Social work is a social phenomenon, existing in most societies, that has given rise to a multitude of special organizations and professions. For that reason social work is dealing with a complex identity. The purpose of this study is to illustrate how social workers and the scientific discourse interpret the concept of social work. In addition to that the study intends to show similarities and differencies. The research process containes two studies, one based on qualitative interviews with five social workers and the other consisting a surway of academic litterature. To enable a comparison of the results the studies start out of some, deliberatly choosen, themes. These are “definitions of social work”, “socialworkers”, “society, law and organization” and “ethics”. In summary, the results, reviled a surprising unity in the interpretations of social work. Social workers, as well as the scientific discourse, manifest social work as a profession that promotes social change and problem solving in human relationships. The differencies concern social work beeing interpret normative by the social workers and more descriptive by the scientific discourse.

Architecture, Engineering, Construction (AEC) and Facilities Management (FM) involve domains that require a very diverse set of information and model exchanges to fully realize the potential of Building Information Modeling (BIM). Industry Foundation Classes (IFC) provides a neutral and open schema for interoperability. Model View Definitions (MVD) provide a common subset for specifying the exchanges using IFC, but are expensive to build, test and maintain. A semantic analysis of IFC data schema illustrates the complexities of embedding semantics in model views. A software engineering methodology based on formal specification of shared resources, reusable components and standards that are applicable to the AEC-FM industry for development of a Semantic Exchange Module (SEM) structure for IFC schema is adopted for this research. This SEM structure is based on engineering ontologies that are capable of developing more consistent MVDs. In this regard, Ontology is considered as a machine-readable set of definitions that create a taxonomy of classes and subclasses, and relationships between them. Typically, the ontology contains the hierarchical description of important entities that are used in IFC, along with their properties and business rules. This model of an ontological framework, similar to that of Semantic Web, makes the IFC more formal and consistent as it is capable of providing precise definition of terms and vocabulary. The outcome of this research, a formal classification structure for IFC implementations for the domain of Precast/ Prestressed Concrete Industry, when implemented by software developers, provides the mechanism for applications such as modular MVDs, smart and complex querying of product models, and transaction based services, based on the idea of testable and reusable SEMs. It can be extended and also helps in consistent implementation of rule languages across different domains within AEC-FM, making data sharing across applications simpler with limited rework. This research is expected to impact the overall interoperability of applications in the BIM realm.

Magistro darbo objektas – poezijos refleksija, atsiskleidžianti trijuose Alfonso Nykos-Niliūno „Dienoraščio fragmentų“ tomuose. Analizuojant dienoraščius pastebima, jog toji refleksija labai svarbi ir aktuali poeto pasaulėžiūros, jo poezijos (auto)suvokimui. Nykos-Niliūno kūrybą, jo dienoraščius lydi labai dinamiška, įvairiausius analizės aspektus ir metodus aktualizavusi kritika, tačiau daugelyje darbų siekiama atskleisti poetinio teksto esmę, jo giluminius klodus, bet nebandoma atsakyti į klausimą, kas poezija apskritai yra Nykai Niliūnui. Todėl darbo naujumą, jo reikšmę nulemia tai, kad niekas Nykos-Niliūno poezijos refleksijos atskirai neanalizavo. Pagrindinės darbe tiriamos problemos yra kelios: kokia yra/galėtų būti bendroji poezijos samprata, ar Nyka-Niliūnas prie jos priartėja, ar nutolsta; kokią poezijos sampratą poetas pateikia savo dienoraščiuose, kokie poezijos vertės kriterijai juose aptinkami; kaip kinta poezijos suvokimas ir vertinimas, kokie veiksniai tai lemia. Darbo tikslas – analitiniu aprašomuoju metodu analizuojant dienoraščiuose aptinkamas poezijos refleksijas, atskleisti Nykos-Niliūno poezijos sampratą bei išsiaiškinti, kokiais kriterijais vadovaujantis nustatoma poetinio teksto vertė. Siekiant šio tikslo, darbe aktualizuojamas poezijos neapibrėžiamumo aspektas ir keliami tokie darbo uždaviniai: (a) išsiaiškinti, kaip dienoraščiuose Nyka Niliūnas apibrėžia, kas yra poezija; (b) remiantis pavyzdžiais iš dienoraščių, nustatyti, kokiais vertinimo... [toliau žr. visą tekstą] / The object of this master’s thesis – poetry reflection which unfolds in three volumes of “The Diary Fragments” by Alfonsas Nyka-Niliūnas. Having analysed the diaries it was noted that the reflection is important and relevant for the understanding of the poet’s perception of world and his poetry. The creative work and the diaries of Nyka-Niliūnas are followed by criticism that is dynamic and actualising various aspects and approaches of analysis. However, most of the works are attempts to reveal the essence of the poetic text, its deep layers, but they do not aim to answer the question of what does poetry mean for Nyka-Niliūnas in general. Therefore, the novelty of the thesis, its significance is determined by the fact that there has not been any separate analysis of Nyka-Niliūnas poetry reflection. The main problems being developed in the present thesis are the following: what is/could be the common conception of poetry, does Nyka-Niliūnas approach it or recede from it; what conception of poetry does the poet have in his diaries, what criteria of value of poetry are found in the diaries; how do perception and evaluation of poetry change, and what factors determine it. The aim of the thesis – using a descriptive analytical method and analysing poetry reflection in the diaries, to reveal Nyka-Niliūnas conception of poetry, and to clarify the criteria for determining the value of the poetic text. To achieve the aim, the aspect of poetry indeterminacy is actualised in the thesis... [to full text]

Background Ontologies play a major role in life sciences, enabling a number of applications, from new data integration to knowledge verification. SNOMED CT is a large medical ontology that is formally defined so that it ensures global consistency and support of complex reasoning tasks. Most biomedical ontologies and taxonomies on the other hand define concepts only textually, without the use of logic. Here, we investigate how to automatically generate formal concept definitions from textual ones. We develop a method that uses machine learning in combination with several types of lexical and semantic features and outputs formal definitions that follow the structure of SNOMED CT concept definitions. Results We evaluate our method on three benchmarks and test both the underlying relation extraction component as well as the overall quality of output concept definitions. In addition, we provide an analysis on the following aspects: (1) How do definitions mined from the Web and literature differ from the ones mined from manually created definitions, e.g., MeSH? (2) How do different feature representations, e.g., the restrictions of relations’ domain and range, impact on the generated definition quality?, (3) How do different machine learning algorithms compare to each other for the task of formal definition generation?, and, (4) What is the influence of the learning data size to the task? We discuss all of these settings in detail and show that the suggested approach can achieve success rates of over 90%. In addition, the results show that the choice of corpora, lexical features, learning algorithm and data size do not impact the performance as strongly as semantic types do. Semantic types limit the domain and range of a predicted relation, and as long as relations’ domain and range pairs do not overlap, this information is most valuable in formalizing textual definitions. Conclusions The analysis presented in this manuscript implies that automated methods can provide a valuable contribution to the formalization of biomedical knowledge, thus paving the way for future applications that go beyond retrieval and into complex reasoning. The method is implemented and accessible to the public from: https://github.com/alifahsyamsiyah/learningDL.

Research about what differences and similarities exists between UNHCR and UNRWA in the opinion of a refugee? This examination focuses on a study between The United Nations High Commissioner for Refugees (UNHCR) and THE United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA). Both organizations are UN-related and are in charge of refugees, however they differ by the fact the UNHCR controls all of the world’s refugees with the exception of the Palestinian refugees, for which UNRWA. The aim of this work will be to examine the definition of refugees as well as their entitlements and in what way they differ depending on which organization they belong to. As theory I have, among others, used Rainer Bauböck’s book ” Transnational Citizenship”. In his writing he focuses on entitlements and this book became very useful in my work and helped with the structure of the paper. In conclusion, even though there is some resemblance in the aspect of a refugee’s entitlements, there are a lot of differences between UNHCR and UNRWA, mainly regarding the definition of a refugee but also in terms of assignments. What’s most noticeable when it comes to differences between these two organs is that UNHCR has mandate to assist with international protection and to seek permanent solutions for refugees. The mandate of UNRWA is limited to only assist Palestinian refugees with humanitarian assistance. UNRWA has been criticized to contribute directly to Palestinian dreams of return instead of accepting incorporation of refugees in neigbouring Arab countries.

This report works with a case provided in the course IS/IT for Organizing, Communication and Coordination II at Linnaeus University, Sweden. The case involves a University in North America that is renovating and revamping and, in essence, reinventing its library along with the services offered by the library and the facilities within. Along with the university staff in charge of the library renovations, the group analysed the possible gaps in the current working ecosystem and discussed how they can be improved upon. It was found out and understood that there is a lack of cohesion in the way the library staff generate, store and share documents and resources, which was intertwined with the lack of team culture and sense of professional community. Useful information was said to be in silos in the form of staff members that were somewhat disconnected from each other. This information was often in the form of explicit knowledge that was not easily accessible and tacit knowledge that was, in a sense, locked away since it was involuntarily not being shared. The group preparing this report used the theoretical background of knowledge management and knowledge sharing, along with a Soft Systems Methodology approach, to provide recommendations that the professionals in charge of the library renovations could execute upon during their plans. The recommendations revolve around organizing the organizational knowledge and bringing more cohesiveness to the way the staff and systems generate, store and share this knowledge, leading the way towards a knowledge-friendly culture. The proposed solutions elaborated by the group take Nonaka’s two types of knowledge (1994) into consideration: explicit and tacit knowledge. The recommendations begin with organizing the knowledge with aims of easier retrieval by users, using Shared Folder platforms or Content Management Systems. The active creation and sharing of knowledge shall be supported using blogs, wikis and e-learning authoring systems. Sharing of tacit knowledge can be enhanced by a Yellow Pages of the library staff, Community of Practice and through mentoring and networking activities. / <p>Rapport inom Informatikskurs 5IK501 IS/IT for Organizing, Communicating, and Coordinating II, läsåret 2016/2017</p><p>Report in the Informatics course 5IK501 IS/IT for Organizing, Communicating, and Coordinating II, year 2016/2017</p>

The essay begins by asserting that the theoretical approaches of men’s violence against women are just as important to study as its extent. The purpose is therefore to analyse and compare two theoretical approaches which is done by a comparative text analysis of two texts written on the subject. The essay attempts to answer two questions; what the theoretical approaches are and how they can be understood in light of feminist theory. Previous research on men’s violence against women discuss especially three theoretical aspects. These are how the concept is defined, if the different forms of violence are being treated separately or not, and how it is explained. These aspects are used as the basis for the analysis which is conducted in two steps. The result shows that the theoretical approaches analysed share many similarities with both each other and the feminist theory. All apply a broad definition, hold the different forms of violence together, and consider the most basic explanation for the violence to be the unequal power structure between the sexes. The biggest difference between the two theoretical approaches and the feminist theory is that the former also emphasizes other explanatory levels as well as the purely structural.

Masters of Art / This project suggested that HIV people in Region A (Nelson Mandela Metropole, formerly Port Elizabeth) health district of the Eastern Cape, seek HIV testing when they are already in stages three (late disease) and four (AIDS) of HIV infection. Data had been obtained from the AIDS Training Information and Counselling Centre in the Nelson Mandela Metropole in 2000. The consequences of diagnoses only in the advanced stages of HIV infection will have a devastating impact on case management. Therefore, this paper yielded important data for South African policy makers to write health and welfare policies that might improve the quality of life of those terminally infected with HIV. / South Africa

BACKGROUND: Ontologies play a major role in life sciences, enabling a number of applications, from new data integration to knowledge verification. SNOMED CT is a large medical ontology that is formally defined so that it ensures global consistency and support of complex reasoning tasks. Most biomedical ontologies and taxonomies on the other hand define concepts only textually, without the use of logic. Here, we investigate how to automatically generate formal concept definitions from textual ones. We develop a method that uses machine learning in combination with several types of lexical and semantic features and outputs formal definitions that follow the structure of SNOMED CT concept definitions. RESULTS: We evaluate our method on three benchmarks and test both the underlying relation extraction component as well as the overall quality of output concept definitions. In addition, we provide an analysis on the following aspects: (1) How do definitions mined from the Web and literature differ from the ones mined from manually created definitions, e.g., MeSH? (2) How do different feature representations, e.g., the restrictions of relations' domain and range, impact on the generated definition quality?, (3) How do different machine learning algorithms compare to each other for the task of formal definition generation?, and, (4) What is the influence of the learning data size to the task? We discuss all of these settings in detail and show that the suggested approach can achieve success rates of over 90%. In addition, the results show that the choice of corpora, lexical features, learning algorithm and data size do not impact the performance as strongly as semantic types do. Semantic types limit the domain and range of a predicted relation, and as long as relations' domain and range pairs do not overlap, this information is most valuable in formalizing textual definitions. CONCLUSIONS: The analysis presented in this manuscript implies that automated methods can provide a valuable contribution to the formalization of biomedical knowledge, thus paving the way for future applications that go beyond retrieval and into complex reasoning. The method is implemented and accessible to the public from: https://github.com/alifahsyamsiyah/learningDL.

Background Ontologies play a major role in life sciences, enabling a number of applications, from new data integration to knowledge verification. SNOMED CT is a large medical ontology that is formally defined so that it ensures global consistency and support of complex reasoning tasks. Most biomedical ontologies and taxonomies on the other hand define concepts only textually, without the use of logic. Here, we investigate how to automatically generate formal concept definitions from textual ones. We develop a method that uses machine learning in combination with several types of lexical and semantic features and outputs formal definitions that follow the structure of SNOMED CT concept definitions. Results We evaluate our method on three benchmarks and test both the underlying relation extraction component as well as the overall quality of output concept definitions. In addition, we provide an analysis on the following aspects: (1) How do definitions mined from the Web and literature differ from the ones mined from manually created definitions, e.g., MeSH? (2) How do different feature representations, e.g., the restrictions of relations’ domain and range, impact on the generated definition quality?, (3) How do different machine learning algorithms compare to each other for the task of formal definition generation?, and, (4) What is the influence of the learning data size to the task? We discuss all of these settings in detail and show that the suggested approach can achieve success rates of over 90%. In addition, the results show that the choice of corpora, lexical features, learning algorithm and data size do not impact the performance as strongly as semantic types do. Semantic types limit the domain and range of a predicted relation, and as long as relations’ domain and range pairs do not overlap, this information is most valuable in formalizing textual definitions. Conclusions The analysis presented in this manuscript implies that automated methods can provide a valuable contribution to the formalization of biomedical knowledge, thus paving the way for future applications that go beyond retrieval and into complex reasoning. The method is implemented and accessible to the public from: https://github.com/alifahsyamsiyah/learningDL.