scholarly journals Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Xuefeng Yan ◽  
Yong Zhou ◽  
Yan Wen ◽  
Xudong Chai
Keyword(s):  
Hierarchical Model ◽  
Description Logic ◽  
Expert Knowledge ◽  
Uncertain Reasoning ◽  
Model Structure ◽  
Meta Model ◽  
Simulation And Optimization ◽  
Qualitative And Quantitative ◽  
Level Model ◽  
High Level

The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation.

scholarly journals Automated movement assessment in stroke rehabilitation

2021 ◽  
Author(s):  
Tamim Ahmed ◽  
Kowshik Thopalli ◽  
Thanassis Rikakis ◽  
Pavan Turaga ◽  
Aisling Kelliher ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Hierarchical Model ◽  
Stroke Rehabilitation ◽  
Expert Knowledge ◽  
Low Cost ◽  
Data Driven ◽  
Task Completion ◽  
Convolutional Network ◽  
Rgb Images ◽  
High Level

We are developing a system for long-term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper extremity stroke rehabilitation at the home. We propose a hierarchical model for automatically segmenting stroke survivor's movements and generating training task performance assessment scores during rehabilitation. The hierarchical model fuses expert therapist knowledge-based approaches with data-driven techniques. The expert knowledge is more observable in the higher layers of the hierarchy (task and segment) and therefore more accessible to algorithms incorporating high-level constraints relating to activity structure (i.e. type and order of segments per task). We utilize an HMM and a Decision Tree model to connect these high-level priors to data-driven analysis. The lower layers (RGB images and raw kinematics) need to be addressed primarily through data-driven techniques. We use a transformer-based architecture operating on low-level action features (tracking of individual body joints and objects) and a Multi-Stage Temporal Convolutional Network(MS-TCN) operating on raw RGB images. We develop a sequence combining these complementary algorithms effectively, thus encoding the information from different layers of the movement hierarchy. Through this combination, we produce robust segmentation and task assessment results on noisy, variable, and limited data, which is characteristic of low-cost video capture of rehabilitation at the home. Our proposed approach achieves 85% accuracy in per-frame labeling, 99% accuracy in segment classification, and 93% accuracy in task completion assessment. Although the methodology proposed in this paper applies to upper extremity rehabilitation using the SARAH system, it can potentially be used, with minor alterations, to assist automation in many other movement rehabilitation contexts (i.e. lower extremity training for neurological accidents).

Model Based Monitoring and Controlling for Platform-as-a-Service (PaaS)

2012 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Jin Shao ◽  
Qianxiang Wang ◽  
Hong Mei
Keyword(s):  
Cloud Service ◽  
Quality Of Services ◽  
Meta Model ◽  
Platform As A Service ◽  
Low Level ◽  
Model Based ◽  
Level Model ◽  
High Level ◽  
Service Paradigm

Platform as a Service (PaaS) is a typical cloud service paradigm that allows PaaS consumers to deploy and manage applications (usually services to SaaS consumers). To ensure the quality of services to both PaaS consumers and SaaS consumers, PaaS must be equipped with enough monitoring and controlling ability to make runtime adjustment actions. Although most of the components in PaaS have provided their own management interface, it is hard to perform adjustment actions based on raw runtime data collected from these low level management interfaces due to the diversity and dynamics of components in PaaS. This paper proposes a model based monitoring and controlling approach for PaaS. The proposed approach masks the underlying heterogeneity of components in PaaS and presents a high level model for monitoring and controlling. The model is instantiated automatically based on pre-defined meta-model, which effectively reduces the development efforts. A monitoring and controlling framework based on this approach is designed and implemented in a practical PaaS, which shows the feasibility of the proposed approach.

scholarly journals Automated Movement Assessment in Stroke Rehabilitation

2021 ◽  
Vol 12 ◽  
Author(s):  
Tamim Ahmed ◽  
Kowshik Thopalli ◽  
Thanassis Rikakis ◽  
Pavan Turaga ◽  
Aisling Kelliher ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Hierarchical Model ◽  
Stroke Rehabilitation ◽  
Expert Knowledge ◽  
Low Cost ◽  
Data Driven ◽  
Task Completion ◽  
Convolutional Network ◽  
Rgb Images ◽  
High Level

We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper extremity stroke rehabilitation at the home. We propose a hierarchical model for automatically segmenting stroke survivor's movements and generating training task performance assessment scores during rehabilitation. The hierarchical model fuses expert therapist knowledge-based approaches with data-driven techniques. The expert knowledge is more observable in the higher layers of the hierarchy (task and segment) and therefore more accessible to algorithms incorporating high level constraints relating to activity structure (i.e., type and order of segments per task). We utilize an HMM and a Decision Tree model to connect these high level priors to data driven analysis. The lower layers (RGB images and raw kinematics) need to be addressed primarily through data driven techniques. We use a transformer based architecture operating on low-level action features (tracking of individual body joints and objects) and a Multi-Stage Temporal Convolutional Network(MS-TCN) operating on raw RGB images. We develop a sequence combining these complimentary algorithms effectively, thus encoding the information from different layers of the movement hierarchy. Through this combination, we produce a robust segmentation and task assessment results on noisy, variable and limited data, which is characteristic of low cost video capture of rehabilitation at the home. Our proposed approach achieves 85% accuracy in per-frame labeling, 99% accuracy in segment classification and 93% accuracy in task completion assessment. Although the methodology proposed in this paper applies to upper extremity rehabilitation using the SARAH system, it can potentially be used, with minor alterations, to assist automation in many other movement rehabilitation contexts (i.e., lower extremity training for neurological accidents).

Pollen morphology of some Tamarix (Tamaricaceae) species of Iran

2020 ◽  
Vol 62 (1-2) ◽  
pp. 151-161
Author(s):  
T. Shagholi ◽  
M. Keshavarzi ◽  
M. Sheidai
Keyword(s):  
North Africa ◽  
Pollen Grains ◽  
Ecological Niches ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Qualitative And Quantitative ◽  
Petal Length ◽  
Electron Microscopes ◽  
High Level ◽  
Scanning Electron Microscopes

Tamarix L. (Tamaricaceae) is a halophytic shrub in different parts of Asia and North Africa. Taxonomy and species limitation of Tamarix is very complex. This genus has three sections as Tamarix, Oligadenia, and Polyadenia, which are mainly separated by petal length, the number of stamens, the shape of androecial disk and attachment of filament on the androecial disk. As there was no palynological data on pollen features of Tamarix species of Iran, in the present study 12 qualitative and quantitative pollen features were evaluated to find diagnostic ones. Pollen grains of 8 Tamarix species were collected from nature. Pollen grains were studied without any treatment. Measurements were based on at least 50 pollen grains per specimen. Light and scanning electron microscopes were used. Multivariate statistical methods were applied to clarify the species relationships based on pollen data. All species studied showed monad and tricolpate (except some individuals of T. androssowii). Some Tamarix species show a high level of variability, in response to ecological niches and phenotypic plasticity, which make Tamarix species separation much more difficult. Based on the results of the present study, pollen grains features are not in agreement with previous morphological and molecular genetics about the sectional distinction.

Modeling and design of role engineering in development of access control for dynamic information systems

2013 ◽  
Vol 61 (3) ◽  
pp. 569-579 ◽  
Author(s):  
A. Poniszewska-Marańda
Keyword(s):  
Information Systems ◽  
Dynamic Information ◽  
Minimal Set ◽  
Distributed Information ◽  
Heterogeneous Information ◽  
System Protection ◽  
Level Model ◽  
Model Independent ◽  
Role Concept ◽  
High Level

Abstract Nowadays, the growth and complexity of functionalities of current information systems, especially dynamic, distributed and heterogeneous information systems, makes the design and creation of such systems a difficult task and at the same time, strategic for businesses. A very important stage of data protection in an information system is the creation of a high level model, independent of the software, satisfying the needs of system protection and security. The process of role engineering, i.e. the identification of roles and setting up in an organization is a complex task. The paper presents the modeling and design stages in the process of role engineering in the aspect of security schema development for information systems, in particular for dynamic, distributed information systems, based on the role concept and the usage concept. Such a schema is created first of all during the design phase of a system. Two actors should cooperate with each other in this creation process, the application developer and the security administrator, to determine the minimal set of user’s roles in agreement with the security constraints that guarantee the global security coherence of the system.

scholarly journals Dynamic modelling of a servo self-pierce riveting (SPR) process

2021 ◽  
pp. 095440542110374
Author(s):  
Daniel Tang ◽  
Mike Evans ◽  
Paul Briskham ◽  
Luca Susmel ◽  
Neil Sims
Keyword(s):  
Dynamic Modelling ◽  
System Level ◽  
Optimum Process ◽  
Current Limit ◽  
Level Model ◽  
System Level Model ◽  
Head Height ◽  
Extensive Experimental Data ◽  
High Level

Self-pierce riveting (SPR) is a complex joining process where multiple layers of material are joined by creating a mechanical interlock via the simultaneous deformation of the inserted rivet and surrounding material. Due to the large number of variables which influence the resulting joint, finding the optimum process parameters has traditionally posed a challenge in the design of the process. Furthermore, there is a gap in knowledge regarding how changes made to the system may affect the produced joint. In this paper, a new system-level model of an inertia-based SPR system is proposed, consisting of a physics-based model of the riveting machine and an empirically-derived model of the joint. Model predictions are validated against extensive experimental data for multiple sets of input conditions, defined by the setting velocity, motor current limit and support frame type. The dynamics of the system and resulting head height of the joint are predicted to a high level of accuracy. Via a model-based case study, changes to the system are identified, which enable either the cycle time or energy consumption to be substantially reduced without compromising the overall quality of the produced joint. The predictive capabilities of the model may be leveraged to reduce the costs involved in the design and validation of SPR systems and processes.

scholarly journals High Level Model of Time Predictable Multitask Control Unit

2015 ◽  
Vol 48 (4) ◽  
pp. 348-353 ◽  
Author(s):  
Łukasz Golly ◽  
Adam Milik ◽  
Andrzej Pulka
Keyword(s):  
Control Unit ◽  
Level Model ◽  
High Level

FEMLIB: An Object-Oriented Framework for Optimization and Simulation

1995 ◽  
Author(s):  
Michael M. Tiller ◽  
Jonathan A. Dantzig
Keyword(s):  
Material Properties ◽  
Object Oriented ◽  
The Finite Element Method ◽  
Simulation And Optimization ◽  
Gradient Based ◽  
Level Problem ◽  
Simulation Results ◽  
Optimization And Simulation ◽  
High Level ◽  
Simulation Parameters

Abstract In this paper we discuss the design of an object-oriented framework for simulation and optimization. Although oriented around high-level problem solving, the framework defines several classes of problems and includes concrete implementations of common algorithms for solving these problems. Simulations are run by combining these algorithms, as needed, for a particular problem. Included in this framework is the capability to compute the sensitivity of simulation results to the different simulation parameters (e.g. material properties, boundary conditions, etc). This sensitivity information is valuable in performing optimization because it allows the use of gradient-based optimization algorithms. Also included in the system are many useful abstractions and implementations related to the finite element method.

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