Display/control gain is the amount of movement that occurs on a display in response to a unit amount of movement on the control. Two studies were conducted to determine the adequacy of identifying the optimum gain for an interface as a method of control-display interface optimization. The first study examined the effects of changes in both the maximum control input and the display width on target acquisition performance with a touch tablet and a trackball. The hypothesis that an interaction between the control input and the display output would determine performance was not supported for either device. There was a main effect of the control input for the touch tablet, and significant effects of the control input and the display width for the trackball. The results also indicate that, at least for the touch tablet, gain is not a sufficient specification for performance. The second study evaluated the effects of changes in the display amplitude, the display target width, and the control amplitude. There were significant interactions among these three factors for both touch tablet and trackball target acquisition performance. These results extend the findings of the first study with respect to the inability of gain to predict performance. In addition, the inadequacy of Fitts' Law as it applies to the given interfaces is discussed. / Ph. D. / incomplete_metadata

Thesis (MScEng)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: The Electronic Systems Laboratory at Stellenbosch University is currently developing a fully 3-axis controlled Attitude Determination and Control Subsystem (ADCS) for CubeSats. This thesis describes the design and development of an Onboard Computer (OBC) suitable for ADCS application. A separate dedicated OBC for ADCS purposes allows the main CubeSat OBC to focus only on command and data handling, communication and payload management. This thesis describes, in detail the development process of the OBC. Multiple Microcontroller Unit (MCU) architectures were considered before selecting an ARM Cortex-M3 processor due to its performance, power efficiency and functionality. The hardware was designed to be as robust as possible, because radiation tolerant and redundant components could not be included, due to their high cost and the technical constraints of a CubeSat. The software was developed to improve recovery from lockouts or component failures and to enable the operational modes to be configured in real-time or uploaded from the ground station. Ground tests indicated that the OBC can handle radiation-related problems such as latchups and bit-flips. The peak power consumption is around 500 mW and the orbital average is substantially lower. The proposed OBC is therefore not only sufficient in its intended application as an ADCS OBC, but could also stand in as a backup for the main OBC in case of an emergency. / AFRIKAANSE OPSOMMING: Die Elektroniese Stelsels Laboratorium by die Universiteit van Stellenbosch is tans besig om ’n volkome 3-as gestabiliseerde oriëntasiebepaling en -beheerstelsel (Engels: ADCS) vir ’n CubeSat te ontwikkel. Hierdie tesis beskryf die ontwerp en ontwikkeling van ’n aanboordrekenaar (Engels: OBC) wat gebruik kan word in ’n ADCS. ’n Afsonderlike OBC wat aan die ADCS toegewy is, stel die hoof-OBC in staat om te fokus op beheer- en datahantering, kommunikasie en loonvragbestuur. Hierdie tesis beskryf breedvoerig die werkswyse waarvolgens die OBC ontwikkel is. Verskeie mikroverwerkers is as moontlike kandidate ondersoek voor daar op ’n ARM Cortex-M3-gebaseerde mikroverwerker besluit is. Hierdie mikroverwerker is gekies vanweë sy spoed, effektiewe kragverbruik en funksionaliteit. Die hardeware is ontwikkel om so robuust moontlik te wees, omdat stralingbestande en oortollige komponente weens kostebeperkings, asook tegniese beperkings van ’n CubeSat, nie ingesluit kon word nie. Die programmatuur is ontwikkel om van ’n uitsluiting en ’n komponentfout te kan herstel. Verder kan programme wat tydens vlug in werking is, verstel word en vanaf ’n grondstasie gelaai word. Grondtoetse het aangedui dat die OBC stralingverwante probleme, soos ’n vergrendeling (latchup) of bis-omkering (bit-flip), kan hanteer. Die maksimum kragverbruik is ongeveer 500 mW en die gemiddelde wentelbaankragverbruik is beduidend kleiner. Die voorgestelde OBC is dus voldoende as ADCS OBC asook hoof-OBC in geval van nood.

Ph.D. / Computer Science and Electrical Engineering / We envision that next-generation spoken dialogue systems will be supporting a complex user goal and multiple parallel tasks, which requires the system and the user to jointly direct the flow of conversation. The problem, however, is that there lacks an effective model of directing the flow of conversation. This thesis research aims to develop such a model for next-generation spoken dialogue systems. We started with conventions actually used in human-human dialogue, which are natural for users to follow and probably also efficient in problem-solving. An annotation framework, DialogueView, was established to allow for the investigation of complex interaction in dialogue. A series of empirical studies on two corpora, the Trains and the MTD, were then conducted to understand people's initiative behavior of directing the conversation flow. We first examined people's initiative behavior in decomposing a complex goal into sub-goals and achieving each of them in the Trains domain. We found that initiative is subservient to discourse goal. We next examined people's initiative behavior in switching the conversation to a more urgent task. We found that conversants strive to switch tasks at a less disruptive place; but where they cannot, they exert additional effort to signal the task switching, such as increasing pitch. We finally examined people's behavior on initiative conflicts, where both conversants try to direct the conversation at the same time. We found that conversants try to avoid initiative conflicts; but when initiative conflicts occur, they are efficiently resolved with simple linguistic devices such as volume. Computer simulation experiments were also conducted to better understand the underlying benefits of using the human conventions. Our findings on human-human dialogues have important implication for building next-generation spoken dialogue systems by (1) guiding the system when to show initiative, and when to let the user show initiative; (2) guiding the system when and how to switch to a more urgent task, and to understand the user's switch; and (3) guiding the system how to resolve and repair initiative conflicts.

This essay follows a Media Teacher in her work as a coordinator and an artistic leader for a European project called Legalopoli concerning laws and ethics in a senior level school for 13-16 year-olds in Mora, Sweden. The students write film stories about how their characters have to make choices in ethical dilemma situations. Then the learners create interactive computer games together through practical film work. At the same time we can see how the educator also gets into difficult ethical situations, when she is working with the students. This forces her to self-reflection. She realizes that the practical knowledge in her work has a greater deal of an ethical dimension, than she earlier has been aware of. She understands that the convincing force in the project consists of the confidence and trust she has to create and develop among the students, who, in the start, were unsure and lacked in respect for one another. Through the practical film work they all get close and learn to see both themselves and each other. The students develop from being afraid of saying anything in the group to become confident and capable media producers, where their voices get listened to. They have started a journey into becoming democratic and caring citizens with wider perspectives of themselves and of the world. / Denna essä följer en mediepedagogs arbete som koordinator och konstnärlig ledare för ett Europeiskt projekt kallat Legalopoli, om lagar och etik i en högstadieskola i Mora. Eleverna skriver filmberättelser om rollkaraktärer, som ställs inför olika etiska dilemman i det interaktiva dataspel, som studenterna gemensamt skapar genom praktiskt filmarbete. Samtidigt får vi följa hur pedagogen på samma sätt, ställs inför olika svåra valsituationer i det pågående arbetet med eleverna. Hon tvingas till självreflektion och inser att den praktiska kunskapen i hennes arbete innehar en större etisk dimension än hon tidigare trott. Hon inser att bärkraften i projektet är det förtroende och den tillit, som hon måste skapa och utveckla bland eleverna, som från början var osäkra och betedde sig respektlöst mot varandra. Genom det praktiska filmarbetet kommer de alla nära varandra och får efter hand syn på både sig själva och varandra. Eleverna utvecklas från att ha varit rädda för att yttra sig i gruppen, till att bli tillitsfulla och kapabla medieproducenter, där de får göra sina röster hörda. De påbörjar en bildningsresa till att bli demokratiska och solidariska medborgare med vidgade perspektiv på sig själva och världen.

Theory as an approach to generative composition and interactive computer music. Inspired by the notion of Performance Indeterminacy, software has been developed that attempts to simulate the interactions of improvising performers using a multi-agent system based on the ‘Iterated Prisoner’s Dilemma’. Composition activities and programming activities have formed a symbiotic relationship throughout the creation of the portfolio as each has constantly informed the other. Stylistically, the works presented fall into the experimental genre, although individually they address a wide range of aesthetic goals. The main contribution of this portfolio is a new approach to generative composition based on behavioural models, creating a sense of form bottom-up through modelling the social dynamics of music performance. Through this approach, the direct modelling of musical structures is avoided; instead larger scale forms emerge through the interactions of an ensemble of ‘improvising’ agents. This method offers a departure from previous complex systems work in the area of music, creating computer models of specific musical situations. Links between the Iterated Prisoner’s Dilemma and music are also established and combined with current music technologies. / Thesis(Ph.D.)- University of Adelaide, Elder Conservatorium of Music, 2008

Theory as an approach to generative composition and interactive computer music. Inspired by the notion of Performance Indeterminacy, software has been developed that attempts to simulate the interactions of improvising performers using a multi-agent system based on the ‘Iterated Prisoner’s Dilemma’. Composition activities and programming activities have formed a symbiotic relationship throughout the creation of the portfolio as each has constantly informed the other. Stylistically, the works presented fall into the experimental genre, although individually they address a wide range of aesthetic goals. The main contribution of this portfolio is a new approach to generative composition based on behavioural models, creating a sense of form bottom-up through modelling the social dynamics of music performance. Through this approach, the direct modelling of musical structures is avoided; instead larger scale forms emerge through the interactions of an ensemble of ‘improvising’ agents. This method offers a departure from previous complex systems work in the area of music, creating computer models of specific musical situations. Links between the Iterated Prisoner’s Dilemma and music are also established and combined with current music technologies. / Thesis(Ph.D.)- University of Adelaide, Elder Conservatorium of Music, 2008

Orientadores: Ricardo da Silva Torres, Alexandre Xavier Falcão / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-23T15:18:27Z (GMT). No. of bitstreams: 1 Santos_JeferssonAlexdos_D.pdf: 18672412 bytes, checksum: 58ac60d8b5342ab705a78d5c82265ab8 (MD5) Previous issue date: 2013 / Resumo: Um grande esforço tem sido feito para desenvolver sistemas de classificação de imagens capazes de criar mapas temáticos de alta qualidade e estabelecer inventários precisos sobre o uso do solo. As peculiaridades das imagens de sensoriamento remoto (ISR), combinados com os desafios tradicionais de classificação de imagens, tornam a classificação de ISRs uma tarefa difícil. Grande parte dos desafios de pesquisa estão relacionados à escala de representação dos dados e, ao mesmo tempo, à dimensão e à representatividade do conjunto de treinamento utilizado. O principal foco desse trabalho está nos problemas relacionados à representação dos dados e à extração de características. O objetivo é desenvolver soluções efetivas para classificação interativa de imagens de sensoriamento remoto. Esse objetivo foi alcançado a partir do desenvolvimento de quatro linhas de pesquisa. A primeira linha de pesquisa está relacionada ao fato de embora descritores de imagens propostos na literatura obterem bons resultados em várias aplicações, muitos deles nunca foram usados para classificação de imagens de sensoriamento remoto. Nessa tese, foram testados doze descritores que codificam propriedades espectrais e sete descritores de textura. Também foi proposta uma metodologia baseada no classificador K-Vizinhos mais Próximos (K-nearest neighbors - KNN) para avaliação de descritores no contexto de classificação. Os descritores Joint Auto-Correlogram (JAC), Color Bitmap, Invariant Steerable Pyramid Decomposition (SID) e Quantized Compound Change Histogram (QCCH), apresentaram os melhores resultados experimentais na identificação de alvos de café e pastagem. A segunda linha de pesquisa se refere ao problema de seleção de escalas de segmentação para classificação de imagens de sensoriamento baseada em objetos. Métodos propostos recentemente exploram características extraídas de objetos segmentados para melhorar a classificação de imagens de alta resolução. Entretanto, definir uma escala de segmentação adequada é uma tarefa desafiadora. Nessa tese, foram propostas duas abordagens de classificação multiescala baseadas no algoritmo Adaboost. A primeira abordagem, Multiscale Classifier (MSC), constrói um classificador forte que combina características extraídas de múltiplas escalas de segmentação. A outra, Hierarchical Multiscale Classifier (HMSC), explora a relação hierárquica das regiões segmentadas para melhorar a eficiência sem reduzir a qualidade da classificação xi quando comparada à abordagem MSC. Os experimentos realizados mostram que é melhor usar múltiplas escalas do que utilizar apenas uma escala de segmentação. A correlação entre os descritores e as escalas de segmentação também é analisada e discutida. A terceira linha de pesquisa trata da seleção de amostras de treinamento e do refinamento dos resultados da classificação utilizando segmentação multiescala. Para isso, foi proposto um método interativo para classificação multiescala de imagens de sensoriamento remoto. Esse método utiliza uma estratégia baseada em aprendizado ativo que permite o refinamento dos resultados de classificação pelo usuário ao longo de interações. Os resultados experimentais mostraram que a combinação de escalas produzem melhores resultados do que a utilização de escalas isoladas em um processo de realimentação de relevância. Além disso, o método interativo obtém bons resultados com poucas interações. O método proposto necessita apenas de uma pequena porção do conjunto de treinamento para construir classificadores tão fortes quanto os gerados por um método supervisionado utilizando todo o conjunto de treinamento disponível. A quarta linha de pesquisa se refere à extração de características de uma hierarquia de regiões para classificação multiescala. Assim, foi proposta uma abordagem que explora as relações existentes entre as regiões da hierarquia. Essa abordagem, chamada BoW-Propagation, utiliza o modelo bag-of-visual-word para propagar características ao longo de múltiplas escalas. Essa ideia foi estendida para propagar descritores globais baseados em histogramas, a abordagem H-Propagation. As abordagens propostas aceleram o processo de extração e obtém bons resultados quando comparadas a descritores globais / Abstract: A huge effort has been made in the development of image classification systems with the objective of creating high-quality thematic maps and to establish precise inventories about land cover use. The peculiarities of Remote Sensing Images (RSIs) combined with the traditional image classification challenges make RSI classification a hard task. Many of the problems are related to the representation scale of the data, and to both the size and the representativeness of used training set. In this work, we addressed four research issues in order to develop effective solutions for interactive classification of remote sensing images. The first research issue concerns the fact that image descriptors proposed in the literature achieve good results in various applications, but many of them have never been used in remote sensing classification tasks. We have tested twelve descriptors that encode spectral/color properties and seven texture descriptors. We have also proposed a methodology based on the K-Nearest Neighbor (KNN) classifier for evaluation of descriptors in classification context. Experiments demonstrate that Joint Auto-Correlogram (JAC), Color Bitmap, Invariant Steerable Pyramid Decomposition (SID), and Quantized Compound Change Histogram (QCCH) yield the best results in coffee and pasture recognition tasks. The second research issue refers to the problem of selecting the scale of segmentation for object-based remote sensing classification. Recently proposed methods exploit features extracted from segmented objects to improve high-resolution image classification. However, the definition of the scale of segmentation is a challenging task. We have proposed two multiscale classification approaches based on boosting of weak classifiers. The first approach, Multiscale Classifier (MSC), builds a strong classifier that combines features extracted from multiple scales of segmentation. The other, Hierarchical Multiscale Classifier (HMSC), exploits the hierarchical topology of segmented regions to improve training efficiency without accuracy loss when compared to the MSC. Experiments show that it is better to use multiple scales than use only one segmentation scale result. We have also analyzed and discussed about the correlation among the used descriptors and the scales of segmentation. The third research issue concerns the selection of training examples and the refinement of classification results through multiscale segmentation. We have proposed an approach for xix interactive multiscale classification of remote sensing images. It is an active learning strategy that allows the classification result refinement by the user along iterations. Experimental results show that the combination of scales produces better results than isolated scales in a relevance feedback process. Furthermore, the interactive method achieves good results with few user interactions. The proposed method needs only a small portion of the training set to build classifiers that are as strong as the ones generated by a supervised method that uses the whole available training set. The fourth research issue refers to the problem of extracting features of a hierarchy of regions for multiscale classification. We have proposed a strategy that exploits the existing relationships among regions in a hierarchy. This approach, called BoW-Propagation, exploits the bag-of-visual-word model to propagate features along multiple scales. We also extend this idea to propagate histogram-based global descriptors, the H-Propagation method. The proposed methods speed up the feature extraction process and yield good results when compared with global low-level extraction approaches / Doutorado / Ciência da Computação / Doutor em Ciência da Computação

APLAN is a computer software system developed to aid in an apparel company's management system. APLAN is designed to improve the efficiency of production management by combining the companies' main production activities in one system. This project was designed to use MYSQL as the database system. JSP (Java Server Pages) is an interface between MySQL and the web browser and the database access scheme is JDBC (JAVA Database Connectivity).

No description available.

One of the common research goals in disciplines such as computer graphics and robotics is to understand the subtleties of human motion and develop tools for recreating natural and meaningful motion. Physical simulation of virtual human characters is a promising approach since it provides a testbed for developing and testing control strategies required to execute various human behaviors. Designing generic control algorithms for simulating a wide range of human activities, which can robustly adapt to varying physical environments, has remained a primary challenge. This dissertation introduces methods for generic and robust control of virtual characters in an interactive physical environment. Our approach is to use the information of the physical contacts between the character and her environment in the control design. We leverage high-level knowledge of the kinematics goals and the interaction with the surroundings to develop active control strategies that robustly adapt to variations in the physical scene. For synthesizing intentional motion requiring long-term planning, we exploit properties of the physical model for creating efficient and robust controllers in an interactive framework. The control design leverages the reference motion capture data and the contact information with the environment for interactive long-term planning. Finally, we propose a compact soft contact model for handling contacts for rigid body virtual characters. This model aims at improving the robustness of existing control methods without adding any complexity to the control design and opens up possibilities for new control algorithms to synthesize agile human motion.