Pattern-based topics for document modelling in information filtering

Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models

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.

HeatWave : a handheld 3D thermography system for energy auditing

Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.

The 2013 creative industries statistical analysis for Western Australia

The Department of Culture and the Arts undertook the first mapping of Perth’s creative industries in 2007 in partnership with the City of Perth and the Departments of Industry and Resources and the Premier and Cabinet. The 2013 Creative Industries Statistical Analysis for Western Australia report has updated the mapping with the 2011 Census employment data to provide invaluable information for the State’s creative industries, their peak associations and potential investors. The report maps sector employment numbers and growth between the 2006 and 2011 Census in the areas of music, visual and performing arts, film, TV and radio, advertising and marketing, software and digital content, publishing, and architecture and design, which includes designer fashion.

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.

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.

A recurrent network in the lateral amygdala : a mechanism for coincidence detection

Synaptic changes at sensory inputs to the dorsal nucleus of the lateral amygdala (LAd) play a key role in the acquisition and storage of associative fear memory. However, neither the temporal nor spatial architecture of the LAd network response to sensory signals is understood. We developed a method for the elucidation of network behavior. Using this approach, temporally patterned polysynaptic recurrent network responses were found in LAd (intra-LA), both in vitro and in vivo, in response to activation of thalamic sensory afferents. Potentiation of thalamic afferents resulted in a depression of intra-LA synaptic activity, indicating a homeostatic response to changes in synaptic strength within the LAd network. Additionally, the latencies of thalamic afferent triggered recurrent network activity within the LAd overlap with known later occurring cortical afferent latencies. Thus, this recurrent network may facilitate temporal coincidence of sensory afferents within LAd during associative learning.

The epidemiology of basal cell carcinoma

Basal cell carcinoma (BCC) is a skin cancer of particular importance to the Australian community. Its rate of occurrence is highest in Queensland, where 1% to 2% of people are newly affected annually. This is an order of magnitude higher than corresponding incidence estimates in European and North American populations. Individuals with a sun-sensitive complexion are particularly susceptible because sun exposure is the single most important causative agent, as shown by the anatomic distribution of BCC which is in general consistent with the levels of sun exposure across body sites. A distinguishing feature of BCC is the occurrence of multiple primary tumours within individuals, synchronously or over time, and their diagnosis and treatment costs contribute substantially to the major public health burden caused by BCC. A primary knowledge gap about BCC pathogenesis however was an understanding of the true frequency of multiple BCC occurrences and their body distribution, and why a proportion of people do develop more than one BCC in their life. This research project sought to address this gap under an overarching research aim to better understand the detailed epidemiology of BCC with the ultimate goal of reducing the burden of this skin cancer through prevention. The particular aim was to document prospectively the rate of BCC occurrence and its associations with constitutional and environmental (solar) factors, all the while paying special attention to persons affected by more than one BCC. The study built on previous findings and recent developments in the field but set out to confirm and extend these and propose more adequate theories about the complex epidemiology of this cancer. Addressing these goals required a new approach to researching basal cell carcinoma, due to the need to account for the phenomenon of multiple incident BCCs per person. This was enabled by a 20 year community-based study of skin cancer in Australians that provided the methodological foundation for this thesis. Study participants were originally randomly selected in 1986 from the electoral register of all adult residents of the subtropical township of Nambour in Queensland, Australia. On various occasions during the study, participants were fully examined by dermatologists who documented cumulative photodamage as well as skin cancers. Participants completed standard questionnaires about skin cancer-related factors, and consented to have any diagnosed skin cancers notified to the investigators by regional pathology laboratories in Queensland. These methods allowed 100% ascertainment of histologically confirmed BCCs in this study population. 1339 participants had complete follow-up to the end of 2007. Statistical analyses in this thesis were carried out using SAS and SUDAAN statistical software packages. Modelling methods, including multivariate logistic regressions, allowed for repeated measures in terms of multiple BCCs per person. This innovative approach gave new findings on two levels, presented in five chapters as scientific papers: 1. Incidence of basal cell carcinoma multiplicity and detailed anatomic distribution: longitudinal study of an Australian population The incidence of people affected multiple times by BCC was 705 per 100,000 person years compared to an incidence rate of people singly affected of 935 per 100,000 person years. Among multiply and singly affected persons alike, site-specific BCC incidence rates were far highest on facial subsites, followed by upper limbs, trunk, and then lower limbs 2. Melanocytic nevi and basal cell carcinoma: is there an association? BCC risk was significantly increased in those with forearm nevi (Odds Ratios (OR) 1.43, 95% Confidence Intervals (CI) 1.09-1.89) compared to people without forearm nevi, especially among those who spent their time mainly outdoors (OR 1.6, 95%CI 1.1-2.3) compared to those who spent their time mainly indoors. Nevi on the back were not associated with BCC. 3. Clinical signs of photodamage are associated with basal cell carcinoma multiplicity and site: a 16-year longitudinal study Over a 16-year follow-up period, 58% of people affected by BCC developed more than one BCC. Among these people 60% developed BCCs across different anatomic sites. Participants with high numbers of solar keratoses, compared to people without solar keratoses, were most likely to experience the highest BCC counts overall (OR 3.3, 95%CI 1.4-13.5). Occurrences of BCC on the trunk (OR 3.3, 95%CI 1.4-7.6) and on the limbs (OR 3.7, 95%CI 2.0-7.0) were strongly associated with high numbers of solar keratoses on these sites. 4. Occurrence and determinants of basal cell carcinoma by histological subtype in an Australian community Among 1202 BCCs, 77% had a single growth pattern and 23% were of mixed histological composition. Among all BCCs the nodular followed by the superficial growth patterns were commonest. Risk of nodular and superficial BCCs on the head was raised if 5 or more solar keratoses were present on the face (OR 1.8, 95%CI 1.2-2.7 and OR 4.5, 95%CI 2.1-9.7 respectively) and similarly on the trunk in the presence of multiple solar keratoses on the trunk (OR 4.2, 95%CI 1.5-11.9 and OR 2.2, 95%CI 1.1-4.4 respectively). 5. Basal cell carcinoma and measures of cumulative sun exposure: an Australian longitudinal community-based study Dermal elastosis was more likely to be seen adjacent to head and neck BCCs than trunk BCCs (p=0.01). Severity of dermal elastosis increased on each site with increasing clinical signs of cutaneous sun damage on that site. BCCs that occurred without perilesional elastosis per se, were always found in an anatomic region with signs of photodamage. This thesis thus has identified the magnitude of the burden of multiple BCCs. It does not support the view that people affected by more than one BCC represent a distinct group of people who are prone to BCCs on certain body sites. The results also demonstrate that BCCs regardless of site, histology or order of occurrence are strongly associated with cumulative sun exposure causing photodamage to the skin, and hence challenge the view that BCCs occurring on body sites with typically low opportunities for sun exposure or of the superficial growth pattern are different in their association with the sun from those on typically sun-exposed sites, or nodular BCCs, respectively. Through dissemination in the scientific and medical literature, and to the community at large, these findings can ultimately assist in the primary and secondary prevention of BCC, perhaps especially in high-risk populations.

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.