869 resultados para Machine to Machine


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Estudio preliminar para la construcción de una máquina que sea capaz de reconocer la letra impresa para su uso por parte de invidentes. Establecen unos métodos de reconocimiento que tratan un mínimo de información con un nivel de reconocimiento aceptable y con el objetivo de que el aparato resultante sea lo más económico posible. El sistema, desde la introducción de la información luminosa hasta la salida en braille, fue simulado en un ordenador. Los resultados obtenidos fueron satisfactorios: con una pequeña cámara de captación de informaciones luminosas, conteniendo aproximadamente 50 elementos fotorreceptores, se obtiene más de un 90 por ciento de reconocimiento, y esto independientemente de la velocidad de desplazamiento de la cámara con relación al texto y con una muestra de datos de calidad bastante mediocre. Suponen que los excelentes resultados obtenidos son aún mejorables y que con este estudio previo y los resultados obtenidos va a permitirles ahora, realizar la construcción definitiva de la máquina.

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Modern organisms are adapted to a wide variety of habitats and lifestyles. The processes of evolution have led to complex, interdependent, well-designed mechanisms of todays world and this research challenge is to transpose these innovative solutions to resolve problems in the context of architectural design practice, e.g., to relate design by nature with design by human. In a design by human environment, design synthesis can be performed with the use of rapid prototyping techniques that will enable to transform almost instantaneously any 2D design representation into a physical three-dimensional model, through a rapid prototyping printer machine. Rapid prototyping processes add layers of material one on top of another until a complete model is built and an analogy can be established with design by nature where the natural lay down of earth layers shapes the earth surface, a natural process occurring repeatedly over long periods of time. Concurrence in design will particularly benefit from rapid prototyping techniques, as the prime purpose of physical prototyping is to promptly assist iterative design, enabling design participants to work with a three-dimensional hardcopy and use it for the validation of their design-ideas. Concurrent design is a systematic approach aiming to facilitate the simultaneous involvment and commitment of all participants in the building design process, enabling both an effective reduction of time and costs at the design phase and a quality improvement of the design product. This paper presents the results of an exploratory survey investigating both how computer-aided design systems help designers to fully define the shape of their design-ideas and the extent of the application of rapid prototyping technologies coupled with Internet facilities by design practice. The findings suggest that design practitioners recognize that these technologies can greatly enhance concurrence in design, though acknowledging a lack of knowledge in relation to the issue of rapid prototyping.

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Rationale. Smokers modify their smoking behaviour when switching from their usual product to higher or lower tar and nicotine-yield cigarettes. Objective. The aims of the current study were to assess the influence of varying nicotine yields at constant tar yield on human puffing measures, nicotine deliveries under human smoking conditions and the sensory response to mainstream cigarette smoke. These assessments would allow an evaluation of the degree of compensation and the various possible causes of changes, if any. Methods. The participants were 13 regular smokers of commercial or hand-rolled cigarettes. They were tested with four cigarettes, which exhibited a wide range of nicotine to 'tar' ratios at a relatively constant 'tar' yield. Their smoking behaviour was monitored by placing the test cigarettes into an orifice-type holder/flowmeter attached to a custom-built smoker behaviour analyser. In addition, a comprehensive sensory evaluation of the products was carried out. Results. The differences in the nicotine to tar ratios of the samples did not significantly influence the puffing behaviour patterns, i.e. puff number and interval, total and average puff volume, integrated pressure and puff duration. Additionally the pre- to post-exhaled CO boosts were not significantly influenced by the experimental samples used in the study. However, the nicotine yields obtained by the smokers were significantly influenced by the machine-smoked nicotine yields or the nicotine to tar ratios of the samples. The machine-smoked nicotine yields were highly correlated with the nicotine yields obtained under human smoking conditions. For the sensory evaluation, there was only a significant difference between the samples in the intensity of the impact. Conclusion. These observations imply that these puffing variables are not controlled by the nicotine yield of the cigarette.

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The externally recorded electroencephalogram (EEG) is contaminated with signals that do not originate from the brain, collectively known as artefacts. Thus, EEG signals must be cleaned prior to any further analysis. In particular, if the EEG is to be used in online applications such as Brain-Computer Interfaces (BCIs) the removal of artefacts must be performed in an automatic manner. This paper investigates the robustness of Mutual Information based features to inter-subject variability for use in an automatic artefact removal system. The system is based on the separation of EEG recordings into independent components using a temporal ICA method, RADICAL, and the utilisation of a Support Vector Machine for classification of the components into EEG and artefact signals. High accuracy and robustness to inter-subject variability is achieved.

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An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.