ◽  
Rational Therapy ◽  
Therapy Design

The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour–immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development.

Virtual Tools for Safety and Ergonomic Evaluations of Electric Vehicle Architecture

2013 ◽  
Author(s):  
Ambarish Kulkarni ◽  
Ajay Kapoor
Keyword(s):  
Motion Capture ◽  
Computational Models ◽  
Evaluation Studies ◽  
Model Development ◽  
Scale Model ◽  
Second Phase ◽  
Vehicle Architecture ◽  
Camera Systems ◽  
Single Operator ◽  
Ergonomic Evaluation

Electric vehicles (EV’s) are alternative fuel technology in auto industry with wide acceptance across globe. This paper elaborates virtual methods used to as tool for safety and ergonomic evaluations of in wheel design using Switch Reluctance Motor (SRM). In our recent research, a unique design of in wheel design using SRM has been developed. Special advantages of this design include modularity, scalability, cost effectiveness, and easy installation. Easy installation of in wheel design architecture is one of the prime criteria, since it relates to changing of tyres in long runs. In the proposed passenger car, if work is carried out for maintenance issues, generally single operator (mechanic) dose tyre changing or wheel/brake servicing. Two validations are important, mainly safety of the operator; secondly design for assembly of motor, and tyre rims. As a part of this research, Virtual Reality (VR) based safety and ergonomic evaluation studies have been conducted for the in wheel design adaptations. The computational models and virtual modelling simulations using motion capture, Arena and EON reality mimicked live system environments, so as to validate effectiveness motor assembly and disassembly functionality using human as an interface. Initial phase consists of schematic representations of models to evaluate conceptualisation for different designs. Based on schematics, SR motor and rim tyre models were developed and interfaced in VR environment. In second phase, vehicle topology was reverse engineered using hand held 3D scanner and converted to metafile for full scale model development. In third phase, motion capture was used with 20 camera systems to video record the existing human movements and rigid body such as tyre to develop live environment. Finally all three phases were interfaced together in VR environment to evaluate assembly and disassembly functions. Based on the validation of these, designs were fine tuned for effective assembly functionality. The VR based safety and ergonomic evaluation procedures were used for demonstration of wheel assembly disassembly functions by single operator. Similar context can be extended to other automotive design evaluations, without substantial prototype costs for safety and ergonomic evaluations.

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