A worked example

1994 ◽  
Author(s):  
Douglas Schenck ◽  
Peter Wilson
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Initial Step ◽  
Information Model ◽  
Model Specification ◽  
Initial Model ◽  
Modeling Methodology ◽  
Worked Example ◽  
Modeling Process ◽  
Serial Number

In this Chapter we provide a complete worked example of the development of an information model. The initial model specification is taken from an ISO report, TR 9007, which, among other things, describes several means of representing this particular example. The model representations used here are the EXPRESS-G and EXPRESS languages, and this also serves as an introduction to some aspects of the languages. Minor use is also made of EXPRESS-I. For explanatory purposes we do not strictly adhere to the methodology described earlier. The principal difference being that we develop simultaneously both a graphical and a lexical version of the model. The initial model statement for the worked example is given in Section 4.1.1 and 4.1.2 and is taken from ISO TR 9007. In our modeling methodology this would be developed by the modeling team as the initial step in the modeling process. By the time the team is in a position to be as clear on the specification as given in 4.1.2 about the real world aspects of the problem, then the majority of the modeling work has been accomplished. The remaining task, which is what we will be concentrating on, is to formally describe and document the model. The scope of the model to be described has to do with the registration of cars and is limited to the scope of interest of the Registration Authority. The Registration Authority exists for the purpose of: • Knowing who is or was the registered owner of a car at any time from construction to destruction of the car. • To monitor certain laws, for example regarding fuel consumption of cars and their transfer of ownership. There are a number of manufacturers, each with one unique name. Manufacturers may start operation, with the permission of the Registration Authority (which permission cannot be withdrawn). No more than five manufacturers may be in operation at any time. A manufacturer may cease to operate provided he owns no cars, in which case permission to operate lapses. A car is of a particular model and is given a serial number by its manufacturer that is unique among the cars made by that manufacturer.

The modeling process

1994 ◽  
Author(s):  
Douglas Schenck ◽  
Peter Wilson
Keyword(s):  
Real World ◽  
Publishing House ◽  
Information Model ◽  
Information Modeling ◽  
Actual Process ◽  
Quality Model ◽  
Top Down ◽  
Domain Experts ◽  
Worked Example ◽  
Single Person

Each information model is unique, as is the process of developing that model. In this Chapter we provide some broad guidelines to assist you in creating a quality model. We are basically recommending a policy of progressive refinement when modeling but the actual process usually turns out to be iterative. So, although one might start out with good intentions of using a top-down approach, one often ends up with a mixture of top-down, bottom-up, and middle-out strategies. The recommendations are principally cast in the form of check lists and give a skeleton outline of the process. Chapter 4 provides a complete worked example which puts some flesh on the bones. An information model may be created by a single person, given sufficient knowledge, or preferably and more likely by a team of people. An information model represents some portion of the real world. In order to produce such a model an obvious requirement is knowledge of the particular real world aspects that are of interest. People with this knowledge are called domain experts. The other side of the coin is that knowledge of information modeling is required in order to develop an information model. These people are called modeling experts. Typically, the domain experts are not conversant with information modeling and the modeling experts are not conversant with the subject. Hence the usual need for at least two parties to join forces. Together the domain and modeling experts can produce an information model that satisfies their own requirements. However, an information model is typically meant to be used by a larger audience than just its creators. There is a need to communicate the model to those who may not have the skills and knowledge to create such a model but who do have the background to utilize it. Thus the requirement for a third group to review the model during its formative stages to ensure that it is understandable by the target audience. This is the review team who act somewhat like the editors in a publishing house, or like friendly quality control inspectors.

Real-world assessment of urban bus transport in a medium-sized city of the Middle East: Driving behavior, emission performance, and fuel consumption

2021 ◽  
Vol 12 (3) ◽  
pp. 113-124 ◽  
Author(s):  
Omid Ghaffarpasand ◽  
Mohammad Reza Talaie ◽  
Hossein Ahmadikia ◽  
Amirreza Talaie Khozani ◽  
Maryam Davari Shalamzari ◽  
...  
Keyword(s):  
Middle East ◽  
Fuel Consumption ◽  
Real World ◽  
Driving Behavior ◽  
Emission Performance ◽  
Urban Bus ◽  
Bus Transport

scholarly journals Decision Making Under Acute Stress Modeled by an Adaptive Temporal–Causal Network Model

2020 ◽  
Vol 07 (04) ◽  
pp. 433-452 ◽  
Author(s):  
S. Sahand Mohammadi Ziabari ◽  
Jan Treur
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Real World ◽  
Acute Stress ◽  
Second Phase ◽  
Causal Network ◽  
Severe Stress ◽  
Modeling Methodology ◽  
Network Connections ◽  
New Learning

The influence of acute severe stress or extreme emotion based on a Network-Oriented modeling methodology has been addressed here. Adaptive temporal causal network model is an approach to address the phenomena with complexity which cannot be or hard to be explained in a real-world experiment. In the first phase, the suppression of the existing network connections as a consequence of the acute stress modeled and in the second phase relaxing the suppression by giving some time and starting a new learning of the decision making in accordance to presence of stress starts again.

Implementation of the Vinehealth application, a digital health tool, into the care of patients living with brain cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13582-e13582
Author(s):  
Andrew Gvozdanovic ◽  
Riccardo Mangiapelo ◽  
Rayna Patel ◽  
Georgina Kirby ◽  
Neil Kitchen ◽  
...  
Keyword(s):  
Real World ◽  
Brain Cancer ◽  
Care Delivery ◽  
Digital Health ◽  
Patient Empowerment ◽  
Initial Step ◽  
Mixed Methodology ◽  
Structured Interviews ◽  
Strong Basis ◽  
Eortc Qlq

e13582 Background: Cancers of the brain lead to significant neurocognitive, physical and psychological morbidities. Digital technologies provide a novel platform to capture and evaluate these needs. Mobile health (mHealth) applications typically focus on one aspect of care rather than addressing the multimodal needs of the demographic of these patients. The Vinehealth application aims to address this by tracking symptoms, delivering machine learning-based personalised educational content, and facilitating reminders for medications and appointments. Where mHealth interventions traditionally lack the evidence-based approach of pharmaceuticals, this study acts as an initial step in the rigorous assessment of a new digital health tool. Methods: A mixed methodology approach was applied to evaluate the Vinehealth application as a care delivery adjunct. Patients with brain cancer were recruited from the day of their procedure ± 7 days. Over a 12-week period, we collected real-world and ePRO data via the application. We assessed qualitative feedback from mixed-methodology surveys and semi-structured interviews at onboarding and after two weeks of application use. Results: Six participants enrolled of whom four downloaded the application; four completed all interviews. One patient set up their device incorrectly and so couldn't receive the questionnaires; excluding this patient, the EQ-5D-5L and EORTC QLQ-BN20 completion rates were 100% and 83% respectively. Average scores (±SD) at onboarding and offboarding were EQ-5D-5L: 2.07±1.28 and 1.73±1.22, and QLQ-BN20: 13.33 and 22.5. In total: 212 symptoms, 174 activity, and 47 medication data points were captured, and 113 educational articles were read. Participants were generally optimistic about application use. All users stated they would recommend Vinehealth and expressed subjective improvements in care. Accessibility issues in the ePRO delivery system which impacted completion rate were identified and have subsequently been fully addressed. Conclusions: This feasibility study showed acceptable patient use, led to a subjective improvement in care, and demonstrated effective collection of real-world and validated ePRO data. This provides a strong basis to further explore the integration of the Vinehealth application into brain cancer care. This study will inform the design of a larger, more comprehensive trial continuing to evaluate improvements in care delivery through data collection, educational support and patient empowerment.

Real-world exhaust emissions and fuel consumption for diesel vehicles fueled by waste cooking oil biodiesel blends

2018 ◽  
Vol 191 ◽  
pp. 249-257 ◽  
Author(s):  
Xianbao Shen ◽  
Jiacheng Shi ◽  
Xinyue Cao ◽  
Xin Zhang ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Exhaust Emissions ◽  
Waste Cooking Oil ◽  
Biodiesel Blends ◽  
Cooking Oil ◽  
Diesel Vehicles

DEVS-Based Simulation Interoperability

2012 ◽  
pp. 377-393
Author(s):  
Thomas Wutzler ◽  
Hessam Sarjoughian
Keyword(s):  
Programming Languages ◽  
Real World ◽  
Formal Model ◽  
Simulation Models ◽  
Carbon Accounting ◽  
Model Specification ◽  
Abstract Model ◽  
Conceptual Basis ◽  
Accounting Model ◽  
Component Models

This chapter introduces the usage of DEVS for the purpose of implementing interoperability across heterogeneous simulation models. It shows that the DEVS framework provides a simple, yet effective conceptual basis for handling simulation interoperability. It discusses the various useful properties of the DEVS framework, describes the Shared Abstract Model (SAM) approach for interoperating simulation models, and compares it to other approaches. The DEVS approach enables formal model specification with component models implemented in multiple programming languages. The simplicity of the integration of component models designed in the DEVS, DTSS, and DESS simulation formalisms and implemented in the programming languages Java and C++ is demonstrated by a basic educational example and by a real world forest carbon accounting model. The authors hope, that readers will appreciate the combination of generalness and simplicity and that readers will consider using the DEVS approach for simulation interoperability in their own projects.

On the Identification of Modeler Communities

2014 ◽  
Vol 5 (2) ◽  
pp. 22-40 ◽  
Author(s):  
Dirk van der Linden ◽  
Stijn J.B.A. Hoppenbrouwers ◽  
Henderik A. Proper
Keyword(s):  
Conceptual Understanding ◽  
Real World ◽  
Empirical Support ◽  
Enterprise Modeling ◽  
Modeling Language ◽  
Science Students ◽  
Modeling Process ◽  
Psychometric Data ◽  
Computing Science ◽  
Insight Into

The authors discuss the use and challenges of identifying communities with shared semantics in Enterprise Modeling (EM). People tend to understand modeling meta-concepts (i.e., a modeling language's constructs or types) in a certain way and can be grouped by this conceptual understanding. Having an insight into the typical communities and their composition (e.g., what kind of people constitute such a semantic community) can make it easier to predict how a conceptual modeler with a certain background will generally understand the meta-concepts s/he uses, which is useful for e.g., validating model semantics and improving the efficiency of the modeling process itself. The authors have observed that in practice decisions to group people based on certain shared properties are often made, but are rarely backed up by empirical data demonstrating their supposed efficacy. The authors demonstrate the use of psychometric data from two studies involving experienced (enterprise) modeling practitioners and computing science students to find such communities. The authors also discuss the challenge that arises in finding common real-world factors shared between their members to identify them by and conclude that there is no empirical support for commonly used (and often implicit) grouping properties such as similar background, focus and modeling language.

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