Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task

This paper presents our system to address the CogALex-IV 2014 shared task of identifying a single word most semantically related to a group of 5 words (queries). Our system uses an implementation of a neural language model and identifies the answer word by finding the most semantically similar word representation to the sum of the query representations. It is a fully unsupervised system which learns on around 20% of the UkWaC corpus. It correctly identifies 85 exact correct targets out of 2,000 queries, 285 approximate targets in lists of 5 suggestions.

Aggregating energy supply and demand

Energy usage in general, and electricity usage in particular, are major concerns internationally due to the increased cost of providing energy supplies and the environmental impacts of electricity generation using carbon-based fuels. If a "systems" approach is taken to understanding energy issues then both supply and demand need to be considered holistically. This paper examines two research projects in the energy area with IT tools as key deliverables, one examining supply issues and the other studying demand side issues. The supply side project used hard engineering methods to build the models and software, while the demand side project used a social science approach. While the projects are distinct, there was an overlap in personnel. Comparing the knowledge extraction, model building, implementation and interface issues of these two deliverables identifies both interesting contrasts and commonalities.

EUTOPIA 75+ : exploratory futures scenarios for baby boomers’ preferred living spaces

Australia is experiencing the global phenomenon of an ageing population with the baby boomer generation starting to reach retirement age in large numbers. As a result, there is a growing need for appropriate accommodation and this will continue to grow for the foreseeable future. However, the needs of the fit, mobile and techno savvy baby boomers are likely to be far different from those of previous generations of older people, but are as yet unknown and unanticipated. This paper reports on the findings of a Futuring research project to explore the preferred housing futures for the baby boomer generation in the city of Brisbane, an aspiring creative city in South East Queensland (SEQ), Australia. Their future home design and service needs are predicted by firstly employing a global environmental scan of related and associated ageing futures issues. This was followed by a micro-Futuring workshop, based on Inayatullah’s Futures Triangle Analysis, to identify a range of scenarios. The key aspects of the workshop culminated in the development of a Transformational Scenario – EUTOPIA 75+. From this, a suite of six design recommendations for seniors’ housing design and smart services provision are synthesised to give a sense of direction of preferred living styles, especially in terms of physical housing spaces, with a view to identifying new house design opportunities for the allied industries and research organisations. The issues identified are also of concern for aged care service providers, retirement living developers, and for academics involved in the social and physical design of living spaces for older people.

Multimedia super corridor, Malaysia: Knowledge-based urban development lessons from an emerging economy

Purpose Knowledge-based urban development (KBUD) has been an effective strategy and an opportunity for emerging economies for catching up with the developed economies. The paper aims to investigate and provide insights on KBUD in the context of emerging economies. Design/methodology/approach The paper scrutinizes the Multimedia Super Corridor of Malaysia (MSC) by focusing on the planning, development and orchestration of the knowledge corridor. Findings The paper reveals a number of lessons and insights drawn from the development of MSC as the largest manifestation of KBUD initiative in Malaysia. Originality/value The paper provides lessons and recommendations on the planning, development and management of KBUD for emerging economies that are seeking a prosperous development.

A framework for understanding and generating integrated solutions for residential peak energy demand

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

Medical semantic similarity with a neural language model

Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Is being #instagay different from an #lgbttakeover? A cross-platform investigation of sexual and gender identity performances

This paper introduces research in progress that examines how queer women perform sexual identity across social media platforms. Applying a lens of queer theory and Actor Network Theory, it discusses women’s embodied self-representations as taking on forms that both conform to and elaborate upon the selfie genre of digital representation. Acknowledging similarities and differences across platforms, specifically between Instagram and Vine, a novel walkthrough method is introduced to identify platform characteristics that shape identity performances. This method provides insights into the role of platforms in identity performances, which can be combined with analysis of user-generated content and interviews to better understand digital media’s constraints and affordances for queer representation.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Trehalose Toxicity in Cuscuta refexal Correlation With low Trehalase Activity

A toxic effect of a,a-trehalose in an angiospermic plant, Cuscuta reflexa (dodder), Is described. This disaccharide and Its analogs, 2-aminotrehalose and 4-aminotbhakose, induced a raid blackening of the terminal region of the vine which is Involved in elongation growth. From the results of in vitro growth of several angkiopermic plants and determination of trehalase activity in them, it is concluded that the toxic effect of trehalose in Cucaa is because of the very low trehalas activity In the vine. As a result, trehalose accumulates In the vine and interferes with some process closely associated with growth. The growth potential of Lemma (a duckweed) in a medium containing trehalose as the carbon source was ihreversibly lost upon addition of trealosamine, an Inhibitor of trehalase activity. It is concluded that, if allowed to accumulate within the tissue, trehalose may be potentiaMly toxic or inhibitory to higher plants in generaL The presence of trhalase actvity in plants, where Its substrate has not been found to occur, is envisged to relieve the plant from the toxic effects of trehalose which it may encounter in soil or during association with fungi or insects.

Analysis of word embeddings and sequence features for clinical information extraction

This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

Trehalose Toxicity in Cuscuta reflexa

a,a-Trehalose induced a rapid blackening of the terminal 2.5-centimeter region of excised Cuscuta relexa Roxb. vine. The incorporation of radioactivity from [I'C]glucose into alkali-insoluble fraction of shoot tip was markedly inhibited by 12 hours of trehalose feeding to an excised vine. This inhibition was confied to the apical segment of the vine in which cell elongation occurred. The rate of blackening of shoot tip explants was hastened by the addition of gibberellic acid A3, which promoted elongation growth of isolated Cuscuta shoot tips. The symptom of trehalose toxicity was duplicated by 2-deoxygucose, which has been shown to be a potent inhibitor of ceD wall synthesis in yeast. The observations suggest that trehalose interferes with the synthesis of ceDl wail polysaccharides, the chief component of which was presumed to be cellulose.

Identification and host-plant associations of Australian Sericothripinae (Thysanoptera, Thripidae)

The Sericothripinae is a largely tropical group of about 140 species that are often strikingly bicoloured and have complex surface sculpture, but for which the biology is poorly known. Although 15 genera have been described in this subfamily, only three of these are currently recognised, with five new generic synonymies indicated here. In Australia, Sericothrips Haliday is introduced, with one European species deployed as a weed biological control agent. Hydatothrips Karny comprises 43 species worldwide, with six species found in Australia, of which two are shared with Southeast Asia, and four are associated with the native vine genus, Parsonsia. Neohydatothrips John comprises 96 species worldwide, with nine species in Australia, of which one is shared with Southeast Asia and two are presumably introduced from the Americas. Illustrated keys are provided to the three genera and 16 species from Australia, including six new species [Hydatothrips aliceae; H. bhattii; H. williamsi; Neohydatothrips barrowi, N. bellissi, N. katherinae]. One new specific synonym is recognised [Hydatothrips haschemi Girault (= H. palawanensis Kudo)], also four new generic synonyms [Neohydatothrips John (= Faureana Bhatti; Onihothrips Bhatti; Sariathrips Bhatti; Papiliothrips Bhatti); Sericothrips Haliday (= Sussericothrips Han)].

"Like a monkey with a miniature cymbal": Cultural practices of repetition in visual social media

Looping media are recurring components of online content, from gifs to Vine videos, in addition to the conceptual repetition of memes and related practices. This paper analyses practices around looping visual media as examples of vernacular creativity, social media literacies, and internet culture, especially for irreverent and playful purposes. Focusing on the LGBTQ digital cultural context as a pilot study, this research examines multi-platform uses of looping media, including personal narratives through Vine videos and animated gifs on Tumblr. In addition to textual analysis of LGBTQ looping visual social media content, the study will further explore the platform context as part of the experience of looped media. The research will address how these factors may also contribute to practices of irreverence and play, both within the specific case of LGBTQ culture and internet culture more generally.