Despite the increase in popularity of handheld devices, text entry on such devices is becoming more difficult due to reduced form factors that limit display size, input modes, and interaction techniques. In an effort to circumvent these issues, research has found that five-key methods are effective for text entry on devices such as in-car navigation systems, television and gaming controllers, wrist watches, and other small devices. Five-key text entry methods use four directional keys to move a selector over an on-screen keyboard and an Enter key for selection. Although other researchers have described five-key character layouts using alphabetical order and predictive layouts based on digraph frequencies, there is considerable latitude in designing the rest of a comprehensive on-screen keyboard. Furthermore, it might be possible to capitalize on the relative strengths of the alphabetic and predictive layouts by combining them in a hybrid layout. Thus, this research examines the design of alternative keyboard layouts for five-key text entry techniques. Three keyboard layouts (Alphabetical, Predictive, and Hybrid) were selected to represent standard and less familiar arrangements. The analysis centered on a series of controlled experiments conducted on a research platform designed by the author. In this work, when the immediate usability of three alternative keyboard layouts for supporting five-key text entry was investigated, results indicated no statistically significant differences in performance across the tested keyboards. Furthermore, experimental results show that following immediate usability, but still at the onset of learning, there was no overall difference in performance among the three keyboard layouts across four text types. However, the Alphabetical keyboard surpassed both the Predictive and Hybrid keyboards in text entry speed in typing Web addresses. The nonstandard keyboards performed superior to the Alphabetical keyboards in typing Words/Spaces and Sentences, but performed no better in typing Address strings than the Alphabetical. Use of mixed effects modeling suggested that the longitudinal data was best fitted by a quadratic model. Text entry performance on all three layouts improved as a function of practice, demonstrating that participants could learn the unfamiliar layouts to complete text entry tasks. Overall, there was no indication that use of nonstandard layouts impedes performance. In fact, trend in time data suggests that the learning rates were greater for the nonstandard keyboards over the standard layout. Overall, participants preferred the Hybrid layout. In summary, this dissertation focused on creating and validating novel and effective five-key text entry techniques for constrained devices.

Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2018-04-04T12:41:38Z No. of bitstreams: 2 Tese - André Pereira Marques - 2018.pdf: 11271921 bytes, checksum: 086b8deaeaa9f31cd4e5ea975724a254 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-04-04T13:27:18Z (GMT) No. of bitstreams: 2 Tese - André Pereira Marques - 2018.pdf: 11271921 bytes, checksum: 086b8deaeaa9f31cd4e5ea975724a254 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-04-04T13:27:18Z (GMT). No. of bitstreams: 2 Tese - André Pereira Marques - 2018.pdf: 11271921 bytes, checksum: 086b8deaeaa9f31cd4e5ea975724a254 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-22 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / The effective application of predictive maintenance techniques for power transformers is essential for the early detection of defects and failures, and in order to trigger scheduled preventive or corrective actions. This precludes the need for urgent and/or emergency interventions, aiming to reduce unscheduled power outages, which are usually more costly and cause great inconvenience to consumers and the electric power system. In this context, this work focuses on the development of an optimized diagnostic methodology for power transformers, by integrating eleven predictive techniques (with 27 quantities). These techniques are analyzed with respect to voltage level, type of electrical connection and age of the transformers – when applicable –, based on the experience of specialists/analysts, on standards and technical guidelines, and on statistical analyses of a database of actual field and laboratory tests. The analyses of the validation of the results are significant and presented through a specialized system, demonstrating their practical application. The novelty of this thesis consists in the development of an original classification method, called Normalized Doubly Weighted Sum (NDWS), and in the detailed description of the predictive techniques that are integrated, their functionalities, the creation of equations, the definition of criteria and parameters, with their weights and scores for the classification of “A” (excellent) to “E” (very poor), and recommended actions aimed at underpinning decision- making, thereby contributing to the body of studies in this field. Hence, it can be concluded that this work offers a comprehensive and efficient tool to aid in the optimized diagnosis of power transformers, insulated with kraft paper and immersed in mineral insulating oil, providing effective diagnostics and maintenance of these devices, and thus increasing the reliability of electric power systems. / A eficiência da aplicação de técnicas preditivas de manutenção em transformadores de potência é fundamental para se detectar defeitos e falhas ainda em estágio incipiente, disparar ações preventivas ou corretivas programadas, e assim evitar intervenções em caráter de urgência e ou emergência, visando a diminuição de interrupções não programadas no fornecimento de energia elétrica, as quais são comumente mais onerosas e causadoras de grandes transtornos aos consumidores e ao sistema elétrico. Neste sentido, os objetivos deste trabalho baseiam-se em apresentar o desenvolvimento de uma metodologia de diagnóstico otimizado destes equipamentos, mediante a integração de onze técnicas preditivas (com vinte e sete grandezas), analisando-as em relação ao nível de tensão, tipo de ligação elétrica e idade dos transformadores – quando aplicável – e de acordo com o seguinte embasamento: na experiência de especialistas/analistas; em normas e orientações técnicas; e em análises estatísticas de uma base de dados de ensaios reais realizados em campo e em laboratório. As análises com a validação dos resultados são significativas e apresentadas por meio de um sistema especialista, mostrando a sua aplicação prática. O ineditismo desta tese refere-se ao desenvolvimento de um método de classificação original, denominado Soma Duplamente Ponderada Normalizada (SDPN), e à descrição detalhada sobre quais técnicas preditivas são integradas, suas funcionalidades, elaboração de equações, a definição de critérios e de parâmetros, com seus pesos e suas notas para a classificação de “A” (excelente) a “E” (péssimo), e ações recomendadas que auxiliam nas tomadas de decisão, contribuindo com os estudos na área. Portanto, conclui-se que este trabalho possui uma aplicação abrangente e eficiente como ferramenta para o subsídio ao diagnóstico otimizado de transformadores de potência, isolados em papel kraft e imersos em óleo mineral isolante, proporcionando diagnósticos e manutenções efetivas nestes equipamentos e, consequentemente, impactando o aumento da confiabilidade do sistema elétrico.