Towards homeostatic architecture: simulation of the generative process of a termite mound construction

This report sets out to the theme of the generation of a ‘living’, homeostatic and self-organizing architectural structure. The main research question this project addresses is what innovative techniques of design, construction and materials could prospectively be developed and eventually applied to create and sustain human-made buildings which are mostly adaptive, self-controlled and self-functioning, without option to a vast supply of materials and peripheral services. The hypothesis is that through the implementation of the biological building behaviour of termites, in terms of collective construction mechanisms that are based on environmental stimuli, we could achieve a simulation of the generative process of their adaptive structures, capable to inform in many ways human construction. The essay explicates the development of the 3-dimensional, agent-based simulation of the termite collective construction and analyzes the results, which involve besides physical modelling of the evolved structures. It finally elucidates the potential of this emerging and adaptive architectural performance to be translated to human practice and thus enlighten new ecological engineering and design methodologies

LoCoH: nonparameteric kernel methods for constructing home ranges and utilization distributions.

Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: "fixed sphere-of-influence," or r-LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an "adaptive sphere-of-influence," or a-LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a), and compare them to the original "fixed-number-of-points," or k-LoCoH (all kernels constructed from k-1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a-LoCoH is generally superior to k- and r-LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu)

Unconstrained video monitoring of breathing behavior and application to diagnosis of sleep apnea

This paper presents a new real-time automated infrared video monitoring technique for detection of breathing anomalies, and its application in the diagnosis of obstructive sleep apnea. We introduce a novel motion model to detect subtle, cyclical breathing signals from video, a new 3-D unsupervised self-adaptive breathing template to learn individuals' normal breathing patterns online, and a robust action classification method to recognize abnormal breathing activities and limb movements. This technique avoids imposing positional constraints on the patient, allowing patients to sleep on their back or side, with or without facing the camera, fully or partially occluded by the bed clothes. Moreover, shallow and abdominal breathing patterns do not adversely affect the performance of the method, and it is insensitive to environmental settings such as infrared lighting levels and camera view angles. The experimental results show that the technique achieves high accuracy (94% for the clinical data) in recognizing apnea episodes and body movements and is robust to various occlusion levels, body poses, body movements (i.e., minor head movement, limb movement, body rotation, and slight torso movement), and breathing behavior (e.g., shallow versus heavy breathing, mouth breathing, chest breathing, and abdominal breathing). © 2013 IEEE

The Spanish Gitanos of Mexico City: Rhythmicity, Mimesis and Domestication of the Payos

This text addresses a tentative approach to groups in Mexico such as the Roma, who remain poorly known. The analysis focuses on problematizing the particular cultural and economic reproduction strategies of an urban group of Gitanos (Calós) in Mexico City. Greater attention is placed particularly onthe performance and the mimesis in economic exchange with the Payos (non-Gitanos). The idea is that the processes of cultural identification refer to the basic Caló social universe, which reveals epistemological beliefs and assumptions shared by the group in relation to the Payo universe. The idea is that the Calós construct idealized models of the real world during everyday experience in the ecological context within the community. Instead, it relates to the direct perceptual involvement of subjects in a relational context of shared patterns of daily activities in environments that are experienced. The effect is the domestication of the Payo’s world

Learning about a Moving Target in Resource Management: Optimal Bayesian Disease Control

Resource managers must often make difficult choices in the face of imperfectly observed and dynamically changing systems (e.g., livestock, fisheries, water, and invasive species). A rich set of techniques exists for identifying optimal choices when that uncertainty is assumed to be understood and irreducible. Standard optimization approaches, however, cannot address situations in which reducible uncertainty applies to either system behavior or environmental states. The adaptive management literature overcomes this limitation with tools for optimal learning, but has been limited to highly simplified models with state and action spaces that are discrete and small. We overcome this problem by using a recently developed extension of the Partially Observable Markov Decision Process (POMDP) framework to allow for learning about a continuous state. We illustrate this methodology by exploring optimal control of bovine tuberculosis in New Zealand cattle. Disease testing—the control variable—serves to identify herds for treatment and provides information on prevalence, which is both imperfectly observed and subject to change due to controllable and uncontrollable factors. We find substantial efficiency losses from both ignoring learning (standard stochastic optimization) and from simplifying system dynamics (to facilitate a typical, simple learning model), though the latter effect dominates in our setting. We also find that under an adaptive management approach, simplifying dynamics can lead to a belief trap in which information gathering ceases, beliefs become increasingly inaccurate, and losses abound

Sustaining entrepreneurial business: a complexity perspective on processes that produce emergent practice

This article examines the management practices in an entrepreneurial small firm which sustain the business. Using a longitudinal qualitative case study, four general processes are identified (experimentation, reflexivity, organising and sensing), that together provide a mechanism to sustain the enterprise. The analysis draws on concepts from entrepreneurship and complexity science. We suggest that an entrepreneur’s awareness of the role of these parallel processes will facilitate their approaches to sustaining and developing enterprises. We also suggest that these processes operate in parallel at multiple levels, including the self, the business and inter-firm networks. This finding contributes to a general theory of entrepreneurship. A number of areas for further research are discussed arising from this result

Recovering industrial heritage: restoration of the wine cellar cooperative in Falset (Catalonia, Spain)

Awareness regarding conservation of industrial heritage is recent. Several policies have been adopted to start protecting these buildings because of their historic, artistic and scientific values. Wine cellars are an important example of industrial heritage in Catalonia due to the tradition of this product in the territory and the influence of Art Nouveau and Catalan ‘Noucentisme’ in their construction and style. The wine cellar in Falset, built by Cèsar Martinell in 1919, has recently been restored and still maintains its original function. This article analyses its history, its architectonic and construction characteristics, as well as the restoration process carried out in 2009, which consisted of recovering its original appearance and allowed to emphasize the architectural value of the building. This restoration is a prototypical example whose experience can be applied in other cases of restoration of wine cellars both for the characteristics of the building and for its good restoration practices. This restoration enabled the wine cellar to continue carrying out its original industrial function, providing suitable conditions to add a new cultural use as wellPeer ReviewedPostprint (author's final draft