Academic literature on the topic 'Meta-modelling'

Model Driven Software Engineering aims to provide a quality assured process for designing and generating software. Modelling frameworks that offer technologies for domain specific language and associated tool construction are called language workbenches. Since modelling is itself a domain, there are benefits to applying a workbenchbased approach to the construction of modelling languages and tools. Such a framework is a meta-modelling tool and those that can generate themselves are reflective metatools. This article reviews the current state of the art for modelling tools and proposes a set of reflective meta-modelling tool requirements. The XTools framework has been designed as a reflective meta-tool and is used as a benchmark.

Engineering process design for applications that use computationally intensive nonlinear dynamical systems can be expensive in time and resources. The presented work reviews the concept of a meta-model as a way to improve the efficiency of this process. The proposed meta-model will have a computational advantage in implementation over the computationally intensive model therefore reducing the time and resources required to design an engineering process. This work proposes to meta-model a computationally intensive nonlinear dynamical system using reduced-order linear parameter varying system modelling approach with local linear models in velocity based linearization form. The parameters of the linear time-varying meta-model are blended using Gaussian Processes regression models. The meta-model structure is transparent and relates directly to the dynamics of the computationally intensive model while the velocity-based local linear models faithfully reproduce the original system dynamics anywhere in the operating space of the system. The non-parametric blending of the meta-model local linear models by Gaussian Processes regression models is ideal to deal with data sparsity and will provide uncertainty information about the meta-model predictions. The proposed meta-model structure has been applied to second-order nonlinear dynamical systems, a small sized nonlinear transmission line model, medium sized fluid dynamics problem and the computationally intensive nonlinear transmission line model of order 5000.

The advance of electronics and information technology during the last years has made possible the proliferation of embedded systems in all fields. Accordingly, embedded systems have become increasingly available in all automotive products. These systems bring about improvements in functionality, increase of system complexity, and more interaction between hardware and software components. The development of these systems requires that engineers from multi-disciplinary fields cooperate closely in order to efficiently develop such complex products. However, there is often disagreements among these engineers about design concepts such as requirements, functions, and specifications. Despite that there have been various attempts of providing information models for automotive embedded system design, there is in practice a lack of a consistent structure that represents and describes the relationships between these concepts. Moreover, such structure has never been implemented in an industrial modeling language for complex physical systems such as Modelica. The objectives of this thesis are to provide a multi-level structure, which represents different design abstraction levels, and a meta-model for automotive embedded system design. This thesis was done at Scania, Södertälje, where these models were used for designing a fuel level display embedded system for a truck. The multi-level structure was designed and developed using a real case, fuel display system, from high-level abstraction (customer requirements) down to component/ block level specifications. Afterwards, a meta-model was proposed. The proposed meta-model was evaluated based on nine interviews with experts in information modeling and development area from both industry and academia. The following criteria were considered for the evaluation of meta-model: correctness, comprehensibility, expressiveness, generality, and usefulness. Six experts confirmed that the proposed meta-model was correct while two experts commented that in general, models could not be said to be correct or incorrect. One of the experts considered that the model required more details. In addition, the model was comprehensible for the majority of the experts. Discussions regarding semantics and expressiveness resulted in some model refinements. Afterwards, the experts acknowledged the expressiveness of this meta-model. The experts agreed that this meta-model was general for automotive system design, and six of them confirmed that the it was useful. The rest recommended that

Traceability is the common term for mechanisms to record and navigate relationships between artifacts produced by development and assessment processes. Effective management of these relationships is critical to the success of projects involving the development of complex aerospace products. Practitioners use a range of notations to model aerospace products (often as part of a defined technique or methodology). Those appropriate to electrical and electronic systems (avionics) include Use Cases for requirements, Ada for development and Fault Trees for assessment (others such as PERT networks support product management). Most notations used within the industry have tool support, although a lack of well-defined approaches to integration leads to inconsistencies and limits traceability between their respective data sets (internal models). Conceptually, the artifacts produced using such notations populate four traceability dimensions. Of these, three record links between project artifacts (describing the same product), while the fourth relates artifacts across different projects (and hence products), and across product families within the same project. The scope of this thesis is to define a meta-framework that characterises traceability dimensions for aerospace projects, and then to propose a concrete framework capturing the syntax and semantics of notations used in developing avionics for such projects which enables traceability across the four dimensions. The concrete framework is achieved by exporting information from the internal models of tools supporting these notations to an integrated environment consisting of. i) a Workspace comprising a set of structures or meta-models (models describing models) expressed in a common modelling language representing selected notations (including appropriate extensions reflecting the application domain); ii) well-formedness constraints over these structures capturing properties of the notations (and again, reflecting the domain); and iii) associations between the structures. To maintain consistency and identify conflicts, elements of the structures are verified against a system model that defines common building blocks underlying the various notations. The approach is evaluated by (partial) tool implementation of the structures which are populated using case study material derived from actual commercial specifications and industry standards.

Model Driven software development has been considered to be a further software construction technology following object-oriented software development methods and with the potential to bring new breakthroughs in the research of software development. With deepening research, a growing number of Model Driven software development methods have been proposed. The model is now widely used in all aspects of software development. One key element determining progress in Model Driven software development research is how to better express and describe the models required for various software components. From a study of current Model Driven development technologies and methods, Domain-Specific Modelling is suggested in the thesis as a Model Driven method to better realise the potential of Model-Driven Software Development. Domain-specific modelling methods can be successfully applied to actual software development projects, which need a flexible and easy to extend, meta-modelling language to provide support. There is a particular requirement for modelling languages based on domain-specific modelling methods in Meta-modelling as most general modelling languages are not suitable. The thesis focuses on implementation of domain-specific modelling methods. The "domain" is stressed as a keystone of software design and development and this is what most differentiates the approach from general software development process and methods. Concerning the design of meta-modelling languages, the meta-modelling language based on XML is defined including its abstract syntax, concrete syntax and semantics. It can support description and construction of the domain meta-model and the domain application model. It can effectively realise visual descriptions, domain objects descriptions, relationships descriptions and rules relationships of domain model. In the area of supporting tools, a meta-meta model is given. The meta-meta model provides a group of general basic component meta-model elements together with the relationships between elements for the construction of the domain meta-model. It can support multi-view, multi-level description of the domain model. Developers or domain experts can complete the design and construction of the domain-specific meta-model and the domain application model in the integrated modelling environment. The thesis has laid the foundation necessary for research in descriptive languages through further study in key technologies of meta-modelling languages based on Model Driven development.

In dieser Dissertation, schaue ich auf objekt-orientierte Metamodellierung und wie sie verwendet werden kann, um Computersprachen zu beschreiben. Dabei, fokussiere ich mich nicht nur auf die Beschreibung von Sprachen, sondern auch auf die Verwendung von Sprachbeschreibungen zur automatischen Erzeugung von Sprachwerkzeugen aus Sprachbeschreibungen. Ich nutze die Idee von Metasprachen und Metawerkzeugen. Metasprachen werden verwendet um bestimmte Sprachaspekte, wie Notationen und Semantiken, zu beschreiben, und Metawerkzeuge werden verwendet um Sprachwerkzeuge wie Editoren und Interpreter aus entsprechenden Beschreibungen zu erzeugen. Diese Kombination von Beschreibung und automatischer Entwicklung von Werkzeugen ist als Domänenspezifische Modellierung (DSM) bekannt. Ich verwende DSM basierend auf objekt-orientierter Metamodellierung zur Beschreibung der wichtigen Aspekte ausführbarer Computersprachen. Ich untersuche existierende Metasprachen und Metawerkzeuge für die Beschreibung von Sprachvorkommen, ihrer konkreten Repräsentation und Semantik. Weiter, entwickle ich eine neue Plattform zur Beschreibung von Sprachen basierend auf dem CMOF-Modell der OMG MOF 2.x Empfehlungen. Ich entwickle eine Metasprache und Metawerkzeug für textuelle Notationen. Schlussendlich, entwickle ich eine graphische Metasprache und Metawerkzeug zur Beschreibung von operationaler Semantik von Computersprachen. Um die Anwendbarkeit der vorgestellten Techniken zu prüfen, nehme ich SDL, die Specification and Description Language, als einen Archetypen für textuell notierte Sprachen mit ausführbaren Instanzen. Für diesen Archetyp zeige ich, dass die präsentierten Metasprachen und Metawerkzeuge es erlauben solche Computersprachen zu beschreiben und automatisch Werkzeuge für diese Sprachen zu erzeugen.
In this thesis, I look into object-oriented meta-modelling and how it can be used to describe computer languages. Thereby, I do not only focus on describing languages, but also on utilising the language descriptions to automatically create language tools from language descriptions. I use the notion of meta-languages and meta-tools. Meta-languages are used to describe certain language aspects, such as notation or semantics, and meta-tools are used to create language tools, such as editors or interpreters, from corresponding descriptions. This combination of describing and automated development of tools is known as domain specific modelling (DSM). I use DSM based on object-oriented meta-modelling to describe all important aspects of executable computer languages. I look into existing meta-languages and meta-tools for describing language utterances, their concrete representation, and semantics. Furthermore, I develop a new platform to define languages based on the CMOF-model of the OMG MOF 2.x recommendations. I develop a meta-language and meta-tool for textual language notations. Finally, I develop a new graphical meta-language and meta-tool for describing the operational semantics of computer languages. To prove the applicability of the presented techniques, I take SDL, the Specification and Description Language, as an archetype for textually notated languages with executable instances. For this archetype, I show that the presented meta-languages and meta-tools allow to describe such computer languages and allow to automatically create tools for those languages.

Driven by the severe competition within the construction industry, the necessity of improving and optimizing the performance of construction supply chain has been aroused. This thesis proposes three problems with regard to the construction supply chain optimization from three perspectives, namely, deterministic single objective optimization, stochastic optimization and multi-objective optimization respectively. Mathematical models for each problem are constructed accordingly and meta-heuristic algorithms are developed and applied for resolving these three problems.

Now over 25 years old, functional magnetic resonance imaging (fMRI) has made significant contributions in improving our understanding of the human brain function. However, some limitations of fMRI studies, including those associated with the small sample sizes that are typically employed, raise concerns about validity of the technique. Lately, growing interest has been observed in combining the results of multiple fMRI studies in a meta-analysis. This can potentially address the limitations of single experiments and raise opportunities for reaching safer conclusions. Coordinate-based meta-analyses (CBMA) use the peak activation locations from multiple studies to find areas of consistent activations across experiments. CBMA presents statisticians with many interesting challenges. Several issues have been solved but there are also many open problems. In this thesis, we review literature on the topic and after describing the unsolved problems we then attempt to address some of the most important. The first problem that we approach is the incorporation of study-specific characteristics in the meta-analysis model known as meta-regression. We propose an novel meta-regression model based on log-Gaussian Cox processes and develop a parameter estimation algorithm using the Hamiltonian Monte Carlo method. The second problem that we address is the use of CBMA data as prior in small underpowered fMRI studies. Based on some existing work on the topic, we develop a hierarchical model for fMRI studies that uses previous CBMA findings as a prior for the location of the effects. Finally, we discuss a classical problem of meta-analysis, the file drawer problem, where studies are suppressed from the literature because they fail to report any significant finding. We use truncated models to infer the total number of non-significant studies that are missing from a database. All our methods are tested on both simulated and real data.

We have assembled an interdisciplinary group of distinguished authors—all experts in the field—who have been testing the efficacy of cognitive and working-memory training using a combination of behavioral, neuroimaging, meta-analytic, and computational modelling methods. This edited volume is a defining resource on the practicality, utility, and validity of the field of cognitive training research in general, and working memory training in particular. Importantly, one focus of the book is on the notion of transfer-namely, the extent to which cognitive training generalizes to learning and performance measures that were decidedly not part of the training regimen.

The INRA Feeding System for Ruminants has been renewed to better address emerging challenges for animal nutrition: prevision of productive responses, product quality, animal health and emissions to the environment, in a larger extent of breeding contexts. The new system is mainly built from meta-analyses of large data bases, and modelling. The dietary supply model accounts for digestive interactions and flows of individual nutrients, so that feed values depend on the final ration. Animal requirements account for variability in metabolic efficiency. Various productive and non-productive animal responses to diets are quantified. This book presents the whole system for dairy and meat, large and small ruminant production, including specificities for tropical and Mediterranean areas. The first two sections present biological concepts and equations (with their field of application and statistical accuracy) used to predict intake (including at grazing) and nutrient supply (Section 1), animal’s requirements and multiple responses to diets (Section 2). They apply to net energy, metabolisable protein and amino acids, water, minerals and vitamins. Section 3 presents the use of concepts and equations in rationing with two purposes: (1) diet calculation for a given performance objective; and (2) prediction of the multiple responses of animal to diet changes. Section 4 displays the tables of feed values, and their prevision. All the equations and concepts are embedded in the fifth version of INRAtion® software for practical use.

Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asymptomatic disease in current (13%) and former (24%) Australian smokers.(4) The purpose of this Evidence Check review is to identify and analyse existing and emerging evidence for LDCT lung cancer screening in high-risk individuals to guide future program and policy planning. Evidence Check questions This review aimed to address the following questions: 1. What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? 2. What is the evidence of potential harms from lung cancer screening for higher-risk individuals? 3. What are the main components of recent major lung cancer screening programs or trials? 4. What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Summary of methods The authors searched the peer-reviewed literature across three databases (MEDLINE, PsycINFO and Embase) for existing systematic reviews and original studies published between 1 January 2009 and 8 August 2019. Fifteen systematic reviews (of which 8 were contemporary) and 64 original publications met the inclusion criteria set across the four questions. Key findings Question 1: What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? There is sufficient evidence from systematic reviews and meta-analyses of combined (pooled) data from screening trials (of high-risk individuals) to indicate that LDCT examination is clinically effective in reducing lung cancer mortality. In 2011, the landmark National Lung Cancer Screening Trial (NLST, a large-scale randomised controlled trial [RCT] conducted in the US) reported a 20% (95% CI 6.8% – 26.7%; P=0.004) relative reduction in mortality among long-term heavy smokers over three rounds of annual screening. High-risk eligibility criteria was defined as people aged 55–74 years with a smoking history of ≥30 pack-years (years in which a smoker has consumed 20-plus cigarettes each day) and, for former smokers, ≥30 pack-years and have quit within the past 15 years.(5) All-cause mortality was reduced by 6.7% (95% CI, 1.2% – 13.6%; P=0.02). Initial data from the second landmark RCT, the NEderlands-Leuvens Longkanker Screenings ONderzoek (known as the NELSON trial), have found an even greater reduction of 26% (95% CI, 9% – 41%) in lung cancer mortality, with full trial results yet to be published.(6, 7) Pooled analyses, including several smaller-scale European LDCT screening trials insufficiently powered in their own right, collectively demonstrate a statistically significant reduction in lung cancer mortality (RR 0.82, 95% CI 0.73–0.91).(8) Despite the reduction in all-cause mortality found in the NLST, pooled analyses of seven trials found no statistically significant difference in all-cause mortality (RR 0.95, 95% CI 0.90–1.00).(8) However, cancer-specific mortality is currently the most relevant outcome in cancer screening trials. These seven trials demonstrated a significantly greater proportion of early stage cancers in LDCT groups compared with controls (RR 2.08, 95% CI 1.43–3.03). Thus, when considering results across mortality outcomes and early stage cancers diagnosed, LDCT screening is considered to be clinically effective. Question 2: What is the evidence of potential harms from lung cancer screening for higher-risk individuals? The harms of LDCT lung cancer screening include false positive tests and the consequences of unnecessary invasive follow-up procedures for conditions that are eventually diagnosed as benign. While LDCT screening leads to an increased frequency of invasive procedures, it does not result in greater mortality soon after an invasive procedure (in trial settings when compared with the control arm).(8) Overdiagnosis, exposure to radiation, psychological distress and an impact on quality of life are other known harms. Systematic review evidence indicates the benefits of LDCT screening are likely to outweigh the harms. The potential harms are likely to be reduced as refinements are made to LDCT screening protocols through: i) the application of risk predication models (e.g. the PLCOm2012), which enable a more accurate selection of the high-risk population through the use of specific criteria (beyond age and smoking history); ii) the use of nodule management algorithms (e.g. Lung-RADS, PanCan), which assist in the diagnostic evaluation of screen-detected nodules and cancers (e.g. more precise volumetric assessment of nodules); and, iii) more judicious selection of patients for invasive procedures. Recent evidence suggests a positive LDCT result may transiently increase psychological distress but does not have long-term adverse effects on psychological distress or health-related quality of life (HRQoL). With regards to smoking cessation, there is no evidence to suggest screening participation invokes a false sense of assurance in smokers, nor a reduction in motivation to quit. The NELSON and Danish trials found no difference in smoking cessation rates between LDCT screening and control groups. Higher net cessation rates, compared with general population, suggest those who participate in screening trials may already be motivated to quit. Question 3: What are the main components of recent major lung cancer screening programs or trials? There are no systematic reviews that capture the main components of recent major lung cancer screening trials and programs. We extracted evidence from original studies and clinical guidance documents and organised this into key groups to form a concise set of components for potential implementation of a national lung cancer screening program in Australia: 1. Identifying the high-risk population: recruitment, eligibility, selection and referral 2. Educating the public, people at high risk and healthcare providers; this includes creating awareness of lung cancer, the benefits and harms of LDCT screening, and shared decision-making 3. Components necessary for health services to deliver a screening program: a. Planning phase: e.g. human resources to coordinate the program, electronic data systems that integrate medical records information and link to an established national registry b. Implementation phase: e.g. human and technological resources required to conduct LDCT examinations, interpretation of reports and communication of results to participants c. Monitoring and evaluation phase: e.g. monitoring outcomes across patients, radiological reporting, compliance with established standards and a quality assurance program 4. Data reporting and research, e.g. audit and feedback to multidisciplinary teams, reporting outcomes to enhance international research into LDCT screening 5. Incorporation of smoking cessation interventions, e.g. specific programs designed for LDCT screening or referral to existing community or hospital-based services that deliver cessation interventions. Most original studies are single-institution evaluations that contain descriptive data about the processes required to establish and implement a high-risk population-based screening program. Across all studies there is a consistent message as to the challenges and complexities of establishing LDCT screening programs to attract people at high risk who will receive the greatest benefits from participation. With regards to smoking cessation, evidence from one systematic review indicates the optimal strategy for incorporating smoking cessation interventions into a LDCT screening program is unclear. There is widespread agreement that LDCT screening attendance presents a ‘teachable moment’ for cessation advice, especially among those people who receive a positive scan result. Smoking cessation is an area of significant research investment; for instance, eight US-based clinical trials are now underway that aim to address how best to design and deliver cessation programs within large-scale LDCT screening programs.(9) Question 4: What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Assessing the value or cost-effectiveness of LDCT screening involves a complex interplay of factors including data on effectiveness and costs, and institutional context. A key input is data about the effectiveness of potential and current screening programs with respect to case detection, and the likely outcomes of treating those cases sooner (in the presence of LDCT screening) as opposed to later (in the absence of LDCT screening). Evidence about the cost-effectiveness of LDCT screening programs has been summarised in two systematic reviews. We identified a further 13 studies—five modelling studies, one discrete choice experiment and seven articles—that used a variety of methods to assess cost-effectiveness. Three modelling studies indicated LDCT screening was cost-effective in the settings of the US and Europe. Two studies—one from Australia and one from New Zealand—reported LDCT screening would not be cost-effective using NLST-like protocols. We anticipate that, following the full publication of the NELSON trial, cost-effectiveness studies will likely be updated with new data that reduce uncertainty about factors that influence modelling outcomes, including the findings of indeterminate nodules. Gaps in the evidence There is a large and accessible body of evidence as to the effectiveness (Q1) and harms (Q2) of LDCT screening for lung cancer. Nevertheless, there are significant gaps in the evidence about the program components that are required to implement an effective LDCT screening program (Q3). Questions about LDCT screening acceptability and feasibility were not explicitly included in the scope. However, as the evidence is based primarily on US programs and UK pilot studies, the relevance to the local setting requires careful consideration. The Queensland Lung Cancer Screening Study provides feasibility data about clinical aspects of LDCT screening but little about program design. The International Lung Screening Trial is still in the recruitment phase and findings are not yet available for inclusion in this Evidence Check. The Australian Population Based Screening Framework was developed to “inform decision-makers on the key issues to be considered when assessing potential screening programs in Australia”.(10) As the Framework is specific to population-based, rather than high-risk, screening programs, there is a lack of clarity about transferability of criteria. However, the Framework criteria do stipulate that a screening program must be acceptable to “important subgroups such as target participants who are from culturally and linguistically diverse backgrounds, Aboriginal and Torres Strait Islander people, people from disadvantaged groups and people with a disability”.(10) An extensive search of the literature highlighted that there is very little information about the acceptability of LDCT screening to these population groups in Australia. Yet they are part of the high-risk population.(10) There are also considerable gaps in the evidence about the cost-effectiveness of LDCT screening in different settings, including Australia. The evidence base in this area is rapidly evolving and is likely to include new data from the NELSON trial and incorporate data about the costs of targeted- and immuno-therapies as these treatments become more widely available in Australia.