Hacia una arquitectura de procesos : transformaciones disciplinares a través de la Computación en los modelos de Alexander, Negroponte y Price

La premisa inicial de la tesis examina cómo las secuelas de Segunda Guerra mundial motivaron una revisión general de la Ciencia y procuraron una nueva relación entre el hombre y su entorno. Matemáticas, Física y Biología gestaron las Ciencias de la Computación como disciplina de convergencia. En un momento de re-definición del objeto científico, una serie de arquitectos vislumbraron la oportunidad para transformar ciertas convenciones disciplinares. Mediante la incorporación de ontologías y procedimientos de cibernética y computación, trazaron un nuevo espacio arquitectónico. Legitimados por un despegue tecnológico incuestionable, desafían los límites de la profesión explorando campos abiertos a nuevos programas y acciones; amplían el dominio natural de la Arquitectura más allá del objeto(terminado) hacia el proceso(abierto). Se da inicio a la tesis describiendo los antecedentes que conducen a ese escenario de cambio. Se anotan aspectos de Teoría de Sistemas, Computación, Biología y de ciertos referentes de Arquitectura con relevancia para esa nuevo planteamiento. En esos antecedentes residen los argumentos para orientar la disciplina hacia el trabajo con procesos. La linea argumental central del texto aborda la obra de Christopher Alexander, Nicholas Negroponte y Cedric Price a través de una producción teórica y práctica transformada por la computación, y examina la contribución conceptual de cada autor. El análisis comparado de sus modelos se dispone mediante la disección de tres conceptos convergentes: Sistema, Código y Proceso. La discusión crítica se articula por una triangulación entre los autores, donde se identifican comparando por pares las coincidencias y controversias entre ellos. Sirve este procedimiento al propósito de tender un puente conceptual con el escenario arquitectónico actual estimando el impacto de sus propuestas. Se valora su contribución en la deriva del programa cerrado a la especulación , de lo formal a lo informal, de lo único a lo múltiple; del estudio de arquitectura al laboratorio de investigación. Para guiar ese recorrido por la significación de cada autor en el desarrollo digital de la disciplina, se incorporan a la escena dos predicados esenciales; expertos en computación que trabajaron de enlace entre los autores, matizando el significado de sus modelos. El trabajo de Gordon Pask y John Frazer constituye el vehículo de transmisión de los hallazgos de aquellos años, prolonga los caminos iniciados entonces, en la arquitectura de hoy y la que ya se está diseñando para mañana. ABSTRACT The initial premise of the thesis examines how the aftermath of second world war motivated a general revision of science and procure the basis of a new relation between mankind and its environment. Mathematics, Physics, and Biology gave birth to the Computer Sciences as a blend of different knowledge and procedures. In a time when the object of major sciences was being redefined, a few architects saw a promising opportunity for transforming the Architectural convention. By implementing the concepts, ontology and procedures of Cybernetics, Artificial Intelligence and Information Technology, they envisioned a new space for their discipline. In the verge of transgression three prescient architects proposed complete architectural systems through their writings and projects; New systems that challenged the profession exploring open fields through program and action, questioning the culture of conservatism; They shifted architectural endeavor from object to process. The thesis starts describing the scientific and architectural background that lead to that opportunity, annotating aspects of Systems Theory, Computing, Biology and previous Architecture form the process perspective. It then focuses on the Works of Christopher Alexander, Nicholas Negroponte and Cedric Price through their work, and examines each authors conceptual contribution. It proceeds to a critical analysis of their proposals on three key converging aspects: system, architectural encoding and process. Finally, the thesis provides a comparative discussion between the three authors, and unfolds the impact of their work in todays architectural scenario. Their contribution to shift from service to speculation, from formal to informal , from unitary to multiple; from orthodox architecture studio to open laboratories of praxis through research. In order to conclude that triangle of concepts, other contributions come into scene to provide relevant predicates and complete those models. A reference to Gordon Pask and John Frazer is then provided with particular interest in their role as link between those pioneers and todays perspective, pushing the boundaries of both what architecture was and what it could become.

Normative Practical Reasoning via Argumentation and Dialogue

Postprint

Monitoring compliance with E-contracts and norms

Date of Acceptance: 09/07/2015

Dimensionality Reduction Through Sub-Space Mapping for Nearest Neighbour Algorithms

Postprint

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

Web-based OERs in Computer Networks

Learning and teaching processes are continually changing. Therefore, design of learning technologies has gained interest in educators and educational institutions from secondary school to higher education. This paper describes the successfully use in education of social learning technologies and virtual laboratories designed by the authors, as well as videos developed by the students. These tools, combined with other open educational resources based on a blended-learning methodology, have been employed to teach the subject of Computer Networks. We have verified not only that the application of OERs into the learning process leads to a significantly improvement of the assessments, but also that the combination of several OERs enhances their effectiveness. These results are supported by, firstly, a study of both students’ opinion and students’ behaviour over five academic years, and, secondly, a correlation analysis between the use of OERs and the grades obtained by students.

3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Computer Networks Virtualization with GNS3: Evaluating a solution to optimize resources and achieve a distance learning

Designing educational resources allow students to modify their learning process. In particular, on-line and downloadable educational resources have been successfully used in engineering education the last years [1]. Usually, these resources are free and accessible from web. In addition, they are designed and developed by lecturers and used by their students. But, they are rarely developed by students in order to be used by other students. In this work-in-progress, lecturers and students are working together to implement educational resources, which can be used by students to improve the learning process of computer networks subject in engineering studies. In particular, network topologies to model LAN (Local Area Network) and MAN (Metropolitan Area Network) are virtualized in order to simulate the behavior of the links and nodes when they are interconnected with different physical and logical design.

Experiences Using an Open Source Sofware Library to Teach Computer Vision Subjects

Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with enfasis on readability and understanding rather than on efficiency. However, the library can also be used for research purposes. JavaVis is an open source Java library, oriented to the teaching of Computer Vision. It consists of a framework with several features that meet its demands. It has been designed to be easy to use: the user does not have to deal with internal structures or graphical interface, and should the student need to add a new algorithm it can be done simply enough. Once we sketch the library, we focus on the experience the student gets using this library in several computer vision courses. Our main goal is to find out whether the students understand what they are doing, that is, find out how much the library helps the student in grasping the basic concepts of computer vision. In the last four years we have conducted surveys to assess how much the students have improved their skills by using this library.

An Electronic Reconfigurable Neural Architecture for Intrusion Detection

The explosive growth of the traffic in computer systems has made it clear that traditional control techniques are not adequate to provide the system users fast access to network resources and prevent unfair uses. In this paper, we present a reconfigurable digital hardware implementation of a specific neural model for intrusion detection. It uses a specific vector of characterization of the network packages (intrusion vector) which is starting from information obtained during the access intent. This vector will be treated by the system. Our approach is adaptative and to detecting these intrusions by using a complex artificial intelligence method known as multilayer perceptron. The implementation have been developed and tested into a reconfigurable hardware (FPGA) for embedded systems. Finally, the Intrusion detection system was tested in a real-world simulation to gauge its effectiveness and real-time response.

Artificial event

IMB (Irvine, Michigan, Brookline), a collaboration between the University of Michigan, the University of California at Irvine, and the U.S. Department of Energy, was an experiment designed to determine the ultimate stability of matter. Computer display of PMT [photomultiplier tubes] hits from simulated event based on neutrino interatction seen in Gargamelle bubble chamber.

Artificial event

IMB (Irvine, Michigan, Brookline), a collaboration between the University of Michigan, the University of California at Irvine, and the U.S. Department of Energy, was an experiment designed to determine the ultimate stability of matter. Computer display of simulated proton decay info (...) mode

Artificial event

IMB (Irvine, Michigan, Brookline), a collaboration between the University of Michigan, the University of California at Irvine, and the U.S. Department of Energy, was an experiment designed to determine the ultimate stability of matter. Computer display of simulated event based on Gargamelle (...) event produced by neutrino interaction.