Synthesis and characterization of mechanical properties of a novel bioceramic composite material for biological applications

Thesis (M.S.) University of Alaska Fairbanks, 2010Bioceramics are used in a wide range of human skeletal repair and restoration applications as a synthetic bone substitute. 45S5 Bioglass, a bioactive ceramic, exhibits poor mechanical properties limiting the potential of the material and preventing its use in major load bearing applications. This investigation evaluated the synthesis and mechanical properties of a 45S5 Bioglass composite reinforced with different weight percentages of multi-wall carbon nanotubes. The material was analyzed using an X-Ray Diffractometer and a scanning electron microscope to determine the crystal structure, microstructural homogeneity, and surface texture of the composite material. The material was evaluated during the synthesis process to observe the evolution of the composite. Samples were sintered at 1000°C and 850°C to determine the effect of the sintering temperature on the mechanical properties of the composite. Once synthesized, the material was tested using the Vickers hardness indentation test to determine the mechanical properties of the ceramic, as defined by hardness and fracture toughness values. Hardness of the composite decreased with increasing nanotube concentration for all samples. A maximum fracture toughness value of 47.6 GPa·m¹/² corresponded to the addition of 1 weight percent multi-wall carbon nanotubes in the composite samples sintered at 1000°C. All of the composite samples sintered at 850°C reported lower fracture toughness values than the pure bioglass samples indicating that sintering temperature affects bonding between the composite components. These results prove that a Bioglass-multi-wall carbon nanotube composite has the potential for use as a synthetic material to restore function in load bearing bone

Mechanical Characterization of A2 and D2 Tool Steels By Nanoindentation

Nanoindentation technique was used to investigate the surface properties of A2 and D2 tool steel subjected to different heat treatments. the mechanical characteristics of these two easily available tool steels were studied based on microstructural images obtained from SEM, the grain growth after heat treatment using X-ray diffraction method and nanoindentation technique. the investigation showed that a single nanoindentation result can explain how heat treatment influences reliability and failure in A2 and D2 tool steels. in this work, the causes and effects of these variations were studied to explain how they influence reliability and failure in A2 and D2 tool steel. Finally, a cube-corner indenter tip was used to determine the fracture toughness of silicon wafer. the emphasis of this research is on how nanoindentation technique is more extensive in material characterization

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de ComputadoresSendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à interacção homemmáquina é o da criação de sistemas, que possam identificar gestos específicos e usálos para transmitir informações ou para controlar dispositivos. Para isso as interfaces baseados em visão para o reconhecimento de gestos, necessitam de detectar a mão de forma rápida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em visão são capazes de trabalhar com soluções específicas, construídos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investigação estudou e implementou soluções, suficientemente genéricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplicação num conjunto alargado de sistemas de interface homem-máquina, para reconhecimento de gestos em tempo real. A solução proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos estáticos e dinâmicos e que pode ser facilmente integrado e configurado para ser utilizado numa série de aplicações. É um sistema de baixo custo e fácil de treinar e usar, e uma vez que é construído unicamente com bibliotecas de código. As experiências realizadas permitiram mostrar que o sistema atingiu uma precisão de 99,2% em termos de reconhecimento de gestos estáticos e uma precisão média de 93,7% em termos de reconhecimento de gestos dinâmicos. Para validar a solução proposta, foram implementados dois sistemas completos. O primeiro é um sistema em tempo real capaz de ajudar um árbitro a arbitrar um jogo de futebol robótico. A solução proposta combina um sistema de reconhecimento de gestos baseada em visão com a definição de uma linguagem formal, o CommLang Referee, à qual demos a designação de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos estáticos e dinâmicos executados pelo árbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informação para os robôs. O segundo é um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experiências demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fiável. Embora a solução implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema é facilmente extensível para reconhecer o resto do alfabeto. As experiências também permitiram mostrar que a base dos sistemas de interação baseados em visão pode ser a mesma para todas as aplicações e, deste modo facilitar a sua implementação. A solução proposta tem ainda a vantagem de ser suficientemente genérica e uma base sólida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplicação de interface homem-máquina. A linguagem formal de definição da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solução final.Hand gesture recognition is a natural way of human computer interaction and an area of very active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Human-Computer Interaction (HCI) is to create systems, which can identify specific human gestures and use them to convey information or controlling devices. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Nowadays, vision-based gesture recognition systems are able to work with specific solutions, built to solve one particular problem and configured to work in a particular manner. This research project studied and implemented solutions, generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for real-time gesture recognition. The proposed solution, Gesture Learning Module Architecture (GeLMA), allows the definition in a simple way of a set of commands that can be based on static and dynamic gestures and that can be easily integrated and configured to be used in a number of applications. It is easy to train and use, and since it is mainly built with open source libraries it is also an inexpensive solution. Experiments carried out showed that the system achieved an accuracy of 99.2% in terms of hand posture recognition and an average accuracy of 93,72% in terms of dynamic gesture recognition. To validate the proposed framework, two systems were implemented. The first one is an online system able to help a robotic soccer game referee judge a game in real time. The proposed solution combines a vision-based hand gesture recognition system with a formal language definition, the Referee CommLang, into what is called the Referee Command Language Interface System (ReCLIS). The system builds a command based on system-interpreted static and dynamic referee gestures, and is able to send it to a computer interface which can then transmit the proper commands to the robots. The second one is an online system able to interpret the Portuguese Sign Language. The experiments showed that the system was able to reliably recognize the vowels in real-time. Although the implemented solution was only trained to recognize the five vowels, it is easily extended to recognize the rest of the alphabet. These experiments also showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate its implementation. The proposed framework has the advantage of being generic enough and a solid foundation for the development of hand gesture recognition systems that can be integrated in any human-computer interface application. The interface language can be redefined and the system can be easily configured to train different sets of gestures that can be easily integrated into the final solution

Design and implementation of a verb lexicon and verb sense disambiguator for Turkish

Ankara : Department of Computer Engineering and Information Science and Institute of Engineering and Science, Bilkent University, 1994.Thesis (Master's) -- -Bilkent University, 1994.Includes bibliographical refences.The lexicon has a crucial role in all natural language processing systems and has special importance in machine translation systems. This thesis presents the design and implementation of a verb lexicon and a verb sense disambigua- tor for Turkish. The lexicon contains only verbs because verbs encode events in sentences and play the most important role in natural language processing systems, especially in parsing (syntactic analyzing) and machine translation. The verb sense disambiguator uses the information stored in the verb lexicon that we developed. The main purpose of this tool is to disambiguate senses of verbs having several meanings, some of which are idiomatic. We also present a tool implemented in Lucid Common Lisp under X-Windows for adding, accessing, modifying, and removing entries of the lexicon, and a semantic concept ontology containing semantic features of commonly used Turkish nouns.Yılmaz, OkanM.S

Assessing the Impact of Active Signage Systems on Driving Behavior and Traffic Safety

Unsignalized Stop-Controlled Intersections (SCI) are widely used in North America, and account for one out of every ten collisions. Understanding how drivers and pedestrians behave at unsignalized intersections is critical for public safety. Drivers who do not obey the stop-sign’s indication by not coming to a complete stop or miss or fail to stop at SCI create a substantial safety risk. For decades, visibility and placement of road alignments and signage at intersections have been a concern among transportation safety specialists. Deployment of backlit Light-Emitting Diode (LED) or other illuminated signs (also known as active road signs) has been increased especially at hot-spots and locations with known safety problems, or potential collision risks. While these signs are expected to improve safety measures by regulating safe travelers’ passage, their performance is not yet fully understood. Although environmental factors such as intersection type, location, and road design are playing a major role, compositional variables such as driver behaviour, which can be explained in terms of carelessness, lack of attention, or overconfidence, is resulting in a failure to comply with the law of making a complete stop at SCI. Previous empirical research demonstrated some correlation between several variables such as traveller compliance with road signs and alignments, direct and indirect road safety measures, collision/conflict frequency, and road/traffic characteristics. These studies commonly employ before-after or cross-reference analyses to determine the long-term effects of various countermeasures at SCI. A few studies also utilized calibrated micro-simulations models to evaluate the surrogate safety measures at SCI. This thesis defines a methodology to evaluate the safety performance of a new and untested signage without putting traffic at long risk. To evaluate the performance of the signs, the suggested methodology investigates multiple parameters and identifies influencing variables in a conflict-based collision-prediction model at SCI. The proposed methodology is applied to a real-world network in the city of Montreal, with several three-leg SCI equipped with different countermeasures. The experiment was designed in a fashion which isolates the influence of several variables, allowing the focus to be on the impact of the target variable (signage type). Field experiments have been performed to study the driver’s behavior in terms of approaching speed as well as quantitative analysis on reactions to various signs, using different sample groups from the same population. This research sets up a microsimulation model that captures drivers’ behaviour with respect to signage according to the observed data. A genetic algorithm was deployed to calibrate the microsimulation model in terms of turning movement counts and the critical conflicts were calculated at each intersection using vehicle trajectories. Collision-prediction regression models was then developed for the intersections under investigation, using traffic volume and conflict. The results demonstrated a high correlation among countermeasures and drivers’ speed and compliance. The relationship between critical conflicts computed in microsimulation models and actual collisions was found to be statistically significant. The model which includes drivers' compliance in collision-prediction regression was also found to fit the collision data better. However, the results of this study do not support the previous assumption that the conflict-based collision-prediction models fit the collision data better than the volume-based collision-prediction models at SCI, especially with drivers’ compliance supplementary data. Finally, while the backlit signs’ performance was marginally better than that of a normal LED active sign, the difference was not statistically significant. The methodology suggested in this thesis has the potential to be implemented in safety performance evaluation of a countermeasure without placing traffic at danger for an extended period. For instance, when there is apprehension about an adverse effect. Future research could investigate leveraging drivers’ behaviour to countermeasures, to improve the performance of collision-prediction regression models like the one proposed in this thesis. Finally, the results from the performance assessment of the LED active signs can assist transportation specialists in deciding whether or not to deploy these countermeasures

An evaluation of NS-001 and TIMS data for lithological mapping and mineral exploration in weathered vegetated terrain

This thesis evaluates the combined use of multispectral remotely sensed data from the 0.45-2.35µm and 8µm-12µm wavelength regions for lithological mapping and mineral exploration in weathered, vegetated terrain. The area studied is located in N. E. Queensland, Australia, and consists of a mixture of igneous, metamorphic and sedimentary rocks. The extrusive and intrusive igneous rocks of acid to intermediate composition are currently the focus of active exploration for gold mineralisation. The results from this study indicate data from the 0.45-2.35µm wavelength region are of more use for mineral exploration than data from the 8-12µm wavelength region in this terrain. Evaluation of data from the 0.45-2.35µm wavelength region resulted in the discovery of an area of epithermal alteration with potential for gold mineralisation at Blackfellow Mountain. Data from both wavelength regions proved useful for litholgical mapping but certain lithological units could only be discriminated with the data from the 8-12µm wavelength region. In order to obtain these results the data were reduced to physically meaningful parameters (reflectance, temperature and emittance). This necessitated the removal of radiometric and geometric distortions. The techniques used to remove these distortions are outlined, including two new methods for the removal of atmospheric effects from data from the 8-12µm wavelength region. After correction, the data from the 0.45-2.35µm wavelength region were analysed by a variety of techniques to extract the relevant reflectance information. These included compositing, channel ratios, log residuals, directed principal components and least squares fit residuals (LRES). The log residual and LRES techniques proved most effective for lithological mapping and mineral exploration respectively. The corrected data from the 8-12µm wavelength region were also analysed by several techniques for extracting emittance and temperature information. These techniques were the decorrelation stretch, model emittance calculation and thermal log residuals. The latter technique, developed during this study, proved most effective for lithological mapping