This diploma thesis deals with the modeling and evaluation tools that are used for process modeling. The aim is to provide a method of selecting the most appropriate tool for selected requirements. This goal is achieved by using several subgoals, which include tools analysis for process modeling, design criteria for the selection of tools, their weights calculation, design and construction method for selecting tools in Excel and create case studies that will demonstrate the principles of selection tools. At the beginning of the thesis is characterized by the area of process management, its history, actual trends and definitions related thereto. Another chapter is a description of notations that are used for modeling processes. The largest part of the chapter is devoted to the characteristics Notation Business Process Model and Notation (BPMN), which together with their graphic design described all the elements of notation. The remaining part of the chapter describes the notation event-driven process chain (EPC) and the Unified Modeling Language (UML). A description of tools for process modeling is dedicated to the fifth chapter includes a detailed characterization of each instrument. Based on the individual tools and literary sources, the next chapter in the proposed criteria by which the tools will be evaluated. For calculating the weights of the proposed criteria is used Fuller method. The chapter concludes with evaluation tools previously described and a description of how to select the creation tools in Excel. The work ends with case studies which serve to illustrate the procedure for selecting tools.

This thesis evaluates several aspects of the cognitive modeling tools, using a questionnaire as the survey method. We try to assess the the suitability for cognitive modeling task of the cognitive modeling tools, from the perspective of international community of cognitive modeling tool users. Part of this assessment is done with respect to general usability of software and the rest is specialized for the cognitive modeling issues. Frequency and correlation analyses reveal that there is a significant relationship between suitability as a software product and suitability as a cognitive modeling tool. Specifically, there are correlations between the features of the tool involving flexibility, presentation of input and output and the process of design, implementation and evaluation of a cognitive modeling tool, while these processes are negatively related to adversely effecting features of the tool, such as having to do extra tasks that are not related to the actual task. Our study confirms that a cognitive modeling tool can also be evaluated from the perspective of a general purpose software product, and also gives clues about directions for improvement to tool developers.

Enterprises are growing in complexity due to numerous interactions within and outside the enterprise. Enterprise modeling addresses this issue of complexity by helping to structure it. A review of the literature indicates several issues in the field of enterprise modeling need to be addressed. First, the terms related to enterprise modeling have numerous definitions, each one focusing on different aspects. These definitions are analyzed and a comprehensive definition is provided. Next, enterprise modeling methodologies and enterprise modeling frameworks in the literature focus on different views when modeling an enterprise, thus making it difficult for an enterprise to choose the framework that best fits their needs. In order to resolve this, an enterprise modeling framework is designed that attempts to incorporate all of the views of an enterprise. This framework is then extended, by taking into account various models and functionalities provided in enterprise modeling software packages.

Background: Software Engineering is a high-demand field constantly changing with new languages, tools, and frameworks. The use of software modeling in Software Engineering is essential for solving complex problems since it helps the developer understand abstraction and develop high-level code. For an overview of the current state of software modeling, this research attempts to present an overview of software modeling curricula and how students benefit from attending these courses. Method: First, to assess the survey’s clarity and eliminate any potential for bias, we conducted a pilot study with five teachers at M¨alardalen University. We surveyed 23 participants from 23 institutions and ten countries to get their responses to Research Questions 2, 3, and 4. We have collected data for programs from 10 different countries with their top 5 universities to address Research Question 1. Results: To maintain meaning in the Software Engineering domain, we used our findings to seek the usage of knowledge gained from the academic environment in the industry when the students shift from academia to industry. Through this thesis, we present the current view of software modeling curricula and their contribution to preparing students for the industry. The following significant findings were reached: (i) software modeling aids in better understanding of abstraction concepts and the development of high-level applications; (ii) UML is one of the most popular languages; and (iii) some limitations of software modeling tools include license type, outdated tools, or poorly documented tools.

Aujourd'hui, l'évaluation des conséquences environnementales et sanitaires d'événements majeurs liés aux rejets dans l'atmosphère de substances radiologiques ou chimiques est, de plus en plus, basée sur la mise en œuvre d'outils de modélisation. La capacité de ces outils à appréhender de manière toujours plus fine l'ampleur spatiale et temporelle de ce type d'événements contribue à leur positionnement croissant en appui aux situations d'urgence. Cependant, l'accident de Fukushima a souligné qu'en dépit de cette tendance, l'apport des outils n'est pas encore optimal au regard de l'environnement décisionnel de l'organisation de sécurité civile en charge, notamment, des décisions de protection des populations. Cette recherche s'attèle donc, sur la base d'interviews et d'observations d'exercices de crise, à clarifier la place des outils de modélisation en situation d'urgence. L'étude suggère qu'à ce jour, la gestion de ces situations prend place dans un processus de co-construction de sens entre acteurs d'expertise NRBC-E et décideurs, favorisant l'atteinte de consensus en matière de prise de décision. L'étude met également en lumière l'importance que joue le COD, de par sa structure même, comme lieu d'échange entre acteurs aux expertises et expériences complémentaires, dans la perception et la gestion des changements de contexte. Ainsi, nous suggérons qu'en se positionnant au niveau de l'évaluation de la situation, les outils de modélisation fournissent une information qui respecte les pratiques actuelles dans l'aide à la décision en situation d'urgence et le respect des rôles et expertises de chaque acteur. Dans cette optique, les modèles de dispersion et d'impact sont donc susceptibles de s'intégrer au développement plus global d'outils d'aide à la gestion des crises auprès de l'organisation de sécurité civile, principalement comme soutien à la construction d'une représentation collective et dynamique de la situation entre expert et décideur. / Environmental and health impact assessment of accidental or intentional releases of potentially hazardous materials in the atmosphere is increasingly supported by the development of modeling tools. Their potential to assess the spatial and temporal extent and severity of toxic plumes contributes to their growing development as CBRN-E emergency support tools. However, the Fukushima nuclear accident underlined that their support is not yet optimal regarding civil security organizations in charge of population protection. This research therefore tends to clarify the role of these modelling tools in emergency management. For this purpose, interviews and observations of crisis exercises have been conducted. This study suggests that nowadays, CBRN-E emergency management takes place in a sensemaking co-constructing process between CBRN-E experts and emergency managers contributing to the achievement of consensus in the decision making process. This study also highlights the key role played by the crisis center, regarding its proper organizational structure as a sharing place between actors with complementary expertise and experience, in the perception and response to changing circumstances. Thus, this study suggests that by providing situation assessment results, modeling tools meet the current practices both in terms of emergency support tools used for civilian protection organization and in respect of each actors' contributions. In this perspective, these modelling tools are likely to end up being part of the development of crisis management support tools for building a collective representation of the CBRN-E situation between expertise and decision.

Information uncertainty is inherent in many real-world problems and adds a layer of complexity to modeling and visualization tasks. This often causes users to ignore uncertainty, especially when it comes to visualization, thereby discarding valuable knowledge. A coherent framework for the modeling and visualization of information uncertainty is needed to address this issue In this work, we have identified four major barriers to the uptake of uncertainty modeling and visualization. Firstly, there are numerous uncertainty modeling tech- niques and users are required to anticipate their uncertainty needs before building their data model. Secondly, parameters of uncertainty tend to be treated at the same level as variables making it easy to introduce avoidable errors. This causes the uncertainty technique to dictate the structure of the data model. Thirdly, propagation of uncertainty information must be manually managed. This requires user expertise, is error prone, and can be tedious. Finally, uncertainty visualization techniques tend to be developed for particular uncertainty types, making them largely incompatible with other forms of uncertainty information. This narrows the choice of visualization techniques and results in a tendency for ad hoc uncertainty visualization. The aim of this thesis is to present an integrated information uncertainty modeling and visualization environment that has the following main features: information and its uncertainty are encapsulated into atomic variables, the propagation of uncertainty is automated, and visual mappings are abstracted from the uncertainty information data type. Spreadsheets have previously been shown to be well suited as an approach to visu- alization. In this thesis, we devise a new paradigm extending the traditional spreadsheet to intrinsically support information uncertainty.Our approach is to design a framework that integrates uncertainty modeling tech- niques into a hierarchical order based on levels of detail. The uncertainty information is encapsulated and treated as a unit allowing users to think of their data model in terms of the variables instead of the uncertainty details. The system is intrinsically aware of the encapsulated uncertainty and is therefore able to automatically select appropriate uncertainty propagation methods. A user-objectives based approach to uncertainty visualization is developed to guide the visual mapping of abstracted uncertainty information. Two main abstractions of uncertainty information are explored for the purpose of visual mapping: the Unified Uncertainty Model and the Dual Uncertainty Model. The Unified Uncertainty Model provides a single view of uncertainty for visual mapping, whereas the Dual Uncertainty Model distinguishes between possibilistic and probabilistic views. Such abstractions provide a buffer between the visual mappings and the uncertainty type of the underly- ing data, enabling the user to change the uncertainty detail without causing the visual- ization to fail. Two main case studies are presented. The first case study covers exploratory and forecasting tasks in a business planning context. The second case study inves- tigates sensitivity analysis for financial decision support. Two minor case studies are also included: one to investigate the relevancy visualization objective applied to busi- ness process specifications, and the second to explore the extensibility of the system through General Purpose Graphics Processor Unit (GPGPU) use. A quantitative anal- ysis compares our approach to traditional analytical and numerical spreadsheet-based approaches. Two surveys were conducted to gain feedback on the from potential users. The significance of this work is that we reduce barriers to uncertainty modeling and visualization in three ways. Users do not need a mathematical understanding of the uncertainty modeling technique to use it; uncertainty information is easily added, changed, or removed at any stage of the process; and uncertainty visualizations can be built independently of the uncertainty modeling technique.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis investigates integrating recommender systems into model-driven engineering tools powered by domain-specific modeling languages. The objective of integrating recommender systems into such tools is overcome a shortcoming of proactive modeling where the modeler must inform the model intelligence engine how to progress when it cannot automatically determine the next modeling action to execute (e.g., add, delete, or edit). To evaluate our objective, we integrated a recommender system into the Proactive Modeling Engine, which is a add-on for the Generic Modeling Environment (GME). We then conducted experiments to both subjective and objectively evaluate the enhancements to the Proactive Modeling Engine. The results of our experiments show that integrating recommender system into the Proactive Modeling Engine results in an Average Reciprocal Hit-Rank (ARHR) of 0.871. Likewise, the integration results in System Usability Scale (SUS) rating of 77. Finally, user feedback shows that the integration of the recommender system to the Proactive Modeling Engine increases the usability and learnability of domain-speci c modeling tools.

Building energy usage can be derived and controlled by performing building energy modeling. BEM can be performed using numerous software tools such as DesignBuilder, OpenStudio, EnergyPlus etc. These modeling tools can be sorted into three different modeling categories: Black-box, Gray-box and White-box. It is important for a modeler to be able to quickly select the proper tool from the proper category to meet the need of the project. To validate the method of categorizing tools, the three models generated using tools from each category and the modeling outputs required were compared. Each model was designed to estimate the amount of heat transfer through building envelope elements. All the modeling tools were able to generate the required output, therefore, the method for selecting the most effective tool will be based on the output requirements and the time it takes to build the model, time it takes to generate the output and interpret the output.

<p dir="ltr">This research aims to address these critical challenges in uncertainty quantification. The objective is to employ data-driven approaches for UQ with physics models.</p>