Music is widely used to accompany moving images, in films, advertising, television programmes and computer games. The process of choosing and using a piece of pre-existing commercial music for this purpose is known as synchronisation. The addition of music to a piece of film enhances the final work with cultural meaning, and generates additional income for the rights holders. This research examines the information needs of professionals involved in the selection of music, including Users from the advertising and film communities and Owners from the recording and publishing industries. A tentative communications model is developed and proposed from musicological, semiotic and communications literature. Interviews, knowledge organisation systems, queries and observations are identified as rich potential sources of textual data relating to the communications process around satisfying the Users’ information needs. The content of these texts is analysed to identify key musical facets. Mood is found to be an important factor when searching for unknown musical items. Using a Discourse Analytic approach to the interview texts, four discourses, or interpretive repertoires, are identified. These repertoires carry conflicting meanings of music and are employed throughout the community, although relative emphases vary according to the viewpoint of the stakeholder. This is supported by an analysis of the written texts of both the Owners (music search engines) and the Users (written queries, or briefs). A comparison is drawn between the emphasis of the repertoires and the precision of the search engines. The repertoires are applied to the theoretical communications model, which is revised to reflect the findings of the analyses. This is used to make recommendations on how to improve the disintermediated communications process, by emphasising the repertoires employed by the Users rather than those of the Owners.

This report presents research and development of dedicated system architecture, designed to enable its users to interact with each other as well as to access information on Points of Interest that exist in their immediate environment. This is accomplished through managing personal preferences and contextual information in a distributed manner and in real-time. The advantage of this system architecture is that it uses mobile devices, heterogeneous sensors and a selection of user interface paradigms to produce a sociotechnical framework to enhance the perception of the environment and promote intuitive interactions. The thrust of the work has been on software development and component integration. Iterative prototyping was adopted as a development method in order to effectively implement the users’ feedback and establish a platform for collaboration that closely meets the requirements and aids their decision-making process. The requirement acquisition was followed by the system-modelling phase in order to produce a robust software prototype. The implementation includes component-based development and extensive use of design patterns over native programming. Conclusively, the software product has become the means to evaluate differences in the use of mixed reality technologies in a ubiquitous scenario. The prototype can query a number of context sources such as sensors, or details of the personal profile, to acquire relevant data. The data (and metadata) is stored in opensource structures, so that they are accessible at every layer of the system architecture and at any time. By proactively processing the acquired context, the system can assist the users in their tasks (e.g. navigation) without explicit input – e.g. by simply creating a gesture with the device. However, advanced interaction with the application via the user interface is available for requests that are more complex. Representations of the real world objects, their spatial relations and other captured features of interest are visualised on scalable interfaces, ranging from 2D to 3D models and from photorealism to stylised clues and symbols. Two principal modes of operation have been implemented; one, using geo-referenced virtual reality models of the environment, updated in real time, and second, using the overlay of descriptive annotations and graphics on the video images of the surroundings, captured by a video camera. The latter is referred to as augmented reality. The continuous feed of the device position and orientation data, from the GPS receiver and the digital compass, into the application, makes the framework fit for use in unknown environments and therefore suitable for ubiquitous operation. This is one of the novelties of the proposed framework, because it enables a whole range of social, peer-to-peer interactions to take place. The scenarios of how the system could be employed to pursue these remote interactions and collaborative efforts on mobile devices are addressed in the context of urban navigation. The conceptual design and implementation of the novel location and orientation based algorithm for mobile AR are presented in detail. The system is, however, multifaceted and capable of supporting peer-to-peer exchange of information in a pervasive fashion, usable in various contexts. The modalities of these interactions are explored and laid out in several scenarios, but particularly in the context of user adoption. Two evaluation tasks took place. The preliminary evaluation examined certain aspects that influence user interaction while being immersed in a virtual environment, whereas the second summative evaluation compared the utility and certain usability aspects of the AR and VR interfaces.

Saudi Arabia is struggling to provide quality healthcare services in light of the growing population, rapid spread of chronic diseases, and limited resources available. In addition to these obstacles, the Saudi society is a highly conservative one, and certain traditions may sometimes limit how healthcare services can be offered. This work examines the impact of a Telecare solution on the healthcare system at the National Guard Health Affairs (NGHA). It focuses on diabetes, and the challenges faced by both the healthcare officials at NGHA, and the patients. These challenges also include social factors that may pose at obstacle in delivering healthcare services. The ‘Telecare for Managing Diabetes – TeMaD’ system is designed and developed using the Soft Systems Methodology. It was then integrated into the hospital information systems at King Abdulaziz Medical City in the Central Region, and consisted of 52 participating patients, and four involved Diabetic Educators. HbA1c levels of all patients were recorded prior to commencement of the study. Patients were required to use TeMaD for a 3-month period, then, had their HbA1c levels recorded again after completion of the study. Overall observation of the results showed a reduction in the HbA1c levels of 83% of the patients. Participating patients expressed their acceptance of the system, indicating that TeMaD allowed them to overcome some obstacles such as lack of transportation. It also assisted the majority of participants to better manage their diabetes and ease communication with their diabetic educators. Most patients requested that the system be offered permanently at the clinic. Diabetic educators were in favour of integrating TeMaD into the current healthcare system at NGHA, and they were enthusiastic about its numerous benefits. Telecare solutions can be used to enhance the quality of healthcare services, meet current demands, and address obstacles faced by the healthcare system in Saudi Arabia, including social factors that are unique. They can be adopted by neighbouring Gulf States which share common obstacles in healthcare.

No description available.

Background: Controlled vocabularies in the molecular biology domain exist to facilitate data integration across database resources. One such tool is the Gene Ontology (GO), a classification designed to act as a universal index for gene products from any species. The Gene Ontology is used extensively in annotating gene products and analysing gene expression data, yet very little research exists from a library and information science perspective exploring the design principles, philosophy and social role of ontologies in biology. Aim: To explore how molecular biologists, in creating the Gene Ontology, devised guidelines and rules for determining which scientific concepts are included in the ontology, and the criteria for how these concepts are represented. Methods: A domain analysis approach was used to devise a mixed methodology to study the design of the Gene Ontology. Concept analysis of a GO term and a critical discourse analysis of GO developer mailing list texts were used to test whether ontological realism is a tenable basis for constructing objective ontologies. A comparison of the current GO vocabulary construction guidelines and a study of the reasons why GO terms are removed from the ontology further explored the justifications for the design of the Gene Ontology. Finally, a content analysis of published GO papers examined how authors use and cite GO data and terminology. Results: Gene Ontology terms can be presented according to different epistemologies for concepts, indicating that ontological realism is not the only way objective ontologies can be designed. Social roles and the exercise of power were found to play an important role in determining ontology content, and poor synonym control, a lack of clear warrant for deciding terminology and arbitrary decisions to delete and invent new terms undermine the objectivity and universal applicability of the Gene Ontology. Authors exhibited poor compliance with GO data citation policies, and in re-wording and misquoting GO terminology, risk exacerbating the semantic problems this controlled vocabulary was designed to solve. Conclusions: The failure of the Gene Ontology to define what is meant by a molecular function, the exercise of power by GO developers in clearing contentious concepts from the ontology, and the strict adherence to ontological realism, which marginalises social and subjective ways of classifying scientific concepts, limits the utility of the ontology as a tool to unify the molecular biology domain. These limitations to the Gene Ontology design could be overcome with the development of lighter, pluralistic, user-controlled ‘open ontologies’ for gene products that can work alongside more traditional, ‘top-down’ developed vocabularies.

Thesis (Master's)--Karachi University, 2003. / Includes bibliographical references (p. 108-115).

Thesis (Ph.D.)--University of California, Los Angeles, 2007. / (UMI)AAI3272325. Source: Dissertation Abstracts International, Volume: 68-07, Section: A, page: 2705. Adviser: Anne Gilliland.

Thesis (Master's)--Karachi University, 2003. / Includes bibliographical references (p. 108-115).

Oral administration is the most common route for administration of drugs. With the growing cost of drug discovery, the development of Quantitative Structure-Activity Relationships (QSAR) as computational methods to predict oral absorption is highly desirable for cost effective reasons. The aim of this research was to develop QSAR models that are highly accurate and interpretable for the prediction of oral absorption. In this investigation the problems addressed were datasets with unbalanced class distributions, feature selection and the effects of solubility and permeability towards oral absorption prediction. Firstly, oral absorption models were obtained by overcoming the problem of unbalanced class distributions in datasets using two techniques, under-sampling of compounds belonging to the majority class and the use of different misclassification costs for different types of misclassifications. Using these methods, models with higher accuracy were produced using regression and linear/non-linear classification techniques. Secondly, the use of several pre-processing feature selection methods in tandem with decision tree classification analysis – including misclassification costs – were found to produce models with better interpretability and higher predictive accuracy. These methods were successful to select the most important molecular descriptors and to overcome the problem of unbalanced classes. Thirdly, the roles of solubility and permeability in oral absorption were also investigated. This involved expansion of oral absorption datasets and collection of in vitro and aqueous solubility data. This work found that the inclusion of predicted and experimental solubility in permeability models can improve model accuracy. However, the impact of solubility on oral absorption prediction was not as influential as expected. Finally, predictive models of permeability and solubility were built to predict a provisional Biopharmaceutic Classification System (BCS) class using two multi-label classification techniques, binary relevance and classifier chain. The classifier chain method was shown to have higher predictive accuracy by using predicted solubility as a molecular descriptor for permeability models, and hence better final provisional BCS prediction. Overall, this research has resulted in predictive and interpretable models that could be useful in a drug discovery context.

High-impact academic papers are not necessarily the most cited. For example, Einstein's 'Special Relativity' paper from 1905 received (and continues to receive) fewer citations from other papers than his 'Brownian Motion" paper of the same year, despite the former radically changing the course of an entire scientific discipline to a much greater extent. Similarly, 'impact' metrics using citation count alone are, it is argued, not adequate for determining the scientific influence of papers, authors or small groups of authors. Although valid, they remain controversial when used to determine influence of larger groups or journals. While the term 'impact' has become closely linked to a journal's citation-based Journal Impact Factor score, this thesis uses the term 'influence' to describe the wider effectiveness of research, combining citation and metadata analysis to allow richer calculations to be performed over large-scale document networks. As a result, more qualitative influence ratings can be determined and a broader outlook on scientific disciplines can be produced. These ratings are best applied using an ontology-based data source, allowing more efficient inference than under a traditional RDBMS system, and allowing easier integration between heterogeneous data sources. These metrics, termed 'Semantic Bibliometrics' or 'Semiometrics', can be applied at a variety of levels of granularity, allowing a compositional framework for impact and influence analysis. This thesis describes the process of data preparation, systems architecture, metric value and data integration for such a system, introducing novel approaches at all four stages, thereby creating a working semiometrics system for determining influence at different semantic levels of granularity.