Thesis (M.J.)--Carleton University, 2002. / Includes bibliographical references (p. 149-157). Also available in electronic format on the Internet.

Thesis (Ph. D.)--Carleton University, 2004. / Includes bibliographical references (p. 306-341). Also available in electronic format on the Internet.

Human localisation of sound in enclosed spaces is a cross-disciplinary research topic, with important applications in auditory science, room acoustics, spatial audio and telecommunications. By combining an accelerated model of $3$D sound propagation in rooms with a perceptual model of spatial processing, this thesis provides an integrated framework for studying sound localisation in enclosed spaces on the horizontal plane, with particular emphasis on room acoustics applications. The room model is based on the finite difference time domain (FDTD) method, which has been extended to include physically-constrained sources and binaural receivers based on laser-scanned listener geometries. The underlying algorithms have been optimised to run on parallel graphics hardware, thus allowing for a high spatial resolution, and accordingly, a significant decrease of numerical dispersion evident in the FDTD method. The perceptual stage of the model features a signal processing chain emulating the physiology of the auditory periphery, binaural cue selection based on interaural coherence, and a final decision maker based on supervised learning. The entire model is shown to be capable of imitating human sound localisation in different listening situations, including free field conditions and at the presence of sound occlusion, diffraction and reflection. Results are validated against subjective data found in the literature, and the model's applications to the fields of room acoustics and spatial audio are demonstrated and discussed.

This Creative Writing thesis argues for the need to rethink our understanding of climate change and focuses on the response of creative writers to this phenomenon, whilst also offering its own creative contribution. The critical component aims at articulating a post-climate change poetics. It reviews the mainstream literature in popular science writing, fiction and poetry from the point of view of a political frame-analysis of climate change, to demonstrate how a certain understanding of climate change maps onto conventions of literary genre. The thesis takes the view that many mainstream literary attempts to negotiate climate change are compromised by the teleological way in which they conceive of the phenomenon. As an alternative position, it draws on the work of climatologist Mike Hulme and physicist and cultural theorist Karen Barad to encourage participation in climate change as a condition for negotiating its meaning. Lewis Carroll’s Through the Looking Glass is proposed as a model for literary production informed by this poetics and as a model for the author’s own creative practice. The creative component of this thesis is an intra-generic text presenting the fictionalised narrative of a cycle expedition the author made from Salford to the Greek island of Ikaria in the summer of 2010. This substantial work aims to interrogate, imagine, and enquire into the epistemology of a post-climate change world.

Classification is one of the primary tasks of data mining and aims to assign a class label to unseen examples by using a model learned from a training dataset. Most of the accepted classifiers are designed to minimize the error rate but in practice data mining involves costs such as the cost of getting the data, and cost of making an error. Hence the following question arises: Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem? It is well known to the machine learning community that there is no single algorithm that performs best for all domains. This observation motivates the need to develop an “algorithm selector” which is the work of automating the process of choosing between different algorithms given a specific domain of application. Thus, this research develops a new meta-learning system for recommending cost-sensitive classification methods. The system is based on the idea of applying machine learning to discover knowledge about the performance of different data mining algorithms. It includes components that repeatedly apply different classification methods on data sets and measuring their performance. The characteristics of the data sets, combined with the algorithm and the performance provide the training examples. A decision tree algorithm is applied on the training examples to induce the knowledge which can then be applied to recommend algorithms for new data sets, and then active learning is used to automate the ability to choose the most informative data set that should enter the learning process. This thesis makes contributions to both the fields of meta-learning, and cost sensitive learning in that it develops a new meta-learning approach for recommending cost-sensitive methods. Although, meta-learning is not new, the task of accelerating the learning process remains an open problem, and the thesis develops a novel active learning strategy based on clustering that gives the learner the ability to choose which data to learn from and accordingly, speed up the meta-learning process. Both the meta-learning system and use of active learning are implemented in the WEKA system and evaluated by applying them on different datasets and comparing the results with existing studies available in the literature. The results show that the meta-learning system developed produces better results than METAL, a well-known meta-learning system and that the use of clustering and active learning has a positive effect on accelerating the meta-learning process, where all tested datasets show a decrement of error rate prediction by 75 %.

The acoustic character of a space is often quantified using objective room acoustic parameters. The measurement of these parameters is difficult in occupied conditions and thus measurements are usually performed when the space is un-occupied. This is despite the knowledge that occupancy can impact significantly on the measured parameter value. Within this thesis new methods are developed by which naturalistic signals such as speech and music can be used to perform acoustic parameter measurement. Adoption of naturalistic signals enables passive measurement during orchestral performances and spoken announcements, thus facilitating easy in-situ measurement. Two methods are described within this work; (1) a method utilising artificial neural networks where a network is taught to recognise acoustic parameters from received, reverberated signals and (2) a method based on the maximum likelihood estimation of the decay curve of the room from which parameters are then calculated. (1) The development of the neural network method focuses on a new pre-processor for use with music signals. The pre-processor utilises a narrow band filter bank with centre frequencies chosen based on the equal temperament scale. The success of a machine learning method is linked to the quality of the training data and therefore realistic acoustic simulation algorithms were used to generate a large database of room impulse responses. Room models were defined with realistic randomly generated geometries and surface properties; these models were then used to predict the room impulse responses. (2) In the second approach, a statistical model of the decay of sound in a room was further developed. This model uses a maximum likelihood (ML) framework to yield a number of decay curve estimates from a received reverberant signal. The success of the method depends on a number of stages developed for the algorithm; (a) a pre-processor to select appropriate decay phases for estimation purposes, (b) a rigorous optimisation algorithm to ensure the correct maximum likelihood estimate is found and (c) a method to yield a single optimum decay curve estimate from which the parameters are calculated. The ANN and ML methods were tested using orchestral music and speech signals. The ANN method tended to perform well when estimating the early decay time (EDT), for speech and music signals the error was within the subjective difference limens. However, accuracy was reduced for the reverberation time (Rt) and other parameters. By contrast the ML method performed well for Rt with results for both speech and music within the difference limens for reasonable (<4s) reverberation time. In addition reasonable accuracy was found for EDT, Clarity (C80), Centre time (Ts) and Deutichkeit (D). The ML method is also capable of producing accurate estimates of the binaural parameters Early Lateral Energy Fraction (LEF) and the late lateral strength (LG). A number of real world measurements were carried out in concert halls where the ML accuracy was shown to be sufficient for most parameters. The ML method has the advantage over the ANN method due to its truly blind nature (the ANN method requires a period of learning and is therefore semi-blind). The ML method uses gaps of silence between notes or utterances, when these silence regions are not present the method does not produce an estimate. Accurate estimation requires a long recording (hours of music or many minutes of speech) to ensure that at least some silent regions are present. This thesis shows that, given a sufficiently long recording, accurate estimates of many acoustic parameters can be obtained directly from speech and music. Further extensions to the ML method detailed in this thesis combine the ML estimated decay curve with cepstral methods which detect the locations of early reflections. This improves the accuracy of many of the parameter estimates.

Social media is increasingly used for social protest, but does online participation advance the aims of social movements, or does it undermine efforts for social change? We explore this question in the present thesis by examining how the use of social media for collective action shapes, and is shaped by, the social psychological concerns of technology users. Adopting a diverse approach in terms of research questions and methodology, we examine how collective action is affected by: (1) features of the digital environment, (2) internet-enabled modes of participation, and (3) digitally-facilitated communities. Our findings demonstrate that group-level representations of the self and salient others are integral to the relationship between digital technology and collective action. Ultimately, we argue that digital technology can act as both a psychological bridge and barrier between disparate groups and issues; in this way it can both facilitate and undermine mobilisation efforts and broader aims for social change.

The Internet has revolutionized the way in which people are entertained, communicate and collect information. As people increase their ability to connect with the outside world from inside their homes, they hold the power to become their own gatekeepers filtering information as they see fit. Many question whether this will weaken the power of the traditional media sources that are often seen as elitist and potentially biased. This researcher hypothesized that people who cite high credibility ratings of news media channels are more likely to use traditional media channels such as television and newspapers and people who cite low credibility ratings of news media channels are more likely to use alternate media channels such as the Internet. While the researcher was unable to reject the null hypothesis, a pattern of general mistrust of traditional news media was revealed when nearly three-fourths of respondents gave traditional media channels a "not-credible" rating. / by Katrina Herring. / Thesis (M.A.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Submitted by CARLOS EDUARDO DE LIMA (kadulima.planner@gmail.com) on 2018-05-07T14:07:05Z No. of bitstreams: 1 CarlosEduardoDeLima - PequisaPPGMIT.pdf: 3805666 bytes, checksum: 230489a041e8c83f67320e15714cf8ad (MD5) / Rejected by Lucilene Cordeiro da Silva Messias null (lubiblio@bauru.unesp.br), reason: Solicitamos que realize uma nova submissão seguindo as orientações abaixo: 1 - Preencher e inserir a ficha catalográfica no arquivo em pdf, pois é um ítem obrigatório. 1 - Inserir a ata de defesa no arquivo em pdf, pois é um ítem obrigatório. Agradecemos a compreensão. on 2018-05-07T18:51:39Z (GMT) / Submitted by CARLOS EDUARDO DE LIMA (kadulima.planner@gmail.com) on 2018-05-07T19:40:12Z No. of bitstreams: 1 CarlosEduardoDeLima - PequisaPPGMIT.pdf: 4248684 bytes, checksum: 9dc7a3260da510a2abea5c583764f524 (MD5) / Approved for entry into archive by Lucilene Cordeiro da Silva Messias null (lubiblio@bauru.unesp.br) on 2018-05-08T13:07:34Z (GMT) No. of bitstreams: 1 lima_ce_me_bauru.pdf: 4122614 bytes, checksum: 0db356c3911bdb32092653e2195a5519 (MD5) / Made available in DSpace on 2018-05-08T13:07:34Z (GMT). No. of bitstreams: 1 lima_ce_me_bauru.pdf: 4122614 bytes, checksum: 0db356c3911bdb32092653e2195a5519 (MD5) Previous issue date: 2018-03-14 / O presente estudo visa identificar as inúmeras transformações que o planejamento de propaganda tem enfrentado desde o advento da Internet e das tecnologias de comunicação e informação baseadas em big data, Machine Learning, cluster e outras ferramentas de inteligência de dados. Dessa forma, buscou-se fazer um levantamento histórico e documental sobre os modelos de planejamento de propaganda e briefs criativos. Percebeu-se fundamental traçar uma breve documentação histórica sobre a concepção da disciplina de planejamento para o planejador e a forma como esse processo foi desenvolvido no Brasil, assim como sua evolução. Fez-se necessário também definir conceitos sobre big data e inovação, buscando identificar como afetam a estrutura e as metodologias até então usadas pelo planejamento. Com isso, objetivou-se poder entender como o planejador está sendo levado a desenvolver novas competências que abordam diferentes disciplinas, além das que já eram aplicadas no processo de investigação e criação do planejamento. Dessa forma, foram utilizadas metodologias de pesquisa de campo com entrevistas em profundidade com heads e diretores de planejamento de agências de comunicação e players reconhecidos por sua competência e experiência no planejamento de propaganda. Sendo assim, esta pesquisa apresenta uma proposta de um método de planejamento que, por meio de ferramentas baseadas em softwares e aplicativos, permita que o profissional de planejamento possa gerar ideias inovadoras e propor uma nova cultura de pensamento à agência. / This study aims to spot the countless transformations that the advertising planning has been passing through since the appearance of the Internet, as well as communication and information technologies based upon big data, Machine Learning , cluster and othe r data intelligence mechanisms. Along these lines, it was undertaken to assemble historical and documental facts about advertising planning and creative briefs guidelines. It was noticed the importance to picture a brief historical documentation about the conception of the planning subject for planners and the way this process was developed in Brazil, as well as its evolution. It was also necessary to define concepts about big data and innovation, in order to find how they impact the structure and methodolo gies used by the advertising planning until then. Thereby, the goal is to understand how the planner is being compelled to develop new skills which approach different matters, beyond the ones that were already used in the process of inquiring and creating in advertising planning. Thus, field research methodologies were applied with in - depth interviews with heads and directors of planning at communication agencies and market players whom are renowned for their competence and experience in advertising plannin g. Therefore, this essay proposes a planning approach which, utilizing tools based upon softwares and appliances, enables planners to develop disrupting ideas and come up with new mindsets to agencies.

Submitted by LAÍS AKEMI MARGADONA (laisakemi.ma@gmail.com) on 2018-05-28T18:25:48Z No. of bitstreams: 1 DISSERTAÇÃO FINAL - 2018 (Pós-Defesa).pdf: 14288738 bytes, checksum: b2a31b6757140f2a6c7acc0c57c0d969 (MD5) / Approved for entry into archive by Lucilene Cordeiro da Silva Messias null (lubiblio@bauru.unesp.br) on 2018-05-28T18:51:43Z (GMT) No. of bitstreams: 1 margadona_la_me_bauru.pdf: 14288738 bytes, checksum: b2a31b6757140f2a6c7acc0c57c0d969 (MD5) / Made available in DSpace on 2018-05-28T18:51:43Z (GMT). No. of bitstreams: 1 margadona_la_me_bauru.pdf: 14288738 bytes, checksum: b2a31b6757140f2a6c7acc0c57c0d969 (MD5) Previous issue date: 2018-03-29 / O objetivo deste trabalho é apresentar uma análise dos principais canais em que as fotografias dos Jogos Olímpicos Rio 2016 foram veiculadas dentro do rico ecossistema midiático contemporâneo, de modo a estabelecer debates e discussões. A escolha do objeto foi devido à profusão de meios de publicação das fotografias: mídias como o Google+, Instagram, Facebook, Snapchat e Twitter; websites oficiais; websites de notícias, esportes e entretenimento; revistas e jornais digitais; bancos de imagens e agências de notícias; transmissões televisivas e aplicativos oficiais do evento. A Ecologia dos Meios foi um arcabouço teórico capaz de contemplar os diversos aspectos do contexto em que a fotografia foi produzida e partilhada. A metodologia consistiu em: revisão bibliográfica, definição de canais digitais em que os registros fotográficos foram inseridos, coleta qualitativa de imagens, monitoramento de hashtags no Instagram, compilação de infográficos e estatísticas realizados por agências e sites de tecnologia e entretenimento e por fim, desenvolvimento de discussões por meio dos dados coletados. A dissertação está estruturada em três principais eixos: base teórica, eixo prático e discussões advindas da coleta das imagens, unida à pesquisa teórica. Como resultado, propomos oferecer um panorama da produção fotográfica nos Jogos Rio 2016, bem como levantar discussões e debates sobre a fotografia no ecossistema midiático e oferecer materiais teóricos e fotográficos para pesquisas posteriores. / This work intends to present an analysis of the main channels in which the Rio 2016 Olympic Games photographs were shared in the rich contemporary media ecosystem, in order to establish debates and discussions. This object was chosen due to the profusion of photo publishing media, such as Google+, Instagram, Facebook, Snapchat and Twitter; official websites; sports, news and entertainment websites; digital magazines and newspapers; image banks and news agencies; television broadcasts; official event applications. The Media Ecology studies were a theoretical framework capable of contemplating the various aspects of the context in which the photographs were produced and shared. The methodology consisted in bibliographic revision, definition of digital channels in which the photographic records were inserted, qualitative image gathering, research of Instagram hashtags, compilation of statistics made by technology agencies and entertainment websites and development of discussions through the collected data. This dissertation is structured in three main sections: theoretical basis, practical part and discussions developed with the image gathering and theoretical research. As a result, we propose to offer a panorama of the photographic production in Rio 2016 Olympics and material for later researches, as well as to raise discussions and debates on the photography in the media ecosystem