A major problem to be solved in health informatics is high quality, structured and timely data collection. Standard terminologies and uniform domain conceptual models are important steps to alleviate this problem which are also proposed to enable interoperability among systems. With the aim of contributing to the solution of this problem, this study proposes novel features for the Archetypes and multi-level modeling technique in health information and knowledge modeling. The study consists of the development of a research prototype for endoscopic data management, and based on that experience, the extension of Minimal Standard Terminology in Digestive Endoscopy (MST). A major contribution of the study consists of significant extensions to the modeling formalism. The proposed modeling approach may be used in the design and development of health information systems based on archetypes for structured data collection, validation and dynamic user interface creation. The thesis work is aimed to make considerable contribution to the emerging Electronic Health Records (EHR) standards and specifications.

The motivation for computer forensics research includes the increase in crimes that involve the use of computers, the increasing capacity of digital storage media, a shortage of trained computer forensics technicians, and a lack of computer forensics standard practices. The hypothesis of this dissertation is that domain modeling of the computer forensics case environment can serve as a methodology for selecting keyword search terms and planning forensics examinations. This methodology can increase the quality of forensics examinations without significantly increasing the combined effort of planning and executing keyword searches. The contributions of this dissertation include: ? A computer forensics examination planning method that utilizes the analytical strengths and knowledge sharing abilities of domain modeling in artificial intelligence and software engineering, ? A computer forensics examination planning method that provides investigators and analysts with a tool for deriving keyword search terms from a case domain model, and ? The design and execution of experiments that illustrate the utility of the case domain modeling method. Three experiment trials were conducted to evaluate the effectiveness of case domain modeling, and each experiment trial used a distinct computer forensics case scenario: an identity theft case, a burglary and money laundering case, and a threatening email case. Analysis of the experiments supports the hypothesis that case domain modeling results in more evidence found during an examination with more effective keyword searching. Additionally, experimental data indicates that case domain modeling is most useful when the evidence disk has a relatively high occurrence of text-based documents and when vivid case background details are available. A pilot study and a case study were also performed to evaluate the utility of case domain modeling for typical law enforcement investigators. In these studies the subjects used case domain models in a computer forensics service solicitation activity. The results of these studies indicate that typical law enforcement officers have a moderate comprehension of the case domain modeling method and that they recognize a moderate amount of utility in the method. Case study subjects also indicated that the method would be more useful if supported by a semi-automated tool.

Over the decades, computer forensics has expanded from primarily examining computer evidence found on hard drives into the examination of digital devices with increasing storage capacity, to the identification of crimes and illegal activities involving the use of computers, to addressing standards and practices deficiencies, and to addressing the need to educate and train law enforcement, computer forensic technicians, and investigators. This dissertation presents the concept mapping case domain modeling approach to aid examiners/investigators in searching and identifying digital evidence and analyzing the case domain during the examination and analysis phase of the computer forensic investigation. The examination and analysis phases of a computer forensic process are two of the most important phases of the investigative process because the search for and identification of evidence data is crucial to a case; any data uncovered will help determine the guilt or innocence of a suspect. In addition, these phases can become very time consuming and cumbersome. Therefore, finding a method to reduce the amount of time spent searching and identifying potential evidence and analyzing the case domain would greatly enhance the efficiency of the computer forensic process. The hypothesis of this dissertation is that the concept mapping case domain modeling approach can serve as a method for organizing, examining, and analyzing digital forensic evidence and can enhance the quality of forensic examinations without increasing the time required to examine and analyze forensic evidence by more than 5%. Four experiments were conducted to evaluate the effectiveness of the concept mapping case domain modeling approach. Analysis of the experiments supports the hypothesis that the concept mapping case domain modeling approach can be used to organize, search, identify, and analyze digital evidence in an examination.

This research investigates a novel arrangement to pneumatic suspensions that are commonly used in heavy trucks, toward providing a dynamically balanced system that resists body roll and provides added roll stability to the vehicle. The new suspension, referred to as "balanced suspension," is implemented by retrofitting a conventional pneumatic suspension with two leveling valves and a symmetric plumbing arrangement to provide a balanced airflow and air pressure in the airsprings. This new design contributes to a balanced force distribution among the axles, which enables the suspension to maintain the body in a leveled position both statically and dynamically. This is in contrast to conventional heavy truck pneumatic suspensions that are mainly adjusted quasi-statically to level the body in response to load variations. The main objectives of the research are to discover and analyze the effects of various pneumatic components on the suspension dynamic response and numerically study the benefits of the pneumatically balanced suspension system. A pneumatic suspension model is established to capture the details of airsprings, leveling valves, check valves, pipes, and air tank based on the laws of fluid mechanics and thermodynamics. Experiments are designed and conducted to help determine and verify the modeling parameters and components. Co-simulation technique is applied to establish a multi-domain model that couples highly non-linear fluid dynamics of the pneumatic suspension with complex multi-body dynamics of an articulated vehicle. The model is used to extensively study effects of pneumatic balanced control of the suspensions on the tractor and trailer combination dynamics. The simulations indicate that the dual leveling valve arrangement of the balanced suspension provides better adjustments to the body roll by charging the airsprings on the jounce side, while purging air from the rebound side. Such an adjustment allows maintaining a larger difference in suspension force from side to side, which resists the vehicle sway and levels the truck body during cornering. Additionally, the balanced suspension better equalizes the front and rear drive axle air pressures, for a better dynamic load sharing and pitch control. It is evident from the simulation results that the balanced suspension increases roll stiffness without affecting vertical stiffness, and thereby it can serve as an anti-roll bar that results in a more stable body roll during steering maneuvers. Moreover, the Failure Mode and Effects Analysis (FMEA) study suggests that when one side of the balanced suspension fails, the other side acts to compensate for the failure. On the other hand, if the trailer is also equipped with dual leveling valves, such an arrangement will bring an additional stabilizing effect to the vehicle in case of the tractor suspension failure. The overall research results presented show that significant improvements on vehicle roll dynamics and suspension dynamic responsiveness can be achieved from the balanced suspension system. / PHD

Software development is a complex task. Executable applications comprise a mutlitude of diverse components that are developed with various frameworks, libraries, or communication platforms. The technical complexity in development retains resources, hampers efficient problem solving, and thus increases the overall cost of software production. Another significant challenge in market-driven software engineering is the variety of customer needs. It necessitates a maximum of flexibility in software implementations to facilitate the deployment of different products that are based on one single core. To reduce technical complexity, the paradigm of Model-Driven Software Development (MDSD) facilitates the abstract specification of software based on modeling languages. Corresponding models are used to generate actual programming code without the need for creating manually written, error-prone assets. Modeling languages that are tailored towards a particular domain are called domain-specific languages (DSLs). Domain-specific modeling (DSM) approximates technical solutions with intentional problems and fosters the unfolding of specialized expertise. To cope with feature diversity in applications, the Software Product Line Engineering (SPLE) community provides means for the management of variability in software products, such as feature models and appropriate tools for mapping features to implementation assets. Model-driven development, domain-specific modeling, and the dedicated management of variability in SPLE are vital for the success of software enterprises. Yet, these paradigms exist in isolation and need to be integrated in order to exhaust the advantages of every single approach. In this thesis, we propose a way to do so. We introduce the paradigm of Multi-Domain Engineering (MDE) which means model-driven development with multiple domain-specific languages in variability-intensive scenarios. MDE strongly emphasize the advantages of MDSD with multiple DSLs as a neccessity for efficiency in software development and treats the paradigm of SPLE as indispensable means to achieve a maximum degree of reuse and flexibility. We present HybridMDSD as our solution approach to implement the MDE paradigm. The core idea of HybidMDSD is to capture the semantics of particular DSLs based on properly defined semantics for software models contained in a central upper ontology. Then, the resulting semantic foundation can be used to establish references between arbitrary domain-specific models (DSMs) and sophisticated instance level reasoning ensures integrity and allows to handle partiucular change adaptation scenarios. Moreover, we present an approach to automatically generate composition code that integrates generated assets from separate DSLs. All necessary development tasks are arranged in a comprehensive development process. Finally, we validate the introduced approach with a profound prototypical implementation and an industrial-scale case study. / Softwareentwicklung ist komplex: ausführbare Anwendungen beinhalten und vereinen eine Vielzahl an Komponenten, die mit unterschiedlichen Frameworks, Bibliotheken oder Kommunikationsplattformen entwickelt werden. Die technische Komplexität in der Entwicklung bindet Ressourcen, verhindert effiziente Problemlösung und führt zu insgesamt hohen Kosten bei der Produktion von Software. Zusätzliche Herausforderungen entstehen durch die Vielfalt und Unterschiedlichkeit an Kundenwünschen, die der Entwicklung ein hohes Maß an Flexibilität in Software-Implementierungen abverlangen und die Auslieferung verschiedener Produkte auf Grundlage einer Basis-Implementierung nötig machen. Zur Reduktion der technischen Komplexität bietet sich das Paradigma der modellgetriebenen Softwareentwicklung (MDSD) an. Software-Spezifikationen in Form abstrakter Modelle werden hier verwendet um Programmcode zu generieren, was die fehleranfällige, manuelle Programmierung ähnlicher Komponenten überflüssig macht. Modellierungssprachen, die auf eine bestimmte Problemdomäne zugeschnitten sind, nennt man domänenspezifische Sprachen (DSLs). Domänenspezifische Modellierung (DSM) vereint technische Lösungen mit intentionalen Problemen und ermöglicht die Entfaltung spezialisierter Expertise. Um der Funktionsvielfalt in Software Herr zu werden, bietet der Forschungszweig der Softwareproduktlinienentwicklung (SPLE) verschiedene Mittel zur Verwaltung von Variabilität in Software-Produkten an. Hierzu zählen Feature-Modelle sowie passende Werkzeuge, um Features auf Implementierungsbestandteile abzubilden. Modellgetriebene Entwicklung, domänenspezifische Modellierung und eine spezielle Handhabung von Variabilität in Softwareproduktlinien sind von entscheidender Bedeutung für den Erfolg von Softwarefirmen. Zur Zeit bestehen diese Paradigmen losgelöst voneinander und müssen integriert werden, damit die Vorteile jedes einzelnen für die Gesamtheit der Softwareentwicklung entfaltet werden können. In dieser Arbeit wird ein Ansatz vorgestellt, der dies ermöglicht. Es wird das Multi-Domain Engineering Paradigma (MDE) eingeführt, welches die modellgetriebene Softwareentwicklung mit mehreren domänenspezifischen Sprachen in variabilitätszentrierten Szenarien beschreibt. MDE stellt die Vorteile modellgetriebener Entwicklung mit mehreren DSLs als eine Notwendigkeit für Effizienz in der Entwicklung heraus und betrachtet das SPLE-Paradigma als unabdingbares Mittel um ein Maximum an Wiederverwendbarkeit und Flexibilität zu erzielen. In der Arbeit wird ein Ansatz zur Implementierung des MDE-Paradigmas, mit dem Namen HybridMDSD, vorgestellt.

Software development is a complex task. Executable applications comprise a mutlitude of diverse components that are developed with various frameworks, libraries, or communication platforms. The technical complexity in development retains resources, hampers efficient problem solving, and thus increases the overall cost of software production. Another significant challenge in market-driven software engineering is the variety of customer needs. It necessitates a maximum of flexibility in software implementations to facilitate the deployment of different products that are based on one single core. To reduce technical complexity, the paradigm of Model-Driven Software Development (MDSD) facilitates the abstract specification of software based on modeling languages. Corresponding models are used to generate actual programming code without the need for creating manually written, error-prone assets. Modeling languages that are tailored towards a particular domain are called domain-specific languages (DSLs). Domain-specific modeling (DSM) approximates technical solutions with intentional problems and fosters the unfolding of specialized expertise. To cope with feature diversity in applications, the Software Product Line Engineering (SPLE) community provides means for the management of variability in software products, such as feature models and appropriate tools for mapping features to implementation assets. Model-driven development, domain-specific modeling, and the dedicated management of variability in SPLE are vital for the success of software enterprises. Yet, these paradigms exist in isolation and need to be integrated in order to exhaust the advantages of every single approach. In this thesis, we propose a way to do so. We introduce the paradigm of Multi-Domain Engineering (MDE) which means model-driven development with multiple domain-specific languages in variability-intensive scenarios. MDE strongly emphasize the advantages of MDSD with multiple DSLs as a neccessity for efficiency in software development and treats the paradigm of SPLE as indispensable means to achieve a maximum degree of reuse and flexibility. We present HybridMDSD as our solution approach to implement the MDE paradigm. The core idea of HybidMDSD is to capture the semantics of particular DSLs based on properly defined semantics for software models contained in a central upper ontology. Then, the resulting semantic foundation can be used to establish references between arbitrary domain-specific models (DSMs) and sophisticated instance level reasoning ensures integrity and allows to handle partiucular change adaptation scenarios. Moreover, we present an approach to automatically generate composition code that integrates generated assets from separate DSLs. All necessary development tasks are arranged in a comprehensive development process. Finally, we validate the introduced approach with a profound prototypical implementation and an industrial-scale case study. / Softwareentwicklung ist komplex: ausführbare Anwendungen beinhalten und vereinen eine Vielzahl an Komponenten, die mit unterschiedlichen Frameworks, Bibliotheken oder Kommunikationsplattformen entwickelt werden. Die technische Komplexität in der Entwicklung bindet Ressourcen, verhindert effiziente Problemlösung und führt zu insgesamt hohen Kosten bei der Produktion von Software. Zusätzliche Herausforderungen entstehen durch die Vielfalt und Unterschiedlichkeit an Kundenwünschen, die der Entwicklung ein hohes Maß an Flexibilität in Software-Implementierungen abverlangen und die Auslieferung verschiedener Produkte auf Grundlage einer Basis-Implementierung nötig machen. Zur Reduktion der technischen Komplexität bietet sich das Paradigma der modellgetriebenen Softwareentwicklung (MDSD) an. Software-Spezifikationen in Form abstrakter Modelle werden hier verwendet um Programmcode zu generieren, was die fehleranfällige, manuelle Programmierung ähnlicher Komponenten überflüssig macht. Modellierungssprachen, die auf eine bestimmte Problemdomäne zugeschnitten sind, nennt man domänenspezifische Sprachen (DSLs). Domänenspezifische Modellierung (DSM) vereint technische Lösungen mit intentionalen Problemen und ermöglicht die Entfaltung spezialisierter Expertise. Um der Funktionsvielfalt in Software Herr zu werden, bietet der Forschungszweig der Softwareproduktlinienentwicklung (SPLE) verschiedene Mittel zur Verwaltung von Variabilität in Software-Produkten an. Hierzu zählen Feature-Modelle sowie passende Werkzeuge, um Features auf Implementierungsbestandteile abzubilden. Modellgetriebene Entwicklung, domänenspezifische Modellierung und eine spezielle Handhabung von Variabilität in Softwareproduktlinien sind von entscheidender Bedeutung für den Erfolg von Softwarefirmen. Zur Zeit bestehen diese Paradigmen losgelöst voneinander und müssen integriert werden, damit die Vorteile jedes einzelnen für die Gesamtheit der Softwareentwicklung entfaltet werden können. In dieser Arbeit wird ein Ansatz vorgestellt, der dies ermöglicht. Es wird das Multi-Domain Engineering Paradigma (MDE) eingeführt, welches die modellgetriebene Softwareentwicklung mit mehreren domänenspezifischen Sprachen in variabilitätszentrierten Szenarien beschreibt. MDE stellt die Vorteile modellgetriebener Entwicklung mit mehreren DSLs als eine Notwendigkeit für Effizienz in der Entwicklung heraus und betrachtet das SPLE-Paradigma als unabdingbares Mittel um ein Maximum an Wiederverwendbarkeit und Flexibilität zu erzielen. In der Arbeit wird ein Ansatz zur Implementierung des MDE-Paradigmas, mit dem Namen HybridMDSD, vorgestellt.

Accurate linear and nonlinear models for devices and components are essential for successful RF/microwave computer aided engineering (CAE). The modeling techniques can be categorized in different levels based on the abstraction of the model as well as the application of the models at various design phases. This dissertation deals with behavioral modeling techniques for nonlinear RF components, especially amplifiers. There is an increasing demand for accurate behavioral models of RF and microwave components, or integrated circuit (IC) blocks used in wireless system designs. Accurate behavioral models help designers evaluate and select the appropriate components at simulation phase, thereby cutting development cost. However, there isnt a practical (or flexible) solution for accurate and effective behavioral model generation. This dissertation tries to tackle this problem. Power amplifiers and devices are the main components studied in this dissertation. The primary focus is on the characterization of the loadpull performance of power amplifiers and devices. Major contributions of this dissertation include development of advanced loadpull measurement procedures, large-signal load-aware behavioral model, and a load-aware behavioral model with memory-effect capabilities. There are two advanced loadpull measurements documented in this dissertation: the AM-PM loadpull measurement and the digital demodulation loadpull measurement. These two measurements may have been used internally by some research groups, however, according to the best knowledge of the author, they havent received much attention in the literature. This is the first published work on these two topics. It is shown in this work that the AM-PM performance can be strongly dependent on the load conditions. This property provides important information about the nonlinearities of power amplifiers and is used herein to create better behavioral models. This newly developed digital demodulation loadpull measurement procedure enables system designers to evaluate power amplifiers directly against digital communication system parameters such as error vector magnitude (EVM). Two example measurements are given to demonstrate the measurement system setup and the correlations between traditional nonlinear figure-of-merits and system metrics. A new behavioral modeling technique / procedure is developed based on loadpull AM-AM and AM-PM measurements. The large-signal scattering function theory is applied in the technique to formulate the model. The created model is able to automatically detect the load impedance and generate corresponding nonlinear properties. Three example models are presented to demonstrate the capability of this technique to predict accurately the output power contours, 50 ohm large-signal S21, and 3rd order intermodulation products (through additional file-based model). Finally, a modeling technique is demonstrated to enable predicting the linear memory effect within a varying load condition. The nonlinear block used in the traditional two-box model structure is replaced with the large-signal loadpull model mentioned above. By adding this new feature, the resulting model is able to predict the load-related AM-AM and AM-PM properties, which will improve the accuracy of ACPR prediction.

La fabrication additive (FA) a initié un changement de paradigme dans le secteur de la conception et de la fabrication des produits grâce à ses capacités uniques. Cependant, l'intégration des technologies de fabrication additive dans la productique traditionnelle doit permettre d'assurer une production fiable et une qualité reproductible des pièces. Dans cette optique, la modélisation et la simulation jouent un rôle essentiel pour améliorer la compréhension de la nature complexe et multi-physique des procédés de fabrication additive. De plus, l’intégration simultanée de différents modèles multi-physiques et de la prise en compte du procédé utilisé et de la pièce constituent toujours un défi pour la modélisation de ces technologies. L’objectif final de cette recherche est de développer et d’appliquer une approche de modélisation permettant une modélisation intégrée de la fabrication additive. Cette thèse analyse le processus de développement du produit et présente une méthodologie innovante intitulée ‘Dimensional Analysis Conceptual Modeling’ (DACM) pour modéliser les produits et les procédés de fabrication aux différentes étapes de conception. La méthode a été développée pour permettre la simulation de modèles multi-physiques. Elle intègre également une recherche systématique de faiblesses et de contradictions dans une première évaluation des solutions potentielles au problème. La méthodologie développée est appliquée dans plusieurs études de cas afin de présenter des modèles intégrant les processus de fabrication additive et les pièces à fabriquer. Les résultats montrent que la méthodologie DACM permet de modéliser distinctement et simultanément le produit et le processus de fabrication. Cette méthodologie permet aussi d'intégrer les modèles théoriques et expérimentaux déjà existants. Elle contribue à la conception pour la fabrication additive et aide le concepteur à anticiper les limites des procédés et de la conception plus tôt dans les premières étapes de développement du produit. En particulier, cela permet de prendre les bonnes décisions selon les différentes possibilités d'optimiser la conception des pièces et le paramétrage des machines de fabrication additive pour aboutir à la solution la plus adaptée. La méthode permet également de détecter la nécessité de reconcevoir des machines existantes en détectant les faiblesses de celles-ci. Cette thèse montre que la méthode DACM peut être potentiellement utilisée comme une approche de méta-modélisation pour la fabrication additive.Mots-clés: Fabrication Additive, Conception Pour la Fabrication Additive, Modélisation Intégrée, Développement de Produit, Dimensional Analysis Conceptual Modeling Framework / Additive manufacturing (AM) has created a paradigm shift in product design and manufacturing sector due to its unique capabilities. However, the integration of AM technologies in the mainstream production faces the challenge of ensuring reliable production and repeatable quality of parts. Toward this end, Modeling and simulation play a significant role to enhance the understanding of the complex multi-physics nature of AM processes. In addition, a central issue in modeling AM technologies is the integration of different models and concurrent consideration of the AM process and the part to be manufactured. Hence, the ultimate goal of this research is to present and apply a modeling approach to develop integrated modeling in additive manufacturing. Accordingly, the thesis oversees the product development process and presents the Dimensional Analysis Conceptual Modeling (DACM) Framework to model the product and manufacturing processes at the design stages of product development process. The Framework aims at providing simulation capabilities and systematic search for weaknesses and contradictions to the models for the early evaluation of solution variants. The developed methodology is applied in multiple case studies to present models integrating AM processes and the parts to be manufactured. This thesis results show that the proposed modeling framework is not only able to model the product and manufacturing process but also provide the capability to concurrently model product and manufacturing process, and also integrate existing theoretical and experimental models. The DACM framework contributes to the design for additive manufacturing and helps the designer to anticipate limitations of the AM process and part design earlier in the design stage. In particular, it enables the designer to make informed decisions on potential design alterations and AM machine redesign, and optimized part design or process parameter settings. DACM Framework shows potentials to be used as a metamodeling approach for additive manufacturing.

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