Deriving word association networks from text corpora

This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.

Exploring with Grammar in the Primary Years: Learning about Language in the Australian Curriculum: English

This new volume, Exploring with Grammar in the Primary Years (Exley, Kevin & Mantei, 2014), follows on from Playing with Grammar in the Early Years (Exley & Kervin, 2013). We extend our thanks to the ALEA membership for their take up of the first volume and the vibrant conversations around our first attempt at developing a pedagogy for the teaching of grammar in the early years. Your engagement at locally held ALEA events has motivated us to complete this second volume and reassert our interest in the pursuit of socially-just outcomes in the primary years. As noted in Exley and Kervin (2013), we believe that mastering a range of literacy competences includes not only the technical skills for learning, but also the resources for viewing and constructing the world (Freire and Macdeo, 1987). Rather than seeing knowledge about language as the accumulation of technical skills alone, the viewpoint to which we subscribe treats knowledge about language as a dialectic that evolves from, is situated in, and contributes to active participation within a social arena (Halliday, 1978). We acknowledge that to explore is to engage in processes of discovery as we look closely and examine the opportunities before us. As such, we draw on Janks’ (2000; 2014) critical literacy theory to underpin many of the learning experiences in this text. Janks (2000) argues that effective participation in society requires knowledge about how the power of language promotes views, beliefs and values of certain groups to the exclusion of others. Powerful language users can identify not only how readers are positioned by these views, but also the ways these views are conveyed through the design of the text, that is, the combination of vocabulary, syntax, image, movement and sound. Similarly, powerful designers of texts can make careful modal choices in written and visual design to promote certain perspectives that position readers and viewers in new ways to consider more diverse points of view. As the title of our text suggests, our activities are designed to support learners in exploring the design of texts to achieve certain purposes and to consider the potential for the sharing of their own views through text production. In Exploring with Grammar in the Primary Years, we focus on the Year 3 to Year 6 grouping in line with the Australian Curriculum, Assessment and Reporting Authority’s (hereafter ACARA) advice on the ‘nature of learners’ (ACARA, 2014). Our goal in this publication is to provide a range of highly practical strategies for scaffolding students’ learning through some of the Content Descriptions from the Australian Curriculum: English Version 7.2, hereafter AC:E (ACARA, 2014). We continue to express our belief in the power of using whole texts from a range of authentic sources including high quality children’s literature, the internet, and examples of community-based texts to expose students to the richness of language. Taking time to look at language patterns within actual texts is a pathway to ‘…capture interest, stir the imagination and absorb the [child]’ into the world of language and literacy (Saxby, 1993, p. 55). It is our intention to be more overt this time and send a stronger message that our learning experiences are simply ‘sample’ activities rather than a teachers’ workbook or a program of study to be followed. We’re hoping that teachers and students will continue to explore their bookshelves, the internet and their community for texts that provide powerful opportunities to engage with language-based learning experiences. In the following three sections, we have tried to remain faithful to our interpretation of the AC:E Content Descriptions without giving an exhaustive explanation of the grammatical terms. This recently released curriculum offers a new theoretical approach to building students’ knowledge about language. The AC:E uses selected traditional terms through an approach developed in systemic functional linguistics (see Halliday and Matthiessen, 2004) to highlight the dynamic forms and functions of multimodal language in texts. For example, the following statement, taken from the ‘Language: Knowing about the English language’ strand states: English uses standard grammatical terminology within a contextual framework, in which language choices are seen to vary according to the topics at hand, the nature and proximity of the relationships between the language users, and the modalities or channels of communication available (ACARA, 2014). Put simply, traditional grammar terms are used within a functional framework made up of field, tenor, and mode. An understanding of genre is noted with the reference to a ‘contextual framework’. The ‘topics at hand’ concern the field or subject matter of the text. The ‘relationships between the language users’ is a description of tenor. There is reference to ‘modalities’, such as spoken, written or visual text. We posit that this innovative approach is necessary for working with contemporary multimodal and cross-cultural texts (see Exley & Mills, 2012). Other excellent tomes, such as Derewianka (2011), Humphrey, Droga and Feez (2012), and Rossbridge and Rushton (2011) provide more comprehensive explanations of this unique metalanguage, as does the AC:E Glossary. We’ve reproduced some of the AC:E Glossary at the end of this publication. We’ve also kept the same layout for our learning experiences, ensuring that our teacher notes are not only succinct but also prudent in their placement. Each learning experience is connected to a Content Description from the AC:E and contains an experience with an identified purpose, suggested resource text and a possible sequence for the experience that always commences with an orientation to text followed by an examination of a particular grammatical resource. Our plans allow for focused discussion, shared exploration and opportunities to revisit the same text for the purpose of enhancing meaning making. Some learning experiences finish with deconstruction of a stimulus text while others invite students to engage in the design of new texts. We encourage you to look for opportunities in your own classrooms to move from text deconstruction to text design. In this way, students can express not only their emerging grammatical understandings, but also the ways they might position readers or viewers through the creation of their own texts. We expect that each of these learning experiences will vary in the time taken. Some may indeed take a couple if not a few teaching episodes to work through, especially if students are meeting a concept or a pedagogical strategy for the first time. We hope you use as much, or as little, of each experience as is needed for your students. We do not want the teaching of grammar to slip into a crisis of irrelevance or to be seen as a series of worksheet drills with finite answers. We firmly believe that strategies for effective deconstruction and design practice, however, have much portability. We three are very keen to hear from teachers who are adopting and adapting these learning experiences in their classrooms. Please email us on b.exley@qut.edu.au, lkervin@uow.edu.au or jessicam@ouw.edu.au. We’d love to continue the conversation with you over time. Beryl Exley, Lisa Kervin & Jessica Mantei

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Visual control of an electrohydraulic manipulator for underground mining applications

A large range of underground mining equipment makes use of compliant hydraulic arms for tasks such as rock-bolting, rock breaking, explosive charging and shotcreting. This paper describes a laboratory model electo-hydraulic manipulator which is used to prototype novel control and sensing techniques. The research is aimed at improving the safety and productivity of these mining tasks through automation, in particular the application of closed-loop visual positioning of the machine's end-effector.

Applications of real-time machine vision to the control of mining equipment

The mining industry presents us with a number of ideal applications for sensor based machine control because of the unstructured environment that exists within each mine. The aim of the research presented here is to increase the productivity of existing large compliant mining machines by retrofitting with enhanced sensing and control technology. The current research focusses on the automatic control of the swing motion cycle of a dragline and an automated roof bolting system. We have achieved: * closed-loop swing control of an one-tenth scale model dragline; * single degree of freedom closed-loop visual control of an electro-hydraulic manipulator in the lab developed from standard components.

Integration of Opinion Mining into customer analysis model

This research proposes a multi-dimensional model for Opinion Mining, which integrates customers' characteristics and their opinions about products (or services). Customer opinions are valuable for companies to deliver right products or services to their customers. This research presents a comprehensive framework to evaluate opinions' orientation based on products' hierarchy attributes. It also provides an alternative way to obtain opinion summaries for different groups of customers and different categories of produces.

Sensors and control for mining robotics

This paper discusses some of the sensing technologies and control approaches available for guiding robot manipulators for a class of underground mining tasks including drilling jumbos, bolting arms, shotcreters or explosive chargers. Data acquired with such sensors, in the laboratory and underground, is presented.

[await full-text]Evaluation of QAS Workplace Health and Safety Action Plan

This report identifies the outcomes of a program evaluation of the five year Workplace Health and Safety Strategy (2012-2017), specifically, the engagement component within the Queensland Ambulance Service. As part of the former Department of Community Safety, their objective was to work towards harmonising the occupational health and safety policies and process to improve the workplace culture. The report examines and assess the process paths and resource inputs into the strategy, provides feedback on progress to achieving identified goals as well as identify opportunities for improvements and barriers to progress. Consultations were held with key stakeholders within QAS and focus groups were facilitated with managers and health and safety representatives of each Local Area Service Network.

Pull the plug or take the plunge: Multiple opportunities and the speed of venturing decisions in the Australian mining industry

Effectively capturing opportunities requires rapid decision-making. We investigate the speed of opportunity evaluation decisions by focusing on firms' venture termination and venture advancement decisions. Experience, standard operating procedures, and confidence allow firms to make opportunity evaluation decisions faster; we propose that a firm's attentional orientation, as reflected in its project portfolio, limits the number of domains in which these speed-enhancing mechanisms can be developed. Hence firms' decision speed is likely to vary between different types of decisions. Using unique data on 3,269 mineral exploration ventures in the Australian mining industry, we find that firms with a higher degree of attention toward earlier-stage exploration activities are quicker to abandon potential opportunities in early development but slower to do so later, and that such firms are also slower to advance on potential opportunities at all stages compared to firms that focus their attention differently. Market dynamism moderates these relationships, but only with regard to initial evaluation decisions. Our study extends research on decision speed by showing that firms are not necessarily fast or slow regarding all the decisions they make, and by offering an opportunity evaluation framework that recognizes that decision makers can, in fact often do, pursue multiple potential opportunities simultaneously.

Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

A service-oriented architecture for text analytics enabled business applications

Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

Contextual constraining of student design practices

Background Engineering design is of significant interest to engineering educators. As yet, how the higher education context shapes student outcomes in engineering design courses remains underexplored. Since design courses are the primary way students are taught the critical topic of design, it is important to understand how the institutional and organizational contexts shape student outcomes and how we could improve design projects, given the context. Purpose We sought to answer two questions: What aspects of the design education process are salient, or important, for students? How do these salient aspects affect their design practices? Design/Method We used a qualitative case study approach to address the research questions because of our emphasis on understanding process-related aspects of design work and developing an interpretive understanding from the students’ perspective. Results Using a nested structuration framework, we show that the context of design practices shaped students’ outcomes by constraining their approach to the project and by providing a framework for their design process. We provide recommendations for design educators to help students overcome impediments to achieving learning objectives for design activities. Our research questions the efficacy of teaching engineering design when a design problem lacks a context beyond the classroom. Conclusions The institutional and organizational contexts influence student design practices. Engineering educators should carefully consider the potential effects of the design projects they implement within a higher education context.

Uncovering misconceptions through text analysis

Assessing students’ conceptual understanding of technical content is important for instructors as well as students to learn content and apply knowledge in various contexts. Concept inventories that identify possible misconceptions through validated multiple-choice questions are helpful in identifying a misconception that may exist, but do not provide a meaningful assessment of why they exist or the nature of the students’ understanding. We conducted a case study with undergraduate students in an electrical engineering course by testing a validated multiple-choice response concept inventory that we augmented with a component for students to provide written explanations for their multiple-choice selection. Results revealed that correctly chosen multiple-choice selections did not always match correct conceptual understanding for question testing a specific concept. The addition of a text-response to multiple-choice concept inventory questions provided an enhanced and meaningful assessment of students’ conceptual understanding and highlighted variables associated with current concept inventories or multiple choice questions.

Mining process risks and resource profiles

This research contributes novel techniques for identifying and evaluating business process risks and analysing human resource behaviour. The developed techniques use predefined indicators to identify process risks in individual process instances, evaluate overall process risk, predict process outcomes and analyse human resource behaviour based on the analysis of information about process executions recorded in event logs by information systems. The results of this research can help managers to more accurately evaluate the risk exposure of their business processes, to more objectively evaluate the performance of their employees, and to identify opportunities for improvement of resource and process performance.

Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.