Emotional experiences of preservice science teachers in online learning : the formation, disruption and maintenance of social bonds

The enactment of learning to become a science teacher in online mode is an emotionally charged experience. We attend to the formation, maintenance and disruption of social bonds experienced by online preservice science teachers as they shared their emotional online learning experiences through blogs, or e-motion diaries, in reaction to videos of face-to-face lessons. A multi-theoretic framework drawing on microsociological perspectives of emotion informed our hermeneutic interpretations of students’ first-person accounts reported through an e-motion diary. These accounts were analyzed through our own database of emotion labels constructed from the synthesis of existing literature on emotion across a range of fields of inquiry. Preservice science teachers felt included in the face-to-face group as they watched videos of classroom transactions. The strength of these feelings of social solidarity were dependent on the quality of the video recording. E-motion diaries provided a resource for interactions focused on shared emotional experiences leading to formation of social bonds and the alleviation of feelings of fear, trepidation and anxiety about becoming science teachers. We offer implications to inform practitioners who wish to improve feelings of inclusion amongst their online learners in science education.

WikiLeaks : The Napster of Secrets?

WikiLeaks has become a global phenomenon, and its founder and spokesman Julian Assange an international celebrity (or terrorist, depending on one’s perspective). But perhaps this focus on Assange and his website is as misplaced as the attacks against Napster and its founders were a decade ago: WikiLeaks itself only marks a new phase in a continuing shift in the balance of power between states and citizens, much as Napster helped to undermine the control of major music labels over the music industry. If the history of music filesharing is any guide, no level of punitive action against WikiLeaks and its supporters is going to re-contain the information WikiLeaks has set loose.

Trashtopia by Maison Briz Vegas

Description of the Work Trashtopia was a fashion exhibition at Craft Queensland’s Artisan gallery showcasing outfits made entirely from rubbish materials. The exhibition was part of an on-going series by the Queensland Fashion Archives, called Remember or Revive. Maison Briz Vegas designers, Carla Binotto and Carla van Lunn created a dystopian beach holiday tableau referencing mid-century Californian and Gold Coast beach culture and style, and today’s plastic pollution of the world’s oceans. The display engaged a popular audience with ideas about environmental destruction and climate change while bringing twentieth and twenty-first century consumer and leisure culture into question. The medium of fashion was used as a means of amusement and provocation. The fashion objects and installation questioned current mores about the material value of rubbish and the installation was also a work of environmental activism. Statement of the Research Component The work was framed by critical reflections of contemporary consumer culture and research fields questioning value in waste materials and fashion objects. The work is situated in the context of conceptual and experimental fashion design practice and fashion presentation. The exhibited work transgressed the conventional production methods and material choice of designer fashion garments, for example, discarded plastic shopping bags were painstakingly shredded to mimic ostrich feathers. The viewer was prompted to reflect on the materiality of rubbish and its potential for transformation. The exhibition also sits in the context of culture jamming and contemporary activist practice. The work references and subverts twentieth century beach holiday culture, contrasting resort wear with a contemporary picture of plastic pollution of the oceans and climate change. Hawaiian style prints contained a playful and dark narrative of dying marine-life and the viewer was invited to take a “Greetings from Trashtopia” postcard depicting fashion models floating in oceans of plastic rubbish. This reflective creative practice sought to address the question of whether fashion made from recycled rubbish materials can critically and emotionally engage viewers with questions about contemporary consumer culture and material value. This work presents an innovative model of fashion design practice in which rubbish materials are transformed into designer garments and rubbish is placed centre stage in the public presentation of the designs. In overturning the traditional model of fashion presentation, the viewer is also given a deeper connection to the recycling process and complex ideas of waste and value. In 2015 two outfits from the exhibition were selected, along with works from three leading Australian fashion labels, and four leading New Zealand labels, for a commemorative ANZAC fashion collection shown at iD Dunedin Fashion Week. The show titled, “Together Alone, revisited” reprised an Australian and New Zealand fashion exhibition first held at the National Gallery of Victoria in 2009.

Clustering and labeling a web scale document collection using Wikipedia clusters

Clustering is an important technique in organising and categorising web scale documents. The main challenges faced in clustering the billions of documents available on the web are the processing power required and the sheer size of the datasets available. More importantly, it is nigh impossible to generate the labels for a general web document collection containing billions of documents and a vast taxonomy of topics. However, document clusters are most commonly evaluated by comparison to a ground truth set of labels for documents. This paper presents a clustering and labeling solution where the Wikipedia is clustered and hundreds of millions of web documents in ClueWeb12 are mapped on to those clusters. This solution is based on the assumption that the Wikipedia contains such a wide range of diverse topics that it represents a small scale web. We found that it was possible to perform the web scale document clustering and labeling process on one desktop computer under a couple of days for the Wikipedia clustering solution containing about 1000 clusters. It takes longer to execute a solution with finer granularity clusters such as 10,000 or 50,000. These results were evaluated using a set of external data.

The Fleet Store : devising a public retail exhibition to promote creative, innovative and sustainable business models for emerging fashion designers

1.Description of the Work The Fleet Store was devised as a creative output to establish an exhibition linked to a fashion business model where emerging designers were encouraged to research new and innovative strategies for creating design-driven and commercial collections for a public consumer. This was a project that was devised to break down the perceptions of emerging fashion designers that designing commercial collections linked to a sustainable business model is a boring and unnecessary process. The focus was to demystify the business of fashion and to link its importance to a design-driven and public outcome that is more familiar to fashion designers. The criterion for participation was that all designers had to be registered as a business with the Australian Taxation Office. Designers were chosen from the Creative Enterprise Australia Fashion Business Incubator, the QUT fashion graduate alumni and current QUT fashion design and double degree (fashion and business) students with existing businesses. The project evolved from a series of collaborative workshops where designers were introduced to new and innovative creative industries’ business models and the processes, costings and timings involved to create a niche, sustainable business for a public exhibition of design-driven commercial collections. All designers initiated their own business infra-structure but were then introduced to the concept of collaboration for successful and profitable exhibition and business outcomes. Collaborative strategies such as crowd funding, crowd sourcing, peer to peer mentoring and manufacturing were all researched, and strategies for the establishment of the retail exhibition were all devised in a collaborative environment. All participants also took on roles outside their ‘designer’ background to create a retail exhibition that was creative but also had critical mass and aesthetic for the consumer. The Fleet Store ‘popped up’ for 2 weeks (10 days), in a heritage-listed building in an inner city location. Passers-by were important, but the main consumer was enlisted by the use of interest and investment from crowd sourcing, crowd funding, ethical marketing, corporate social responsibility projects and collaborative public relations and social media strategies. The research has furthered discussion on innovative strategies for emerging fashion designers to initiate and maintain sustainable businesses and suggests that collaboration combined with a design-driven and business focus can create a sustainable and economically viable retail exhibition. 2. Research Statement Research Background The research field involved developing a new ethical, design-driven, collaborative and sustainable model for fashion design practice and management. The research asked can a public, design-driven, collaborative retail exhibition create a platform for promoting creative, innovative and sustainable business models for emerging fashion designers. The methodology was primarily practice-led as all participants were designers in their own right and the project manager acted as a mentor and curator to guide the process and analyse the potential of the research question. The Fleet Store offers new knowledge in design practice and management; with the creation of a model where design outcomes and business models are inextricably linked to the success of the creative output. Key innovations include extending the commercialisation of emerging fashion businesses by creating a curated retail gallery for collaborative and sustainable strategies to support niche fashion designer labels. This has contributed to a broader conversation on how to nurture and sustain competitive Australian fashion designers/labels. Research Contribution and Significance The Fleet Store has contributed to a growing body of research into innovative and sustainable business models for niche fashion and creative industries’ practitioners. All participants have maintained their business infra-structure and many are currently growing their businesses, using the strategies tested for the Fleet Store. The exhibition space was visited by over 1,000 people and sales of $27,000 were made in 10 days of opening. (Follow up sales of $3,000 has also been reported.) Three of the designers were ‘discovered’ from the exhibition and have received substantial orders from high profile national buyers and retailers for next season delivery. Several participants have since collaborated to create other pop up retail environments and are now mentoring other emerging designers on the significance of a collaborative retail exhibition to consolidate niche business models for emerging fashion designers.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

An external field prior for the hidden Potts model with application to cone-beam computed tomography

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.

Robot navigation using human cues: A robot navigation system for symbolic goal-directed exploration

In this paper we present for the first time a complete symbolic navigation system that performs goal-directed exploration to unfamiliar environments on a physical robot. We introduce a novel construct called the abstract map to link provided symbolic spatial information with observed symbolic information and actual places in the real world. Symbolic information is observed using a text recognition system that has been developed specifically for the application of reading door labels. In the study described in this paper, the robot was provided with a floor plan and a destination. The destination was specified by a room number, used both in the floor plan and on the door to the room. The robot autonomously navigated to the destination using its text recognition, abstract map, mapping, and path planning systems. The robot used the symbolic navigation system to determine an efficient path to the destination, and reached the goal in two different real-world environments. Simulation results show that the system reduces the time required to navigate to a goal when compared to random exploration.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

Just label it: Consumer rights, GM food labelling, and international trade

In the United States, there has been fierce debate over state, federal and international efforts to engage in genetically modified food labelling (GM food labelling). A grassroots coalition of consumers, environmentalists, organic farmers, and the food movement has pushed for law reform in respect of GM food labelling. The Just Label It campaign has encouraged United States consumers to send comments to the United States Food and Drug Administration to label genetically modified foods. This Chapter explores the various justifications made in respect of genetically modified food labelling. There has been a considerable effort to portray the issue of GM food labelling as one of consumer rights as part of ‘the right to know’. There has been a significant battle amongst farmers over GM food labelling – with organic farmers and biotechnology companies, fighting for precedence. There has also been a significant discussion about the use of GM food labelling as a form of environmental legislation. The prescriptions in GM food labelling regulations may serve to promote eco-labelling, and deter greenwashing. There has been a significant debate over whether GM food labelling may serve to regulate corporations – particularly from the food, agriculture, and biotechnology industries. There are significant issues about the interaction between intellectual property laws – particularly in respect of trade mark law and consumer protection – and regulatory proposals focused upon biotechnology. There has been a lack of international harmonization in respect of GM food labelling. As such, there has been a major use of comparative arguments about regulator models in respect of food labelling. There has also been a discussion about international law, particularly with the emergence of sweeping regional trade proposals, such as the Trans-Pacific Partnership, and the Trans-Atlantic Trade and Investment Partnership. This Chapter considers the United States debates over genetically modified food labelling – at state, federal, and international levels. The battles often involved the use of citizen-initiated referenda. The policy conflicts have been policy-centric disputes – pitting organic farmers, consumers, and environmentalists against the food industry and biotechnology industry. Such battles have raised questions about consumer rights, public health, freedom of speech, and corporate rights. The disputes highlighted larger issues about lobbying, fund-raising, and political influence. The role of money in United States has been a prominent concern of Lawrence Lessig in his recent academic and policy work with the group, Rootstrikers. Part 1 considers the debate in California over Proposition 37. Part 2 explores other key state initiatives in respect of GM food labelling. Part 3 examines the Federal debate in the United States over GM food labelling. Part 4 explores whether regional trade agreements – such as the Trans-Pacific Partnership (TPP) and the Trans-Atlantic Trade and Investment Partnership (TTIP) – will impact upon

Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Introduction to "Business innovation and disruption in the music industry"

Similar to most other creative industries, the evolution of the music industry is heavily shaped by media technologies. This was equally true in 1999, when the global recorded music industry had experienced two decades of continuous growth largely driven by the rapid transition from vinyl records to Compact Discs. The transition encouraged avid music listeners to purchase much of their music collections all over again in order to listen to their favourite music with ‘digital sound’. As a consequence of this successful product innovation, recorded music sales (unit measure) more than doubled between the early 1980s and the end of the 1990s. It was with this backdrop that the first peer-to-peer file sharing service was developed and released to the mainstream music market in 1999 by the college student Shawn Fanning. The service was named Napster and it marks the beginning of an era that is now a classic example of how an innovation is able to disrupt an entire industry and make large swathes of existing industry competences obsolete. File sharing services such as Napster, followed by a range of similar services in its path, reduced physical unit sales in the music industry to levels that had not been seen since the 1970s. The severe impact of the internet on physical sales shocked many music industry executives who spent much of the 2000s vigorously trying to reverse the decline and make the disruptive technologies go away. At the end, they learned that their efforts were to no avail and the impact on the music industry proved to be transformative, irreversible and, to many music industry professionals, also devastating. Thousands of people lost their livelihood, large and small music companies have folded or been forced into mergers or acquisitions. But as always during periods of disruption, the past 15 years have also been very innovative, spurring a plethora of new music business models. These new business models have mainly emerged outside the music industry and the innovators have been often been required to be both persuasive and persistent in order to get acceptance from the risk-averse and cash-poor music industry establishment. Apple was one such change agent that in 2003 was the first company to open up a functioning and legal market for online music. iTunes Music Store was the first online retail outlet that was able to offer the music catalogues from all the major music companies; it used an entirely novel pricing model, and it allowed consumers to de-bundle the music album and only buy the songs that they actually liked. Songs had previously been bundled by physical necessity as discs or cassettes, but with iTunes Music Store, the institutionalized album bundle slowly started to fall apart. The consequences had an immediate impact on music retailing and within just a few years, many brick and mortar record stores were forced out of business in markets across the world. The transformation also had disruptive consequences beyond music retailing and redefined music companies’ organizational structures, work processes and routines, as well as professional roles. iTunes Music Store in one sense was a disruptive innovation, but it was at the same time relatively incremental, since the major labels��� positions and power structures remained largely unscathed. The rights holders still controlled their intellectual properties and the structures that guided the royalties paid per song that was sold were predictable, transparent and in line with established music industry practices.

Not “just words”: Exposure to homophobic epithets leads to dehumanizing and physical distancing from gay men

We examined whether homophobic epithets (e.g., faggot) function as labels of deviance for homosexuals that contribute to their dehumanization and physical distance. Across two studies, participants were supraliminally (Study 1) and subliminally (Study 2) exposed to a homophobic epithet, a category label, or a generic insult. Participants were then asked to associate human related and animal-related words to homosexuals and heterosexuals. Results showed that after exposure to a homophobic epithet, compared with a category label or a generic insult, participants associated less human-related words with homosexuals, indicating dehumanization. In Study 2, we also assessed the effect of a homophobic epithet on physical distance from a target group member and found that homophobic epithets led to greater physical distancing of a gay man. These findings indicate that homophobic epithets foster dehumanization and avoidance of gay people, in ways that other insults or labels do not.

A Lidl bit of grocery competition could cause a Coles rethink

Australian shoppers have inadvertently invited global discount grocers to our shores by demonstrating their readiness to adopt private labels. In 2001, German discounter Aldi opened its first store in Sydney. The impact this business format would have on the Australian grocery sector was underestimated.

Find my office: Navigating real space from semantic descriptions

This paper shows that by using only symbolic language phrases, a mobile robot can purposefully navigate to specified rooms in previously unexplored environments. The robot intelligently organises a symbolic language description of the unseen environment and “imagines” a representative map, called the abstract map. The abstract map is an internal representation of the topological structure and spatial layout of symbolically defined locations. To perform goal-directed exploration, the abstract map creates a high-level semantic plan to reason about spaces beyond the robot’s known world. While completing the plan, the robot uses the metric guidance provided by a spatial layout, and grounded observations of door labels, to efficiently guide its navigation. The system is shown to complete exploration in unexplored spaces by travelling only 13.3% further than the optimal path.