Architecture for a free subjectivity

In October 2012, Simone presented her book Architecture for a Free Subjectivity to the University of Michigan, Taubman College of Architecture and Urban Planning. This book explores the architectural significance of Deleuze’s philosophy of subjectivization, and Guattari’s overlooked dialogue on architecture and subjectivity. In doing so, it proposes that subjectivity is no longer the exclusive provenance of human beings, but extends to the architectural, the cinematic, the erotic, and the political. It defines a new position within the literature on Deleuze and architecture, while highlighting the neglected issue of subjectivity in contemporary discussion.

Volcanic architecture and chemostratigraphy within the Kalkarindji Continental Flood Basalt Province, Northern Territory : implications for eruption style from multiple fissure eruptions

This thesis was the first to define individual lava flow chemical variation and a detailed definition of the Kalkarindji Continental Flood Basalt Province, a lesser known province of the Phanerozoic eon. This thesis conducted an intensive field study that yielded numerous samples for petrography and chemical analyses as well as the generation of a detailed map of a portion of the Kalkarindji province.

The subject and architecture

Invited Presentation on my book Architecture for a Free Subjectivity. In March of 1982, Skyline, the Institute for Architecture and Urban Studies serial, published the landmark interview between Paul Rabinow, an American anthropologist, and Michel Foucault, which would only appear two years later under the title “Space, Knowledge, and Power,” in Rabinow’s edited book The Foucault Reader. Foucault said that in the spatialization of knowledge and power beginning in the 18th century, architecture is not a signifier or metaphor for power, it is rather the “technique for practising social organization.” The role of the IAUS in the architectural dissemination of Foucault’s ideas on the subject and space in the North American academy – such as the concept “heterotopia,” and Foucault’s writing on surveillance and Jeremy Bentham’s Panopticon, subsequently analysed by Georges Teyssot, who was teaching at the Venice School – is well known. Teyssot’s work is part of the historical canalization of Foucauldianism, and French subjectivity more broadly, along its dizzying path, via Italy, to American architecture schools, where it solidified in the 1980s paradigm that would come to be known as American architecture theory. Foucault was already writing on incarceration and prisons, from the 1970s. (In the 1975 lectures he said “architecture was responsible for the invention of madness.”) But this work was not properly incorporated into architectural discussion until the early ’80s. What is not immediately apparent, what this history suggests to me is that subjectivity was not a marginal topic within “theory”, but was perhaps a platform and entry point for architecture theory. One of the ideas that I’m working on is that “theory” can be viewed, historically, as the making of architectural subjectivity, something that can be traced back to the Frankfurt School critique which begins with the modern subject...

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Cross-layer design for traffic management in wireless networked control systems

Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.

An Interview with John Rajchman, Department of Art History, Columbia University, on Architecture, Deleuze and Foucault

An Interview with John Rajchman, Department of Art History, Columbia University, on Architecture, Deleuze and Foucault at his apartment, Riverside Drive, New York City, February 10, 2003.

Subjectivizations : Deleuze and Architecture

My thesis is an exploration of the architectural production surrounding the French philosopher Gilles Deleuze, specifically, through the overarching theme of Deleuze’s theory of subjectivity, which I will call subjectivization. I interpret this to mean the strange coalescence of matter, architectural subject, and event, in architectural experience and culture. I speculate that subjectivization presents a yet under-explored dimension of deleuzianism in architecture. In order to develop this I pursue two independent trajectories: firstly the narrative of architectural production surrounding Deleuze, from the 1970s until today, as it is an emergence of changing groupings, alliances, formations and disbandment in the pursuit of creative-intellectual tasks—what might be called the subjectivization of architecture—and, secondly, through a speculation about the architecture of subjectivization—that is, an attempt to explore, concretely, what might be the space and time of subjectivization. Chapter One traces an oral history of deleuzianism in architecture, through conversations with Sanford Kwinter and John Rajchman, describing how the Deleuze milieu makes its way into architectural practice and discussion—subjectivization as a social and cultural emergence—whereas Chapter Two theorizes the emergence of an architectural subjectivity where architecture constitutes its own affective event—what I call subjectivization or material becoming-subject.

Handheld 3D thermography using range sensing and computer vision

This thesis developed a method for real-time and handheld 3D temperature mapping using a combination of off-the-shelf devices and efficient computer algorithms. It contributes a new sensing and data processing framework to the science of 3D thermography, unlocking its potential for application areas such as building energy auditing and industrial monitoring. New techniques for the precise calibration of multi-sensor configurations were developed, along with several algorithms that ensure both accurate and comprehensive surface temperature estimates can be made for rich 3D models as they are generated by a non-expert user.

Representations for evolutionary design modelling

This research looked at using the metaphor of biological evolution as a way of solving architectural design problems. Drawing from fields such as language grammars, algorithms and cellular biology, this thesis looked at ways of encoding design information for processing. The aim of this work is to help in the building of software that support the architectural design process and allow designers to examine more variations.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Vision-based docking using an autonomous surface vehicle

This paper describes the development of a novel vision-based autonomous surface vehicle with the purpose of performing coordinated docking manoeuvres with a target, such as an autonomous underwater vehicle, at the water's surface. The system architecture integrates two small processor units; the first performs vehicle control and implements a virtual force based docking strategy, with the second performing vision-based target segmentation and tracking. Furthermore, the architecture utilises wireless sensor network technology allowing the vehicle to be observed by, and even integrated within an ad-hoc sensor network. Simulated and experimental results are presented demonstrating the autonomous vision- based docking strategy on a proof-of-concept vehicle.

Consultant engagement for computer system selection: a pro-active client role in small enterprises

Because of their limited number of senior positions and fewer alternative career paths, small businesses have a more difficult time attracting and retaining skilled information systems (IS) staff and are thus dependent upon external expertise. Small businesses are particularly dependent on outside expertise when first computerizing. Because small businesses suffer from severe financial constraints. it is often difficult to justify the cost of custom software. Hence. for many small businesses, engaging a consultant to help with identifying suitable packaged software and related hardware, is their first critical step toward computerization. This study explores the importance of proactive client involvement when engaging a consultant to assist with computer system selection in small businesses. Client involvement throughout consultant engagement is found to be integral to project success and frequently lacking due to misconceptions of small businesses regarding their role. Small businesses often overestimate the impact of consultant and vendor support in achieving successful computer system selection and implementation. For consultant engagement to be successful, the process must be viewed as being directed toward the achievement of specific organizational results where the client accepts responsibility for direction of the process.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.