Queer criminology, critique, and the "art of not being governed"

This article builds on previous work that argues that a useful path for a ‘‘queer/ed criminology’’ to follow is one that takes ‘‘queer’’ to denote a position. It suggests that one way of developing such an approach is to adopt a particular understanding of critique—specifically one that draws from Michel Foucault’s view of critique as ‘‘the art of not being governed.’’ It then charts some of the possible directions for such a ‘‘queer/ed criminology.’’ While such an approach to critique has previously been discussed within critical criminologies, this article suggests that it is useful for queer criminologists to explore the opportunities that it affords, particularly in order to better appreciate how ‘‘queer/ed criminology’’ might connect to, draw from, or push against other currents among critical criminologies, and help to delineate the unique contribution that this kind of ‘‘queer/ed criminology’’ might make.

Democracy and the Project of Liberal Inclusion

Democracy is a multi-dimensional concept, ranging from definitions based exclusively on institutional frameworks (for example, Held, 2005, Przeworski, Alvarez, Cheibub and Limongi, 2000) to complex and integrated measures that include political and civil rights, democratic practices, values and, finally, a diverse set of institutional arrangements in society, including welfare, education, industrial relations and the legal system (Inglehart and Welzel, 2005, Jaggers and Gurr, 1995, O'Donnell, Cullel and Iazetta, 2004). This reflects the range of and distinction between merely formal electoral democracy and genuinely 'effective liberal democracy' (Inglehart and Welzel, 2005: 149), where democracy is firmly embedded not only in its institutions but in the values of its citizenry. Evidence from cross-national research confirms that formal democratic institutions, different dimensions of effective democracy, and democratic values are indeed strongly linked (Inglehart and Welzel, 2005: 154, Jaggers and Gurr, 1995: 446). Democracy is more than just a set of institutions, rules and mechanisms: it is a set of core values engrained in the 'lived experience' of its citizens. Core values of democracies are individual autonomy and egalitarianism, tolerance of diversity, and freedom from oppression for both individuals and institutions. Democracies restrain their governments by the rule of law and grant its citizens equal access to and equal treatment by legal institutions. Among these institutions, criminal justice and the treatment of those who violated rules and regulations represent sensitive seismographs for the quality of effective democracies, and the ways how democracies realise their core values.

Against Rehabilitation; For Reparitive Justice

The difficulties of re-imagining the possible relationships between crime and justice in capitalist societies, and imagining the possible meanings of democracy in societies characterised by gross inequalities of knowledge, and exclusion of the majority from political decisions are well known. One such difficulty stems from the impossible necessity of maintaining stances of both constant reform and constant critique (see Carlen, 2012). Confronted with economic and cultural inequalities which routinely deny ideals of justice and democracy, there can be a temptation to suppress (or bracket-off) troubling knowledge of criminal justice's and democracy's maligned underbellies and instead talk 'as if' criminal justice's ideal play of governance is always and already realised in its rhetoric. In some senses, this 'as if' talk is aspirational and it is difficult to see how it could be otherwise if more just conceptions of criminal justice and more democratic forms of democracy are to be conceived. However, when, as often happens, aspirational criminal justice concepts become routinised and acted upon as if they can be realised without fundamental social change, they become penal imaginaries, part of a taken-for-granted ideological baggage which, because it is taken-for-granted, obstructs critique (see Carlen, 2008). One such penal imaginary is the concept of rehabilitation, a concept which has a long history of justifying almost every kind of non-lethal response to lawbreaking and which is currently being reborn yet again in theories of criminal desistance and anti-prison campaigns as well as in the more invidious rehabilitation industry with its sales of programmes for cognitive reform.

A novel energy efficient controllable stiffness joint

Achieving energy efficient legged locomotion is an important goal for the future of robot mobility. This paper presents a novel joint for legged locomotion that is energy efficient for two reasons. The first reason is the configuration of the elastic elements and actuator which we show analytically has lower energy losses than the typical arrangement. The second is that the joint stiffness, and hence stance duration, is controllable without requiring any energy from the actuator. Further, the joint stiffness can be changed significantly during the flight phase, from zero to highly rigid. Results obtained from a prototype hopper, demonstrate that the joint allows continuous and peak hopping via torque control. The results also demonstrate that the hopping frequency can be varied between 2.2Hz and 4.6Hz with associated stance duration of between 0.35 and 0.15 seconds.

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals

Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Bearing Fault Diagnostics Using the Spectral Pattern Recognition

In the field of diagnostics of rolling element bearings, the development of sophisticated techniques, such as Spectral Kurtosis and 2nd Order Cyclostationarity, extended the capability of expert users to identify not only the presence, but also the location of the damage in the bearing. Most of the signal-analysis methods, as the ones previously mentioned, result in a spectrum-like diagram that presents line frequencies or peaks in the neighbourhood of some theoretical characteristic frequencies, in case of damage. These frequencies depend only on damage position, bearing geometry and rotational speed. The major improvement in this field would be the development of algorithms with high degree of automation. This paper aims at this important objective, by discussing for the first time how these peaks can draw away from the theoretical expected frequencies as a function of different working conditions, i.e. speed, torque and lubrication. After providing a brief description of the peak-patterns associated with each type of damage, this paper shows the typical magnitudes of the deviations from the theoretical expected frequencies. The last part of the study presents some remarks about increasing the reliability of the automatic algorithm. The research is based on experimental data obtained by using artificially damaged bearings installed in a gearbox.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

A novel method for analysing lighting variance

Robust descriptor matching across varying lighting conditions is important for vision-based robotics. We present a novel strategy for quantifying the lighting variance of descriptors. The strategy works by utilising recovered low dimensional mappings from Isomap and our measure of the lighting variance of each of these mappings. The resultant metric allows different descriptors to be compared given a dataset and a set of keypoints. We demonstrate that the SIFT descriptor typically has lower lighting variance than other descriptors, although the result depends on semantic class and lighting conditions.

Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Constructing a frame of cube : connecting 3D shapes with direction, location and movement

With the advancement of new technologies, this author has in 2010 started to engineer an online learning environment for investigating the nature and development of spatial abilities, and the teaching and learning of geometry. This paper documents how this new digital learning environment can afford the opportunity to integrate the learning about 3D shapes with direction, location and movement, and how young children can mentally and visually construct virtual 3D shapes using movements in both egocentric and fixed frames of reference (FOR). Findings suggest that year 4 (aged 9) children can develop the capacity to construct a cube using egocentric FOR only, fixed FOR only or a combination of both FOR. However, these young participants were unable to articulate the effect of individual or combined FOR movements. Directions for future research are proposed.

Comprehensive Addictive Behaviors and Disorders, Volume 1 : Principles of Addiction

"Principles of Addiction provides a solid understanding of the definitional and diagnostic differences between use, abuse, and disorder. It describes in great detail the characteristics of these syndromes and various etiological models. The book's three main sections examine the nature of addiction, including epidemiology, symptoms, and course; alcohol and drug use among adolescents and college students; and detailed descriptions of a wide variety of addictive behaviors and disorders, encompassing not only drugs and alcohol, but caffeine, food, gambling, exercise, sex, work, social networking, and many other areas. This volume is especially important in providing a basic introduction to the field as well as an in-depth review of our current understanding of the nature and process of addictive behaviors. Principles of Addiction is one of three volumes comprising the 2,500-page series, Comprehensive Addictive Behaviors and Disorders. This series provides the most complete collection of current knowledge on addictive behaviors and disorders to date. In short, it is the definitive reference work on addictions."--publisher website

Comprehensive Addictive Behaviors and Disorders, Volume 2 : Biological Research on Addiction

"Biological Research on Addiction examines the neurobiological mechanisms of drug use and drug addiction, describing how the brain responds to addictive substances as well as how it is affected by drugs of abuse. The book's four main sections examine behavioral and molecular biology; neuroscience; genetics; and neuroimaging and neuropharmacology as they relate to the addictive process. This volume is especially effective in presenting current knowledge on the key neurobiological and genetic elements in an individual's susceptibility to drug dependence, as well as the processes by which some individuals proceed from casual drug use to drug dependence. Biological Research on Addiction is one of three volumes comprising the 2,500-page series, Comprehensive Addictive Behaviors and Disorders. This series provides the most complete collection of current knowledge on addictive behaviors and disorders to date. In short, it is the definitive reference work on addictions."--publisher website