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Se presenta un resumen del proceso de representación de prácticas en aula utilizando instrumentos análogos y digitales en el desarrollo de ejercicios de diseño, aplicado al programa de arquitectura de la Universidad Antonio Nariño en la ciudad de Ibagué. Esta guía tiene como objetivo contrastar el método de Bruce Archer, estructurado en tres fases:...
En este artículo se describe un proceso proyectual, realizado en el taller de arquitectura de tercer semestre, segundo año, donde se intenta vincular la teoría con la práctica arquitectónica en el contexto específico de cada uno de los proyectos.
Se toma como referencia la vida cotidiana, poniendo al ser humano en el centro del proyecto arquitectón...
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... With respect to flowcharts, UML also models interactions between software systems and hardware systems, as well as with system users and stakeholders. When it is applied to software, UML is a semi-formal language, in the sense that it can automatically produce a set of header files with the description of classes and other objects, ready for code development in a variety of programming languages [111]. ...
Data are often represented as graphs. Many common tasks in data science are based on distances between entities. While some data science methodologies natively take graphs as their input, there are many more that take their input in vectorial form. In this survey, we discuss the fundamental problem of mapping graphs to vectors, and its relation with mathematical programming. We discuss applications, solution methods, dimensional reduction techniques, and some of their limits. We then present an application of some of these ideas to neural networks, showing that distance geometry techniques can give competitive performance with respect to more traditional graph-to-vector mappings.
... With respect to flowcharts, UML also models interactions between software systems and hardware systems, as well as with system users and stakeholders. When it is applied to software, UML is a semi-formal language, in the sense that it can automatically produce a set of header files with the description of classes and other objects, ready for code development in a variety of programming languages [111]. ...
Data are often represented as graphs. Many common tasks in data science are based on distances between entities. While some data science methodologies natively take graphs as their input, there are many more that take their input in vectorial form. In this survey we discuss the fundamental problem of mapping graphs to vectors, and its relation with mathematical programming. We discuss applications, solution methods, dimensional reduction techniques and some of their limits. We then present an application of some of these ideas to neural networks, showing that distance geometry techniques can give competitive performance with respect to more traditional graph-to-vector mappings.
