Vocal fold vibration results from an alternating balance between subglottal air pressure that drives the vocal folds apart and muscular, elastic, and restoring forces that draw them together. The aim of the present thesis is to present quantitative data of normal vocal function using a noninvasive method. Measurements are made on the inverse filtered airflow waveform, of estimated average trans glottal pressure and glottal airflow, and of sound pressure for productions of syllable sequences. Statistical results are used to infer mechanisms that underlie differences across ( 1 ) normal, loud, and soft voice, (2) normal, high, and low pitch, and (3) between female and male voices. Interspeaker variation in group data and intra speaker variation across repeated recordings is also investigated. The results showed no significant female-male differences in pressure, suggesting that differences in other measures were not primarily due to differences in the respiratory systems . Most glottal waveforms showed a DC flow offset, suggesting an air leakage through a posterior glottal opening. Results suggested (indirectly) that the males in comparison with the females had significantly higher vocal fold closing velocities (maximum flow declination rate), larger vocal fold oscillations (AC flow), and relatively longer closed portions of the cycle (open quotient) in normal and loud voice. In soft voice, female and male waveforms were more alike. In comparison with normal voice, both females and males produced loud voice with significantly higher values of pressure, vocal fold closing velocity, and AC flow. Soft voice was produced with significantly lower values of these measures and increased DC flow. Correlation analyses indicated that several of the airflow measures were more directly related to vocal intensity than to pitch. Interspeaker variation was large, emphasizing the importance of large subject groups to capture normal variation. Intraspeaker variation across recording sessions was less than 2 standard deviations of the group means. The results should contribute to the understanding of normal voice function, and should be useful as norms in studies of voices disorders as well. / Härtill 5 uppsatser.För att köpa boken skicka en beställning till exp@ling.su.se/ To order the book send an e-mail to exp@ling.su.se

In a commercial Internet environment, the quality of service experienced by a user is critical to competitive advantage and business survivability. The availability and response time of a distributed software service are central components of the overall quality of service provided to users. Traditionally availability is a measure of service down time. Traditionally availability measures the probability that the service will be live and is expressed in terms of failure occurrence and repair or recovery time. Response time is a measure of the time taken from when the service request is made, to when service provision occurs for the user. Deteriorating response time is also a valuable indicator to denial of service attacks which continue to pose a significant threat to service availability. The concept of the service cluster is increasingly being deployed to improve service availability and response time. Cluster processor replication increases service availability. Cluster dispatching of service requests across the replicated cluster processors increases service scalability and therefore response time. This thesis commences with a review of the research and current technology in the area of distributed software service availability. The review aims to identify any deficiencies within that area and propose critical features that mitigate those deficiencies. The three critical features proposed are in relation to user wait time, cluster dispatching, and the trust-based filtering of service requests. The user wait time proposal is that the availability of a distributed service should reflect both liveness probability level and probabalistic user access time of the service. The cluster dispatching proposal is that dispatching processing overhead is a function of the number of Internet Protocol (IP) datagrams/Transport Control Protocol (TCP) segments that are received by the dispatcher in respect of each service request. Consequently the number of IP datagrams/TCP segments should be minimised ideally so that for each incoming service request there is one IP datagram/TCP segment. The trust-based filtering proposal is that the level of trust in respect of each service request should be identified by the service as this is critical in mitigating distributed denial of service attacks - and therefore maximising the availability of the service A conceptual availability model which supports the three critical features within an Internet clustered service environment is then described. The conceptual model proposes an expanded availability definition and then describes the realization of this definition via additional capabilities positioned within the Transport layer of the Internet communication environment. The additional capabilities of this model also facilitate the minimization of cluster dispatcher processing load and the identification by the cluster dispatcher of request trust level. The model is then implemented within the Linux kernel. The implementation involves the addition of several options to the existing TCP specification and also the addition of several functions to the existing Socket API. The implementation is subsequently evaluated in a dispatcher-based clustered service environment.

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Thesis (Ph.D.) -- Mississippi State University. Department of Management and Information Systems. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D.)--George Mason University, 2007. / Title from PDF t.p. (viewed Jan. 18, 2008). Thesis directors: Paul Amman, Duminda Wijesekera. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Technology. Vita: p. 198. Includes bibliographical references (p. 189-197). Also available in print.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 206-216).

Thesis (M.S.)--Ohio University, June, 2000. / Title from PDF t.p.

Thesis (Ph.D.)--University of Wollongong, 2004. / Typescript. Includes bibliographical references: leaf 230-241.

Thesis (Ph.D.)--University of Melbourne, Dept. of Electrical and Electronic Engineering, 2008. / Typescript. Includes bibliographical references (leaves 149-158).

Thesis (M. App. Sc.)--Carleton University, 2001. / Includes bibliographical references (p. 126-131). Also available in electronic format on the Internet.