A Freirian reading of online writing workshops

Online writing workshops provide educational spaces within which writers can learn and refine their craft. In order to better understand the dialogic mechanisms behind that learning, this paper examines ways in which online writing workshops might be described as functioning in manners akin to Freirian culture circles. This paper identifies several key characteristics that define Paulo Freire’s concept of the culture circle. It compares these characteristics to the structure of and interactive practices within an online writing workshop. It unpacks some of Freire’s ideas about codification and decodification of situated problems and about achieving critical consciousness, and examines how exemplars of this can be found in online writing workshops.

Understanding theory of mind in children who are deaf

Research on theory of mind began in the context of determining whether chimpanzees are aware that individuals experience cognitive and emotional states. More recently, this research has involved various groups of children and various tasks, including the false belief task. Based almost exclusively on that paradigm, investigators have concluded that although ``normal'' hearing children develop theory of mind by age 5, children who are autistic or deaf do not do so until much later, perhaps not until their teenage years. The present study explored theory of mind by examining stories told by children who are deaf and hearing (age 9±15 years) for statements ascribing behaviour-relevant states of mind to themselves and others. Both groups produced such attributions, although there were reliable differences between them. Results are discussed in terms of the cognitive abilities assumed to underlie false belief and narrative paradigms and the implications of attributing theory of mind solely on the basis of performance on the false belief task.

Acknowledging, moving toward and transcending psychophysiological angst during a paradox of conflicting desires

In this paper I integrate the work of a number of philosophers to clarify some psychological issues that can arise in human existence when a conflict of intrapersonal or interpersonal desires arises. This paper utilises the work of Deleuze, Freud, Jung, Heidegger, Hegel and Nietzsche to provide a conceptual framework as to how mental disturbances can arise if unconscious desires cannot be satisfied due to the experience of a resistance from a conflicting or opposing desire. This paper argues that the phenomenal experience of a conflict of desires can be unconcealed in moments of un-readiness-to-hand and from the awareness of the psychophysiological experience of stress or angst. The work that is presented, results in the conclusion that it is fundamentally necessary to embrace Nietzsche’s idea of the ‘will to power’ to overcome these difficulties and to achieve personal individuation and authentic wellbeing. This advice is in contrast to an inauthentic choice of depending on the use of Freudian defence mechanisms to conceal a conflict of desires from consciousness. A detailed theoretical example of the process involved in the resolution of a conflict of desires through self-transcendence is specifically informed by the ideas of Nietzsche and Jung.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Strolling the coastline: criminology in everyday life : through ‘landscape’ from gaol to ‘badlands’

Part travelogue, part flight of fancy, this paper recounts a coastline stroll from Maroubra Beach to Bondi in Sydney’s eastern suburbs. The author as ‘travel guide’ points out features of potential interest to two visiting criminological colleagues as they ‘pass by’ scenery of great beauty shadowed by acts of spectacular violence. The everyday acts of walking and talking while passing through a ‘landscape’ serve to constitute a criminology of everyday life, illustrating the way in which a consciousness of crime, crime sites, analyses and theories permeates the ways a ‘tourist trail’ might be experienced and seen, myths made and histories forged. The walk starts with the unseen lines of penal force radiating from Long Bay Gaol, before skirting through surfing and its regulation; the ‘brotherhood’ of the BRA Boys; the Hines killing and the politics of self defence; the shark arm case, the Virgin Mary and the Bali bombing memorial at Coogee; zones of the beach and Jock Young’s Vertigo at Bronte and Tamarama; before finishing at the Marks Park ‘badlands’ at Bondi, scene of a series of mostly unsolved and unpunished homophobic killings, giving rise to reflections on ‘ungrievable lives’, memory, mourning and forgetting.

The curious case of the embedded creative : creative cultural occupations outside the creative industries

This chapter is concerned with innovation that involves creative cultural occupations, but not within the creative industries. Rather, we examine the operation of cultural creative occupations that exist outside the creative industries - so-called 'embedded creatives' who work across all industry sectors (Cunningham and Higgs 2009). In doing so, we concur with Bilton (2007) that the separation of creative industries from other industries is a 'false step'. All industries must be innovative; however, they also must be able to combine both scientific and artistic creativity, and that creativity comes from the intersection of different thinking styles (Kurtzberg 2005). Moreover, we suggest that there are now detailed empirical studies, as well as a nascent theoretical base, to suggest that the transdisciplinarity which results from embedded cultural creativity is an engine of growth in the broader economy. Thus, it is relevant to both policymakers and managers. This chapter addresses the following questions: What is the role and significance of the embedded creative? Given a paucity of detailed empirical work in the area to date, what can be deduced from what extant literature there is about the nature of employment and management of these workers? And what are the practical implications of these consideration?

Knitted images : specimens

Knitting, as a conduit for multiple literacies takes on embodied practice and becomes research, investigation, theorization, and brings about physical and metaphysical theorizing on Deleuzian and Guattarian (1980/1987) concepts of the rhizome: the looping and constructing of the knitted planes prompt thoughts about the project that seem just ‘beyond the level of consciousness’ (Semetsky 2007, p. 200)...

Modeling the effectiveness of counterterrorism interventions

After the terrorist attacks in the United States on 11 September 2001, terrorism and counter-terrorism efforts moved to the front of popular consciousness and became the focus of national security for governments worldwide. With this increased attention came an urgent interest in understanding and identifying what works in fighting terrorism (Belasco 2010). For Australia, understanding the relative effectiveness of counter-terrorism efforts in nearby neighbours of Indonesia, Thailand and the Philippines is highly relevant for our country's national security. Indonesia, Thailand and the Philippines are all countries that are important to Australia not just because of geographic proximity, but also because of a history of economic ties and the role these countries play as Australia’s regional partners...

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.

Critical analysis of spam prevention techniques

E-mail spam has remained a scourge and menacing nuisance for users, internet and network service operators and providers, in spite of the anti-spam techniques available; and spammers are relentlessly circumventing these anti-spam techniques embedded or installed in form of software products on both client and server sides of both fixed and mobile devices to their advantage. This continuous evasion degrades the capabilities of these anti-spam techniques as none of them provides a comprehensive reliable solution to the problem posed by spam and spammers. Major problem for instance arises when these anti-spam techniques misjudge or misclassify legitimate emails as spam (false positive); or fail to deliver or block spam on the SMTP server (false negative); and the spam passes-on to the receiver, and yet this server from where it originates does not notice or even have an auto alert service to indicate that the spam it was designed to prevent has slipped and moved on to the receiver’s SMTP server; and the receiver’s SMTP server still fail to stop the spam from reaching user’s device and with no auto alert mechanism to inform itself of this inability; thus causing a staggering cost in loss of time, effort and finance. This paper takes a comparative literature overview of some of these anti-spam techniques, especially the filtering technological endorsements designed to prevent spam, their merits and demerits to entrench their capability enhancements, as well as evaluative analytical recommendations that will be subject to further research.

Classification of cancer-related death certificates using machine learning

Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.

Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results

The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The ‘small aperture score’ provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

The genome of the domesticated apple (Malus × domestica Borkh.)

We report a high-quality draft genome sequence of the domesticated apple (Malus × domestica). We show that a relatively recent (>50 million years ago) genome-wide duplication (GWD) has resulted in the transition from nine ancestral chromosomes to 17 chromosomes in the Pyreae. Traces of older GWDs partly support the monophyly of the ancestral paleohexaploidy of eudicots. Phylogenetic reconstruction of Pyreae and the genus Malus, relative to major Rosaceae taxa, identified the progenitor of the cultivated apple as M. sieversii. Expansion of gene families reported to be involved in fruit development may explain formation of the pome, a Pyreae-specific false fruit that develops by proliferation of the basal part of the sepals, the receptacle. In apple, a subclade of MADS-box genes, normally involved in flower and fruit development, is expanded to include 15 members, as are other gene families involved in Rosaceae-specific metabolism, such as transport and assimilation of sorbitol.

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.