Computers are becoming indispensable for manipulating most everyday consumer products, ranging from communications and domestic electronics to industrial processes monitoring and control. High performance computer design is not only subject to the technology used for its implementation, it is also a matter of efficient training. The skills that must prevail in a good computer designer come from the type of courses taken and the tools employed during them. This work shows the design of an 8-bit RISC soft-core processor dedicated to a complete understanding of computer architecture. We consider this Processor an effective hands-on training solution for the comprehension of a computer from its lowest level up to testing.

Resumen-En este documento se presenta un método para medir la distancia del centroide de un objeto segmentado en una imagen de color con respecto a un punto de referencia fijo. El algoritmo se probó mediante una secuencia de imágenes de color, analizando más de 100 posiciones verticales diferentes de una esfera alojada en el interior de una columna cilíndrica transparente de acrílico con diámetro y longitud constante. El algoritmo propuesto integra técnicas de corrección por balance de blancos y de calibración de la cámara con sus parámetros intrínsecos, además, se prueba un nuevo método de segmentación en color utilizado para calcular distancias del mundo real a partir de imágenes en color RGB. Los resultados obtenidos reflejan una alta confiabilidad ya que el 100% de las mediciones realizadas tuvo un error menor a 1.64% con un nivel de precisión más alto que el instrumento utilizado de referencia, en un rango de distancia de 0 a 1340 mm. Palabras clave-Fotogrametría, medición de distancias en imágenes, sensor visual de distancias, metrología visual de simple vista, segmentación, seguimiento de objetos.

Knowledge-based systems have the ability to realize inferences out of pre-defined rules. As the antecedents are driven into the fuzzy system, the system infers to obtain the consequents. These consequents are used to obtain crisp output data. The aggregation operator combines these consequents to obtain a unified shape from which a unique result can be obtained. The way to handle the aggregation varies according to the type of membership functions involved. This paper presents a way of realizing aggregation operation when the membership functions are represented by means of α-levels, showing that this case is suitable for discrete fuzzy system implementations.

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