This dissertation examines how disability researchers define disability. It is based on four studies. The first describes different definitions of disability in disability research. The second study is a conceptual analysis of the use of disability in a sample of disability research classics. In this study, it is evident that use of the concept is all but clear. It is concluded that especially environmentally based disability definitions would benefit from further empirical investigations. The notion that environmental factors (such as barriers) are a causal aspect of disability is rather widely accepted among disability researchers. However, it has not been empirically studied to such an extent that it is possible to construct workable theories of this relationship. The third study focuses on administrative definitions of disability and investigates the possibility of using data on disabled people that have been gathered by Swedish welfare authorities. It is concluded that rich data are available, but also that researchers must scrutinize how disability has been defined in these contexts. These authorities often start from medical understandings of disability, which may clash with contemporary understandings of disability as being environmentally based. The fourth study is a statistical analysis of the effects of different disability definitions on dependent variables. The analyses emphasize variables often included in studies of living conditions. There are major effects of choice of disability definition on the outcome in relation to such variables. The dissertation strongly rejects efforts to standardize disability definitions; different analytical purposes require different kinds of conceptualizations. Instead, the dissertation suggests that case-constructing reflexivity be conducted. Case-constructing reflexivity means that the researcher starts with a careful analysis of how disability is best defined in relation to the aims of the study, and continues by being constantly aware of how the choice of definition may affect sampling, analyses and results.

In this thesis, we wanted to stress the tendency to the geometry of data. This should be applicable in almost every branch of science, where data are of great importance, and also in every kind of industry, economy, medicine etc. Since machine&#039 / s hard-disk capacities which is used for storing datas and the amount of data you can reach through internet is increasing day by day, there should be a need to turn this information into knowledge. This is one of the reasons for studying formal concept analysis. We wanted to point out how this application is related with algebra and logic. The beginning of the first chapter emphasis the relation between closure systems, galois connections, lattice theory as a mathematical structure and concept analysis. Then it describes the basic step in the formalization: An elementary form of the representation of data is defined mathematically. Second chapter explains the logic of formal concept analysis. It also shows how implications, which can be regard as special formulas on a set,between attributes can be shown by fewer implications, so called generating set for implications. These mathematical tools are then used in the last chapter, in order to describe complex &#039 / concept&#039 / lattices by means of decomposition methods in examples.

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Knowledge is a critical dimension in the problem solving processes of human intelligence. Consequently, enabling intelligent systems to provide advanced services requires that their artificial intelligence routines have access to knowledge of relevant domains. Ontologies are often utilised as the formal conceptualisation of domains, in that they identify and model the concepts and relationships of the targeted domain. However complexities inherent in ontology development and maintenance have limited their availability. Separate from the conceptualisation component, domain knowledge also encompasses the concept membership of object instances within the domain. The need to capture both the domain model and the current state of instances within the domain has motivated the import of Formal Concept Analysis into intelligent systems research. Formal Concept Analysis, which provides a simplified model of a domain, has the advantage in that not only does it define concepts in terms of their attribute description but object instances are simultaneously ascribed to their appropriate concepts. Nonetheless, a significant drawback of Formal Concept Analysis is that when applied to a large dataset, the lattice with which it models a domain is often composed of a copious amount of concepts, many of which are arguably unnecessary or invalid. In this research a novel measure is introduced which assigns a relevance value to concepts in the lattice. This measure is termed the Collapse Index and is based on the minimum number of object instances that need be removed from a domain in order for a concept to be expunged from the lattice. Mathematics that underpin its origin and behaviour are detailed in the thesis showing that if the relevance of a concept is defined by the Collapse Index: a concept will eventually lose relevance if one of its immediate subconcepts increasingly acquires object instance support; and a concept has its highest relevance when its immediate subconcepts have equal or near equal object instance support. In addition, experimental evaluation is provided where the Collapse Index demonstrated comparable or better performance than the current prominent alternatives in: being consistent across samples; the ability to recall concepts in noisy lattices; and efficiency of calculation. It is also demonstrated that the Collapse Index affords concepts with low object instance support the opportunity to have a higher relevance than those of high supportThe second contribution to knowledge is that of an approach to semantic extraction from a dataset where the Collapse Index is included as a method of selecting concepts for inclusion in a final concept hierarchy. The utility of the approach is demonstrated by reviewing its inclusion in the implementation of a recommender system. This recommender system serves as the final contribution featuring a unique design where lattices represent user profiles and concepts in these profiles are pruned using the Collapse Index. Results showed that pruning of profile lattices enabled by the Collapse Index improved the success levels of movie recommendations if the appropriate thresholds are set.

The objective of this study was to analyse the central concepts of radiography and connections between them, assumed to define the focus of the radiography science. The objective was also to define these concepts theoretically, and to formulate a model defining the focus of radiography science. Radiography refers here to radiographers' professional work, education and radiography science. The concepts of nursing, environment, health and human being were used as starting point for the study, as they are commonly applied, but not clearly defined in radiography. The study was conducted in three phases in accordance with the hybrid method of concept analysis. During the theoretical phase, the theoretical phase model and tentative definitions were developed on the grounds of literature. These were further developed during the empirical phase, as the empirical phase model was formulated on the grounds of empirical data. Data were collected in the form of interviews and written material from selected experts (n = 8). In the analytical phase, theoretical definitions and the model of the focus of radiography science were formulated as a synthesis of the results of former phases. The total number of data was 1,147 pages, and it was analysed with the method of qualitative content analysis. Based on the results, the concept of nursing was substituted with the concept of clinical radiography and radiotherapy, which was defined as radiographer's work within health care. Seamless combination of patient care and service as well as technical usage of radiation and radiation protection was found to be the core of a radiographer's work, aimed at serving the health care field as part of a multiprofessional teamwork. Essential characteristics of the work were found to be theoretical and practical-technical expertise, guiding elements, implementation as a process, and responsibility for safety as well as optimizing decision-making. Environment was defined as the physical and functional environment in health care, cultural environment, cognitive environment, and context of a radiographer's expertise. The concept of health was substituted with the concept of health and illness, which was defined as a holistic and variable state of being that is indirectly affected by radiation. A human being was defined as a dignified individual or community, which is also a holistic and variable being. Connections were found to be positive, negative, characterizing, directing, functional and experimental by nature. On the basis of the results, radiography science could be named the clinical science of radiography and radiotherapy. The model formulated in this study describes the focus of the clinical science of radiography and radiotherapy on a general level. The results may be exploited in the development of the clinical science of radiography and radiotherapy, in theory development and in education within radiography. They may also clarify the identity of this science and understanding regarding it. / Tiivistelmä Tutkimuksen tarkoituksena oli analysoida radiografian keskeisiä käsitteitä ja niiden välisiä yhteyksiä, joiden voidaan olettaa määrittävän radiografiatieteen tutkimuskohdetta. Tarkoituksena oli määritellä käsitteet teoreettisesti sekä muodostaa käsitteiden ja niiden välisten yhteyksien perusteella malli radiografiatieteen tutkimuskohteesta. Radiografialla tarkoitetaan tässä tutkimuksessa röntgenhoitajan työtä ja koulutusta sekä radiografiatiedettä. Lähtökohtana käytettiin hoitotieteen käsitteitä hoitotyö, ympäristö, terveys ja ihminen, joita on radiografiassa käytetty ja sovellettu, mutta ei täsmällisesti määritelty. Tutkimus toteutettiin kolmivaiheisesti hybridisen käsiteanalyysimenetelmän mukaan. Teoreettisessa vaiheessa muodostettiin kirjallisuuden perusteella käsitteiden työmääritelmät ja teoreettisen vaiheen malli. Empiirisessä vaiheessa muodostettiin empiirisen vaiheen malli asiantuntijoilta (n = 8) kerätyn kirjallisen ja haastatteluaineiston perusteella. Analyyttisessä vaiheessa muodostettiin tulosten systemaattiseen vertailuun perustuvana synteesinä käsitteiden teoreettiset määritelmät ja malli radiografiatieteen tutkimuskohteesta. Aineiston kokonaismäärä oli 1147 sivua, ja se analysoitiin laadullisella sisällönanalyysillä. Tutkimuksen tuloksena hoitotyö-käsite korvattiin käsitteellä kliininen röntgenhoitajan työ. Se määriteltiin röntgenhoitajan terveydenhuollossa toteuttamaksi työksi, jonka ydin on teknisen säteilynkäytön ja säteilysuojelun sekä potilaan hoidon ja palvelun saumaton yhdistäminen. Ytimen avulla työ palvelee terveydenhuollon toimintaympäristöä osana moniammatillista tiimityötä. Työn keskeiset ominaisuudet ovat teoreettinen ja käytännöllis-tekninen asiantuntijuus, ohjaavat tekijät, prosessimaisuus sekä turvallisuusvastuu ja optimoiva päätöksenteko. Ympäristö määriteltiin fyysiseksi terveydenhuollon toimintaympäristöksi, kulttuuriympäristöksi, kognitiiviseksi ympäristöksi ja röntgenhoitajan asiantuntijuuden muodostamaksi ympäristöksi. Terveys-käsite korvattiin käsitteellä terveys ja sairaus, joka määriteltiin kokonaisvaltaiseksi ilmiöksi ja muuttuvaksi tilaksi, jonka kannalta keskeisiä ovat säteilyn välilliset vaikutukset. Ihminen määriteltiin arvokkaaksi yksilöksi tai yhteisöksi, joka on kokonaisvaltainen ja muuttuva olento. Käsitteiden väliset yhteydet voivat olla positiivisia, negatiivisia, luonnehtivia ja ohjaavia yhteyksiä sekä tekemis- ja kokemisyhteyksiä. Tulosten perusteella radiografiatieteen nimeksi sopisi kliininen radiografiatiede. Tutkimuksessa tuotettu malli määrittää kliinisen radiografiatieteen tutkimuskohdetta yleisluontoisesti. Tuloksia voidaan hyödyntää lähinnä kliinisen radiografiatieteen kehittämisessä, teorianmuodostuksessa ja radiografian koulutuksessa. Tulokset voivat myös auttaa selkeyttämään kliinisen radiografiatieteen identiteettiä ja lisäämään sitä koskevaa ymmärrystä.

A consumer health decision support system (CDSS) is being developed at the South African Medical Research Council (MRC). It is a software program intended to help members of the public decide when they may be at risk of some common but serious illnesses like tuberculosis and hypertension. It would be ideal for a public health kiosk or e-health programs of the government. The program has been built as an expert system. Its knowledge base consists of rules which are used in assessing the risk of illness. The rules were given by medical experts who took part in the development of the CDSS. The study proposes a method for the evaluation of the rule base of the CDSS using FCA methods. It is important to evaluate the knowledge base of an expert system, because if its knowledge base is of broad scope and is accurate then it can be expected that the expert system will be good at giving advice and hence potentially useful. FCA is a mathematical framework which can be used to investigate causal relations in data. The study explored its utility in the evaluation of the CDSS knowledge base. FCA implications and the FCA formulation of the JSM method were two FCA methods that were selected. The FCA methods were used to generate rules from actual patient data, and these were compared to the rules initially given by the experts. The motivation to use FCA data analysis as well as experts’ knowledge in the development of the CDSS program is that FCA data analysis may discover some things that the experts may have overlooked. Or at least the experts can review their expertise against actual field data which has been analysed by FCA methods. A system like the CDSS cannot be built using FCA data analysis techniques only, involvement of experts is very important. The two FCA methods were chosen so as to compare their results, and it was also thought that they may perhaps complement each other. Preliminarily it was found that FCA implications and the FCA formulation of the JSM method can be used in the evaluation of the rule base of the CDSS. / Dissertation (MSc (Computer Science))--University of Pretoria, 2008. / Computer Science / unrestricted

Purpose: Post-COVID-19 workforce issues have pushed terms like resilience and burnout further into the forefront of professional discourse. Strategies aimed to improve resilience, decrease burnout, and increase retention appear to be less effective in the current climate. One potential unexplored contributor is toxic positivity. The purpose of this research is to analyze the concept of toxic positivity and its relevance to nursing. Aims: Research questions; “1) How is toxic positivity used across contexts?; 2) Whose perspectives are represented and whose are not?; 3) What are the dimensions of toxic positivity?; 4) How are the dimensions related?; and 5) How is toxic positivity constructed and used in nursing? Methods: Using Schatzman’s dimensional analysis approach, the first analytic phase, Identification, elucidates relevant conceptual dimensions. The second analytic phase, Logistics, examines relationships among dimensions and contexts. Finally, a dimensional matrix provides conceptualization of toxic positivity for nursing. Results: Preliminary results reveal roots of toxic positivity in the realm of positive psychology with relevant dimensions including unrealistic optimism, inauthentic platitudes, and emotional invalidation and identified contexts including business, psychology, and medicine with no identified contexts in nursing. Primary limitations include limited time to complete this analysis, lack of empirical evidence regarding toxic positivity, and the potential for other unrealized dimensions or contexts. Conclusions: Results suggest nursing perspectives are missing from the literature about toxic positivity. Identifying toxic positivity as a phenomenon in nursing work environments has potential to inform future research and theoretical work related to nursing workforce burnout, retention, and coping strategies.

Bodies or Books of Knowledge (BoKs) have only been transcribed in mature fields where practices and rules have been well established (settled) and are gathered for any prospective or current practitioner to refer to. As a precursor to creating a BoK, it is first important to know if the domain contains settled knowledge and how this knowledge can be isolated? One approach, as described in this work, is to use Formal Concept Analysis (FCA) to structure the knowledge (or parts of it) and construct a pruned concept lattice to highlight patterns of use and filter out the common and established practices that best suit the solving of a problem within the domain. In the railway domain, formal methods have been applied for a number of years to solve various modelling and verification problems. Their common use and straightforward application (with some refinement) makes them easy to identify and therefore a prime candidate to test for settled knowledge within the railway domain. They also provide other assurances of settled knowledge along the way. / Thesis / Master of Applied Science (MASc)

No description available.

Functional genetics is the study of the genes present in a genome of an organism, the complex interplay of all genes and their environment being the primary focus of study. The motivation for such studies is the premise that gene expression patterns in a cell are characteristic of its current state. The availability of the entire genome for many organisms now allows scientists unparalleled opportunities to characterize, classify, and manipulate genes or gene networks involved in metabolism, cellular differentiation, development, and disease. System-wide studies of biological systems have been made possible by the advent of high-throughput and large-scale tools such as microarrays which are capable of measuring the mRNA levels of all genes in a genome. Tools and methods for the integration, visualization, and modeling of the large-scale data obtained in typical systems biology experiments are indispensable. Our work focuses on a method that integrates gene expression values obtained from microarray experiments with biological functional information related to the genes measured in order to make global comparisons of multiple experiments. In our method, the integrated data is represented as a lattice and, using appropriate measures, a reference experiment can be compared to samples from a database of similar experiments, and a ranking of similarity is returned. In this work, support for the validity of our method is demonstrated both theoretically and empirically: a mathematical description of the lattice structure with respect to the integrated information is developed and the method is applied to data sets of both simulated and reported microarray experiments. A fast algorithm for constructing the lattice representation is also developed. / Ph. D.