Research Purpose: This study aims to build a new model of quality for education based on a Saudi-British consensus regarding the major factors contributing to education quality and after considering other models (such as EFQM) and other authors’ perspectives. Research Methodology: The research relies on realism philosophy and as a multiple case study with 15 cases, it utilises a mainly qualitative research design that employs semi-structured interview as its research instruments. This study has adopted an ‘Inductive’ approach to build a new model. Primary data in this study was collected by interviewing 33 Saudi and 30 British academics and higher education authorities from six Saudi and nine British universities. Content Analysis was used for analysis. Research Findings: While the degree of agreement with each of the 11 propositions was varied (a range from totally agree to totally disagree), all of the Saudi and British participants believe that eleven pillars/criteria of quality education are: Leadership and Strategic Management; Students, Academics and Staff Recruitment; Syllabus/ Curriculum; Research/Teaching; Pedagogy; Learning & research support; Knowledge management; Academics’ achievements; Students’ progress, success & satisfaction; Universities/Schools’ achievements; and Innovation and Change Management. Recommendations: Decision makers in education sector are recommended to consider all eleven identified factors and their connection to each other while developing policies for quality of education. Universities and other educational institutes should plan and allocate required budgets for implementation and maintenance of all aspects of quality in education. Research Contributions: The main contribution of this research is developing the 'Education Quality Model’. Although there has been some research regarding the quality of education, seemingly they have not led to the development of a research-based customised model such as the Education Quality Model. Another contribution is preparing a new and broad ‘Taxonomy of Quality’. In previous taxonomies, either the only focus is on education or in contrast, education is missing in these taxonomies. Furthermore, possibly for the first time, perspectives of Saudi academics are presented alongside their British counterparts regarding quality of education.

Large corporations increasingly utilize business process models for documenting and redesigning their operations. The extent of such modeling initiatives with several hundred models and dozens of often hardly trained modelers calls for automated quality assurance. While formal properties of control flow can easily be checked by existing tools, there is a notable gap for checking the quality of the textual content of models, in particular, its activity labels. In this paper, we address the problem of activity label quality in business process models. We designed a technique for the recognition of labeling styles, and the automatic refactoring of labels with quality issues. More specifically, we developed a parsing algorithm that is able to deal with the shortness of activity labels, which integrates natural language tools like WordNet and the Stanford Parser. Using three business process model collections from practice with differing labeling style distributions, we demonstrate the applicability of our technique. In comparison to a straightforward application of standard natural language tools, our technique provides much more stable results. As an outcome, the technique shifts the boundary of process model quality issues that can be checked automatically from syntactic to semantic aspects.

An inspection approach is proposed for improving the quality of conceptual models developed in a domain specific notation. First, the process of identification of desirable properties of conceptual models in a domain specific notation is described. Intra- and interview properties are considered. Semantic properties are defined considering the conceptual modeling notation. A systematic inspection process is proposed for checking semantic properties of different types of diagrams and of the relations between these diagrams. This process is applied to two real mission space conceptual models. With the proposed inspection approach, it is possible to identify subtle semantic issues which are not identified by many of the contemporary UML CASE tools and other inspection methods.

<p>In this work, I develop computational and visual tools for analyzing and manipulating the backbone of macromolecules, and I demonstrate that these tools support building better structures than currently done. These visualization and analysis tools belong to an "Intelligence Amplification" (IA) tradition (rather than complete Artificial Intelligence (AI) automation), empowering users to improve structures.</p><p>Proteins and nucleic acids are among the most important molecules in biology, mediating the majority of biochemical processes that comprise a living organism. Therefore, these macromolecules are important targets, both for basic research to improve understanding of how life works, and for medical research as possible drug targets. </p><p>The function of these macromolecules is largely determined by their 3D structure. Although these macromolecules are chemically fairly simple, made up of linear sequences of a few possible subunits, they physically fold into complex, compact structures. Overall, structural biology aims to determine the general relationship between sequence and structure of these macromolecules, through determination of the positions of the atoms within individual macromolecules. </p><p>Because it is currently impossible to directly see the position of atoms in a molecule, all structural determination techniques, including X-ray crystallography, NMR, and homology modeling, result in an interpreted <italic>model</italic> of a structure. Nearly all of these models contain mistakes, in which atoms are fit in incorrect or impossible positions. These mistakes, especially at a functionally-important location in a structure, can mislead both basic and medical research, making it critical for structural biologists to build the highest quality models possible. </p><p>This document details how my dissertation work enables the building of better macromolecular structure models. This work follows an iterative development cycle, where visual analysis of models spurs development of better tools, which in turn improves the analysis. First, I describe how my analysis of protein loops from X-ray crystal structures reveals that the traditional definition of loop endpoints is too restrictive. Second, I create a protein backbone analysis and modeling tool, using a new peptide-centric division system. I show how this tool makes it easier to study protein loops, and also how it improves an algorithm for calculating core protein models from NMR residual dipolar coupling (RDC) data. Third, I describe how 3D visualization of RDCs in their structural context improves understanding of RDCs and validates NMR models in a novel way. Fourth, I describe how local quality analysis can diagnose problems in homology models. Fifth, I demonstrate that local quality analysis can be successfully used in conjunction with model rebuilding software to correct errors in low resolution structures. The various tools and software packages I created during the course of my work are freely available and have already made a positive impact on structures being generated by the community.</p><p>Archive versions of several of these software packages (JiffiLoop, RDCvis, and KiNG) should be included with this document; current versions can be downloaded from http://kinemage.biochem.duke.edu.</p> / Dissertation

Companies increasingly use business process modeling for documenting and redesigning their operations. However, due to the size of such modeling initiatives, they often struggle with the quality assurance of their model collections. While many model properties can already be checked automatically, there is a notable gap of techniques for checking linguistic aspects such as naming conventions of process model elements. In this paper, we address this problem by introducing an automatic technique for detecting violations of naming conventions. This technique is based on text corpora and independent of linguistic resources such as WordNet. Therefore, it can be easily adapted to the broad set of languages for which corpora exist. We demonstrate the applicability of the technique by analyzing nine process model collections from practice, including over 27,000 labels and covering three different languages. The results of the evaluation show that our technique yields stable results and can reliably deal with ambiguous cases. In this way, this paper provides an important contribution to the field of automated quality assurance of conceptual models.

Context. The quality of business process models is important in the area of model-based software development. The overall goal of this study was to develop and evaluate a model for assessing the quality of models (Process Diagrams) in Business Process Model and Notation (BPMN). The model was an instantiation of the developed metamodel that adopt ISO/IEC 1926. Objectives. The objectives of the thesis were to propose, implement and evaluate a model for quality assessment of business process models in BPMN. The model was intended to help practitioners to check the quality of their BPMN models and provide meaningful feedback on whether the business process models are of good or bad quality. First objective was to develop a metamodel of models for quality assessment of business process models in BPMN, and later the model that in an instantiation of the metamodel. Within the model, the objectives were to propose the relevant quality characteristics, quality metrics, quality criteria and quality functions. Finally, usefulness of model for quality assessment of business process models in BPMN was to be evaluated. Methods. The methodology was driven by essential elements of the model for quality assessment of business process models in BPMN. This is: quality characteristics, quality metrics, quality criteria and quality functions. In the beginning the metamodel of the model was developed based on the ISO/IEC 1926 standard. Later, in order to identify quality characteristics of models existing in the literature, a systematic literature review was conducted. Quality characteristics explicitly relevant to BPMN were compared against each other and selected. Overlapping quality characteristics relevant to BPMN were merged. Next, in order to obtain quality metrics that measure aspects of models of business processes, a literature review was carried out. The literature review was restricted by a proposed set of selection criteria. The criteria were questions that every relevant literature describing quality metrics must affirmatively answer in order to identify only metrics that were able to be assigned to identify quality characteristics. If the chosen quality metrics needed to be changed or adjusted for the sake of better results, the author added changes or adjustments and provided rationale for them. Next, in order to obtain quality criteria, values of the quality metrics were gathered through measuring a repository of BPMN models. The repository was gathered as a preparatory work for the thesis and it consisted of models of varying quality. Manual measurement of quality metrics for each BPMN model from the repository could not be done within a reasonable amount of time. Therefore, a tool to automatically calculate metrics for BPMN models was implemented. The quality criteria were proposed based on the results from interpretation of the values using statistical analysis. Later, quality functions that aggregate values of the metrics were proposed. The complete model was next integrated into the tool so that it could assess a quality of real BPMN models. Finally, the model for assessing the quality of business process models in BPMN was evaluated for usefulness through a survey and survey-based experiment. Results. A metamodel of models for quality assessment of business process models in BPMN was proposed. A model for the quality assessment of models in BPMN was proposed and evaluated for usefulness. Initial sets of quality characteristics of models were found in the literature and quality characteristics that were relevant to BPMN were extracted. Quality metrics that measure aspects of models were found and adjusted to the BPMN notation. Quality criteria that state how values of quality metrics can be classified as good or bad were provided. Quality functions that state if quality characteristics are good or bad for a chosen BPMN model were provided. Finally, a tool that implements the model for quality assessment of models in BPMN was created. Conclusions. The results of the survey and survey-based experiment showed that the proposed model for quality assessment of models in BPMN works in most cases and is needed in general. Additionally, the elements of the model which should be corrected were identified. Contacted users of BPMN expressed a will to use the suggested tool associated with the model for quality assessment of business process models in BPMN.

La problématique scientifique abordée correspond à la modélisation et à l'amélioration des processus métiers. Ce problème est d'un intérêt croissant pour les entreprises qui prennent conscience de l'impact indéniable que peuvent avoir une meilleure compréhension et une meilleure gestion des processus métiers (PM) sur l'efficacité, la cohérence et la transparence de leurs activités. Le travail envisagé dans le cadre de la thèse vise à proposer une méthode et un outil pour mesurer et améliorer la qualité des modèles de processus métier. L’originalité de l’approche est qu’elle vise non seulement la qualité syntaxique mais aussi la qualité sémantique et pragmatique en s’appuyant notamment sur les connaissances du domaine. / In recent years the problems related to modeling and improving business processes have been of growing interest. Indeed, companies are realizing the undeniable impact of a better understanding and management of business processes (BP) on the effectiveness, consistency, and transparency of their business operations. BP modeling aims at a better understanding of processes, allowing deciders to achieve strategic goals of the company. However, inexperienced systems analysts often lack domain knowledge leading and this affects the quality of models they produce.Our approach targets the problem related to business process modeling quality by proposing an approach encompassing methods and tools for business process (BP) models quality measurement and improvement. We propose to support this modeling effort with an approach that uses domain knowledge to improve the semantic quality of BP models.The main contribution of this thesis is fourfold:1. Exploiting the IS domain knowledge: A business process metamodel is identified.Semantics are added to the metamodel by the mean of OCL constraints.2. Exploiting the application domain knowledge. It relies on domain ontologies. Alignment between the concepts of both metamodels is defined and illustrated.3. Designing of the guided quality process encompassing methods and techniques to evaluate and improve the business process models. Our process propose many quality constraints and metrics in order to evaluat the quality of the models and finally the process propose relevant recommendations for improvement.4. Development of a software prototype “BPM-Quality”. Our prototype implements all theabove mentioned artifacts and proposes a workflow enabling its users to evaluate andimprove CMs efficiently and effectively.We conducted a survey to validate the selection of the quality constraints through a first experience and also conducted a second experiment to evaluate the efficacy and efficiency of our overall approach and proposed improvements.

The purpose of this study was to empirically test the oft-noted hypothesis that shared mental models lead to implicit coordination. Specifically, this dissertation investigated the underlying mechanisms of implicit coordination and how different aspects of shared mental models affect the process. The research questions tested in this study were (a)how perceptions of sharedness affect the initiation of implicit coordination, (b) how actual levels of sharedness affect the process of implicit coordination, and (c) how quality of task mental models affects successful implicit coordination. Sixty same-gender, two-person teams engaged in a complex military reconnaissance planning task in which the team members were required to work together by exchanging information to plan routes for one unmanned aerial vehicle (UAV) and one unmanned ground vehicle (UGV). The results provided partial support for the influence of different facets of shared mental models on the process of implicit coordination. Specifically, individual mental model quality, not perceptions of sharedness or actual mental model sharedness, was the biggest predictor of the initiation of implicit coordination. Additionally, perceptions of sharedness and actual mental model sharedness interacted with one another, such that teams in mismatched conditions (high perceptions of sharedness but low actual sharedness [false consensus], or low perceptions of sharedness and high actual sharedness, [pluralistic ignorance]) tended to increase their communications. The implications and recommendations for future research on implicit coordination and shared mental models are discussed. Additionally, the implications for operators of unmanned vehicles are also discussed.

Psoriasis is not an illness just of these days. 3-7% of world population suffers from this illness. This diploma work focuses on quality of life of ill people. We guess that it influences such a client in a holistic way. This illness interferes into personal, professional and social life. So psoriasis is not just an illness but also an everyday problem or handicap for those who get ill.Two questionnaires were made for this research, where first of those is focused on quality of life by a standard questionnaire and the second one was created on the base of analysis of D. Johnson model. Those questionnaires were given out to ill in South and Central Counties of Bohemia. The respondents were to chose, after their completing, which one is more sensitive to problems implying from this illness. The results are graphically shown and then paid attention in chapter Discussion.Finally I would like to say, those hypotheses were acknowledged. Psoriasis influences life in a holistic way, a nurse can have a significant influence on well-being of a client with this illness in area of her nursing interventions and D. Johnson model is an effective tool for providing those ill with psoriasis with care.

Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). These programs are able to predict model accuracy before the native structure is determined. The accuracy estimation can be divided into two parts: global (the whole model accuracy) and local (the accuracy of each residue). ProQ2 is one of the most successful MQAPs for prediction of both local and global model accuracy and is based on a Machine Learning approach. In this thesis, I present my own contribution to Model Quality Assessment (MQA) and the newest developments of ProQ program series. Firstly, I describe a new ProQ2 implementation in the protein modelling software package Rosetta. This new implementation allows use of ProQ2 as a scoring function for conformational sampling inside Rosetta, which was not possible before. Moreover, I present two new methods, ProQ3 and ProQ3D that both outperform their predecessor. ProQ3 introduces new training features that are calculated from Rosetta energy functions and ProQ3D introduces a new machine learning approach based on deep learning. ProQ3 program participated in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12) and was one of the best methods in the MQA category. Finally, an important issue in model quality assessment is how to select a target function that the predictor is trying to learn. In the fourth manuscript, I show that MQA results can be improved by selecting a contact-based target function instead of more conventional superposition based functions. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>