Informatic Opacity: Biometric Facial Recognition and the Aesthetics and Politics of Defacement

Confronting the rapidly increasing, worldwide reliance on biometric technologies to surveil, manage, and police human beings, my dissertation Informatic Opacity: Biometric Facial Recognition and the Aesthetics and Politics of Defacement charts a series of queer, feminist, and anti-racist concepts and artworks that favor opacity as a means of political struggle against surveillance and capture technologies in the 21st century. Utilizing biometric facial recognition as a paradigmatic example, I argue that today's surveillance requires persons to be informatically visible in order to control them, and such visibility relies upon the production of technical standardizations of identification to operate globally, which most vehemently impact non- normative, minoritarian populations. Thus, as biometric technologies turn exposures of the face into sites of governance, activists and artists strive to make the face biometrically illegible and refuse the political recognition biometrics promises through acts of masking, escape, and imperceptibility. Although I specifically describe tactics of making the face unrecognizable as "defacement," I broadly theorize refusals to visually cohere to digital surveillance and capture technologies' gaze as "informatic opacity," an aesthetic-political theory and practice of anti- normativity at a global, technical scale whose goal is maintaining the autonomous determination of alterity and difference by evading the quantification, standardization, and regulation of identity imposed by biometrics and the state. My dissertation also features two artworks: Facial Weaponization Suite, a series of masks and public actions, and Face Cages, a critical, dystopic installation that investigates the abstract violence of biometric facial diagramming and analysis. I develop an interdisciplinary, practice-based method that pulls from contemporary art and aesthetic theory, media theory and surveillance studies, political and continental philosophy, queer and feminist theory, transgender studies, postcolonial theory, and critical race studies.

Facial and expression recognition for the blind using computer vision

Gemstone Team FACE

Production and recognition bias of stylistic sentences using a story reading task.

Four experiments examined participants' ability to produce surface characteristics of sentences using an on-line story reading task. Participants read a series of stories in which either all, or the majority of sentences were written in the same "style," or surface form. Twice per story, participants were asked to fill in a blank consistent with the story. For sentences that contained three stylistic regularities, participants imitated either all three characteristics (Experiment 2) or two of the three characteristics (Experiment 1), depending on the proportion of in-style sentences. Participants demonstrated a recognition bias for the read style in an unannounced recognition task. When participants read stories in which the two styles were the dative/double object alternation, participants demonstrated a syntactic priming effect in the cloze task, but no consistent recognition bias in a later recognition test (Experiments 3 and 4).

Recognition of Planar Segments in Point Cloud Based on Wavelet Transform

© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.

Differential scanning calorimetry in life science: thermodynamics, stability, molecular recognition and application in drug design

All biological phenomena depend on molecular recognition, which is either intermolecular like in ligand binding to a macromolecule or intramolecular like in protein folding. As a result, understanding the relationship between the structure of proteins and the energetics of their stability and binding with others (bio)molecules is a very interesting point in biochemistry and biotechnology. It is essential to the engineering of stable proteins and to the structure-based design of pharmaceutical ligands. The parameter generally used to characterize the stability of a system (the folded and unfolded state of the protein for example) is the equilibrium constant (K) or the free energy (deltaG(o)), which is the sum of enthalpic (deltaH(o)) and entropic (deltaS(o)) terms. These parameters are temperature dependent through the heat capacity change (deltaCp). The thermodynamic parameters deltaH(o) and deltaCp can be derived from spectroscopic experiments, using the van't Hoff method, or measured directly using calorimetry. Along with isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC) is a powerful method, less described than ITC, for measuring directly the thermodynamic parameters which characterize biomolecules. In this article, we summarize the principal thermodynamics parameters, describe the DSC approach and review some systems to which it has been applied. DSC is much used for the study of the stability and the folding of biomolecules, but it can also be applied in order to understand biomolecular interactions and can thus be an interesting technique in the process of drug design.

Binary life after the AGB - Towards a unified picture

We attempt to construct a unified evolutionary scheme that includes post-AGB systems, barium stars, symbiotics and related systems, explaining their similarities as well as their differences. Special attention is given to the comparison of the barium pollution and symbiotic phenomena. Finally, we outline a 'transient torus' evolutionary scenario that makes use of the various observational and theoretical hints and aims at explaining the observed characteristics of the relevant systems.

Idiotypic networks and self-recognition in the immune system.

Journal Article

The UK 9/11 evacuation study: Analysis of survivors’ recognition and response phase in WTC1

The September 11th 2001 impact on the World Trade Centre (WTC) resulted in one of the most significant evacuations of a high-rise building in modern times. The UK High-rise Evacuation Evaluation Database (HEED) study aimed to capture and collate the experiences and behaviours of WTC evacuees in a database, which would facilitate and encourage future research, which in turn would influence the design construction and use of safer built environments. A data elicitation tool designed for the purpose comprised a pre-interview questionnaire followed by a one-to-one interview protocol consisting of free-flow narratives and semi-structured interviews of WTC evacuees. This paper, which is one in a series dealing with issues relating to the successful evacuations of towers 1 and 2, focuses on cue recognition and response patterns within WTC1. Results are presented by vertical floor clusters and include information regarding cues experienced, activities prior and subsequent to occupants first becoming aware that something was wrong, perceived personal risk, time taken to respond and the inter-relationships between them. The results indicate differences in occupant activities across the floor clusters and suggest that these differences can be explained in terms of the perception of risk and the nature and extent of cues received by the participants.

Temporal pattern recognition in video clips detection

Temporal representation and reasoning plays an important role in Data Mining and Knowledge Discovery, particularly, in mining and recognizing patterns with rich temporal information. Based on a formal characterization of time-series and state-sequences, this paper presents the computational technique and algorithm for matching state-based temporal patterns. As a case study of real-life applications, zone-defense pattern recognition in basketball games is specially examined as an illustrating example. Experimental results demonstrate that it provides a formal and comprehensive temporal ontology for research and applications in video events detection.

‘Nothing will prevent me from doing a good job’. The professionalisation of part-time teaching staff in further and adult education

Approximately 85,000 part-time teaching staff working in further education (FE) and adult and community learning (ACL) are often seen as ‘a problem’. The intrinsic ‘part-timeness’ of these staff tends to marginalise them: they remain under-recognised and largely unsupported. Yet this picture is over-simplified. This article examines how part-time staff make creative use of professional autonomy and agency to mitigate problematic ‘casual employment’ conditions, reporting on results from Learning and Skills Development Agency-sponsored research (2002–2006) with 700 part-time staff in the learning and skills sector. The question of agency was reported as a key factor in part-time employment. Change is necessary for the professional agency of part-timers to be harnessed as the sector responds to ambitious sectoral ‘improvement’ agendas following the Foster Report and FE White Paper. Enhanced professionalisation for part-time staff needs greater recognition and inclusion in change agendas.

Towards Real-time Speech Emotion Recognition for Affective E-Learning

The original article is available as an open access file on the Springer website in the following link: http://link.springer.com/article/10.1007/s10639-015-9388-2

Relating sardine recruitment in the Northern Benguela to satellite-derived sea surface height using a neural network pattern recognition approach

Processes of enrichment, concentration and retention are thought to be important for the successful recruitment of small pelagic fish in upwelling areas, but are difficult to measure. In this study, a novel approach is used to examine the role of spatio-temporal oceanographic variability on recruitment success of the Northern Benguela sardine Sardinops sagax. This approach applies a neural network pattern recognition technique, called a self-organising map (SOM), to a seven-year time series of satellite-derived sea level data. The Northern Benguela is characterised by quasi-perennial upwelling of cold, nutrient-rich water and is influenced by intrusions of warm, nutrient-poor Angola Current water from the north. In this paper, these processes are categorised in terms of their influence on recruitment success through the key ocean triad mechanisms of enrichment, concentration and retention. Moderate upwelling is seen as favourable for recruitment, whereas strong upwelling, weak upwelling and Angola Current intrusion appear detrimental to recruitment success. The SOM was used to identify characteristic patterns from sea level difference data and these were interpreted with the aid of sea surface temperature data. We found that the major oceanographic processes of upwelling and Angola Current intrusion dominated these patterns, allowing them to be partitioned into those representing recruitment favourable conditions and those representing adverse conditions for recruitment. A marginally significant relationship was found between the index of sardine recruitment and the frequency of recruitment favourable conditions (r super(2) = 0.61, p = 0.068, n = 6). Because larvae are vulnerable to environmental influences for a period of at least 50 days after spawning, the SOM was then used to identify windows of persistent favourable conditions lasting longer than 50 days, termed recruitment favourable periods (RFPs). The occurrence of RFPs was compared with back-calculated spawning dates for each cohort. Finally, a comparison of RFPs with the time of spawning and the index of recruitment showed that in years where there were 50 or more days of favourable conditions following spawning, good recruitment followed (Mann-Whitney U-test: p = 0.064, n = 6). These results show the value of the SOM technique for describing spatio-temporal variability in oceanographic processes. Variability in these processes appears to be an important factor influencing recruitment in the Northern Benguela sardine, although the available data time series is currently too short to be conclusive. Nonetheless, the analysis of satellite data, using a neural network pattern-recognition approach, provides a useful framework for investigating fisheries recruitment problems.