Outcomes of the Chemistry Discipline Network Mapping Exercises: Are the Threshold Learning Outcomes met?

The Chemistry Discipline Network has recently completed two distinct mapping exercises. The first is a snapshot of chemistry taught at 12 institutions around Australia in 2011. There were many similarities but also important differences in the content taught and assessed at different institutions. There were also significant differences in delivery, particularly laboratory contact hours, as well as forms and weightings of assessment. The second mapping exercise mapped the chemistry degrees at three institutions to the Threshold Learning Outcomes for chemistry. Importantly, some of the TLOs were addressed by multiple units at all institutions, while others were not met, or were met at an introductory level only. The exercise also exposed some challenges in using the TLOs as currently written.

Component modeling for SCADA network mapping

Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.

Mapping the Australian political blogosphere

Network crawling and visualisation tools and other datamining systems are now advanced enough to provide significant new impulses to the study of cultural activity on the Web. A growing range of studies focus on communicative processes in the blogosphere – including for example Adamic & Glance’s 2005 map of political allegiances during the 2004 U.S. presidential election and Kelly & Etling’s 2008 study of blogging practices in Iran. There remain a number of significant shortcomings in the application of such tools and methodologies to the study of blogging; these relate both to how the content of blogs is analysed, and to how the network maps resulting from such studies are understood. Our project highlights and addresses such shortcomings.

Mapping the Australian networked public sphere

This article reports on a research program that has developed new methodologies for mapping the Australian blogosphere and tracking how information is disseminated across it. The authors improve on conventional web crawling methodologies in a number of significant ways: First, the authors track blogging activity as it occurs, by scraping new blog posts when such posts are announced through Really Simple Syndication (RSS) feeds. Second, the authors use custom-made tools that distinguish between the different types of content and thus allow us to analyze only the salient discursive content provided by bloggers. Finally, the authors are able to examine these better quality data using both link network mapping and textual analysis tools, to produce both cumulative longer term maps of interlinkages and themes, and specific shorter term snapshots of current activity that indicate current clusters of heavy interlinkage and highlight their key themes. In this article, the authors discuss findings from a yearlong observation of the Australian political blogosphere, suggesting that Australian political bloggers consistently address current affairs, but interpret them differently from mainstream news outlets. The article also discusses the next stage of the project, which extends this approach to an examination of other social networks used by Australians, including Twitter, YouTube, and Flickr. This adaptation of our methodology moves away from narrow models of political communication, and toward an investigation of everyday and popular communication, providing a more inclusive and detailed picture of the Australian networked public sphere.

Mapping intermedia news flows : topical discussions in the Australian and French political blogospheres

The growth of technologies and tools branded as =new media‘ or =Web 2.0‘ has sparked much discussion about the internet and its place in all facets of social life. Such debate includes the potential for blogs and citizen journalism projects to replace or alter journalism and mainstream media practices. However, while the journalism-blog dynamic has attracted the most attention, the actual work of political bloggers, the roles they play in the mediasphere and the resources they use, has been comparatively ignored. This project will look at political blogging in Australia and France - sites commenting on or promoting political events and ideas, and run by citizens, politicians, and journalists alike. In doing so, the structure of networks formed by bloggers and the nature of communication within political blogospheres will be examined. Previous studies of political blogging around the world have focussed on individual nations, finding that in some cases the networks are divided between different political ideologies. By comparing two countries with different political representation (two-party dominated system vs. a wider political spectrum), this study will determine the structure of these political blogospheres, and correlate these structures with the political environment in which they are situated. The thesis adapts concepts from communication and media theories, including framing, agenda setting, and opinion leaders, to examine the work of political bloggers and their place within the mediasphere. As well as developing a hybrid theoretical base for research into blogs and other online communication, the project outlines new methodologies for carrying out studies of online activity through the analysis of several topical networks within the wider activity collected for this project. The project draws on hyperlink and textual data collected from a sample of Australian and French blogs between January and August 2009. From this data, the thesis provides an overview of =everyday‘ political blogging, showing posting patterns over several months of activity, away from national elections and their associated campaigns. However, while other work in this field has looked solely at cumulative networks, treating collected data as a static network, this project will also look at specific cases to see how the blogospheres change with time and topics of discussion. Three case studies are used within the thesis to examine how blogs cover politics, featuring an international political event (the Obama inauguration), and local political topics (the opposition to the =Création et Internet‘, or HADOPI, law in France, the =Utegate‘ scandal in Australia). By using a mixture of qualitative and quantitative methods, the study analyses data collected from a population of sites from both countries, looking at their linking patterns, relationship with mainstream media, and topics of interest. This project will subsequently help to further develop methodologies in this field and provide new and detailed information on both online networks and internet-based political communication in Australia and France.

A ‘Big Data’ Approach to Mapping the Australian Twittersphere

This chapter discusses the methodological aspects and empirical findings of a large-scale, funded project investigating public communication through social media in Australia. The project concentrates on Twitter, but we approach it as representative of broader current trends toward the integration of large datasets and computational methods into media and communication studies in general, and social media scholarship in particular. The research discussed in this chapter aims to empirically describe networks of affiliation and interest in the Australian Twittersphere, while reflecting on the methodological implications and imperatives of ‘big data’ in the humanities. Using custom network crawling technology, we have conducted a snowball crawl of Twitter accounts operated by Australian users to identify more than one million users and their follower/followee relationships, and have mapped their interconnections. In itself, the map provides an overview of the major clusters of densely interlinked users, largely centred on shared topics of interest (from politics through arts to sport) and/or sociodemographic factors (geographic origins, age groups). Our map of the Twittersphere is the first of its kind for the Australian part of the global Twitter network, and also provides a first independent and scholarly estimation of the size of the total Australian Twitter population. In combination with our investigation of participation patterns in specific thematic hashtags, the map also enables us to examine which areas of the underlying follower/followee network are activated in the discussion of specific current topics – allowing new insights into the extent to which particular topics and issues are of interest to specialised niches or to the Australian public more broadly. Specifically, we examine the Twittersphere footprint of dedicated political discussion, under the #auspol hashtag, and compare it with the heightened, broader interest in Australian politics during election campaigns, using #ausvotes; we explore the different patterns of Twitter activity across the map for major television events (the popular competitive cooking show #masterchef, the British #royalwedding, and the annual #stateoforigin Rugby League sporting contest); and we investigate the circulation of links to the articles published by a number of major Australian news organisations across the network. Such analysis, which combines the ‘big data’-informed map and a close reading of individual communicative phenomena, makes it possible to trace the dynamic formation and dissolution of issue publics against the backdrop of longer-term network connections, and the circulation of information across these follower/followee links. Such research sheds light on the communicative dynamics of Twitter as a space for mediated social interaction. Our work demonstrates the possibilities inherent in the current ‘computational turn’ (Berry, 2010) in the digital humanities, as well as adding to the development and critical examination of methodologies for dealing with ‘big data’ (boyd and Crawford, 2011). Out tools and methods for doing Twitter research, released under Creative Commons licences through our project Website, provide the basis for replicable and verifiable digital humanities research on the processes of public communication which take place through this important new social network.

Genome-wide mapping of cystitis due to Streptococcus agalactiae and Escherichia coli in mice identifies a unique bladder transcriptome that signifies pathogen-specific antimicrobial defense against urinary tract infection

The most common causes of urinary tract infections (UTIs) are Gram-negative pathogens such as Escherichia coli; however, Gram-positive organisms including Streptococcus agalactiae, or group B streptococcus (GBS), also cause UTI. In GBS infection, UTI progresses to cystitis once the bacteria colonize bladder, but the host responses triggered in the bladder immediately following infection are largely unknown. Here, we used genome-wide expression profiling to map the bladder transcriptome of GBS UTI in mice infected transurethrally with uropathogenic GBS that was cultured from a 35 year-old women with cystitis. RNA from bladders was applied to Affymetrix Gene-1.0ST microarrays; qRT-PCR was used to analyze selected gene responses identified in array datasets. A surprisingly small significant gene list of 172 genes was identified at 24h; this compared to 2507 genes identified in a side-by-side comparison with uropathogenic E. coli (UPEC). No genes exhibited significantly altered expression at 2h in GBS-infected mice according to arrays despite high bladder bacterial loads at this early time point. The absence of a marked early host response to GBS juxtaposed with broad-based bladder responses activated by UPEC at 2h. Bioinformatics analyses including integrative systems-level network mapping revealed multiple activated biological pathways in the GBS cystitis transcriptome that regulate leukocyte activation, inflammation, apoptosis, and cytokine-chemokine biosynthesis. These findings define a novel, minimalistic type of bladder host response triggered by GBS UTI, which comprises collective antimicrobial pathways that differ dramatically from those activated by UPEC. Overall, this study emphasizes the unique nature of bladder immune activation mechanisms triggered by distinct uropathogens.

Monitoring the Australian Blogosphere through the 2007 Australian Federal Election

This paper examines the observable patterns of content creation by Australian political bloggers dur‐ing the 2007 election and its aftermath, thereby providing insight into the level and nature of activity in the Australian political blogosphere during that time. The performance indicators which are identi‐fied through this process enable us to target for further in‐depth research, to be reported in subse‐quent papers, those individual blogs and blog clusters showing especially high or unusual activity as compared to the overall baseline. This research forms the first stage in a larger project to investigate the shape and internal dynamics of the Australian political blogosphere. In this first stage, we tracked the activities of some 230 political blogs and related Websites in Australia from 2 November 2007 (the final month of the federal election campaign, with the election itself taking place on 24 Novem‐ber) to 24 January 2008. We harvested more than 65,000 articles for this study.

Challenges of tracking topical discussion networks online

Attempts to map online networks, representing relationships between people and sites, have covered sites including Facebook, Twitter, and blogs. However, the predominant approach of static network visualization, treating months of data as a single case rather than depicting changes over time or between topics, remains a flawed process. As different events and themes provoke varying interactions and conversations, it is proposed that case-by-case analysis would aid studies of online social networks by further examining the dynamics of links and information flows. This study uses hyperlink analysis of a population of French political blogs to compare connections between sites from January to August 2009. Themes discussed in this period were identified for subsequent analysis of topic-oriented networks. By comparing static blogrolls with topical citations within posts, this research addresses challenges and methods in mapping online networks, providing new information on temporal aspects of linking behaviors and information flows within these systems.

Blog research : the 'computational turn' [Blogforschung: Der 'Computational Turn']

ForscherInnen aus Sozial- und Geisteswissenschaften interessieren sich seit nunmehr einem Jahrzehnt für Blogs, Online-Tagebücher und Online-Journale. Auch wenn die Zuwachsrate der Blogosphäre seit der Blütezeit des Bloggens in den 2000ern stagniert, bleiben Blogs doch eines der bedeutendsten Genres der internetgestützten Kommunikation. Tatsächlich ist nach der Massenabwanderung zu Facebook, Twitter und anderen erst in jüngerer Zeit entstandenen Kommunikationsmitteln eine etwas kleinere, aber umso stärker etablierte Blogosphäre von engagierten und eingeschworenen Teilnehmenden übriggeblieben. Blogs werden mittlerweile als Teil einer institutionellen, persönlichen und Gruppen-Kommunikationstrategie akzeptiert. In Stil und Inhalt liegen sie zwischen den statischeren Informationen auf konventionellen Websites und den ständig aktualisierten Facebook- und Twitter-Newsfeeds. Blogs ermöglichen es ihren AutorInnen (und deren KommentatorInnen), bestimmte Themen im Umfang von einigen hundert bis zu einigen tausend Wörtern zu durchdenken, in kürzeren Posts ins Detail zu gehen und ggf. intensiver durchdachte Texte anderswo zu publizieren. Zudem sind sie auch ein sehr flexibles Medium: Bilder, Audio-, Video- sowie andere Materialien können mühelos eingefügt werden - und natürlich auch das grundlegende Instrument des Bloggens: Hyperlinks.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

Mapping personal trip OD from probe data

The paper analyses the expected value of OD volumes from probe with fixed error, error that is proportional to zone size and inversely proportional to zone size. To add realism to the analysis, real trip ODs in the Tokyo Metropolitan Region are synthesised. The results show that for small zone coding with average radius of 1.1km, and fixed measurement error of 100m, an accuracy of 70% can be expected. The equivalent accuracy for medium zone coding with average radius of 5km would translate into a fixed error of approximately 300m. As expected small zone coding is more sensitive than medium zone coding as the chances of the probe error envelope falling into adjacent zones are higher. For the same error radii, error proportional to zone size would deliver higher level of accuracy. As over half (54.8%) of the trip ends start or end at zone with equivalent radius of ≤ 1.2 km and only 13% of trips ends occurred at zones with equivalent radius ≥2.5km, measurement error that is proportional to zone size such as mobile phone would deliver higher level of accuracy. The synthesis of real OD with different probe error characteristics have shown that expected value of >85% is difficult to achieve for small zone coding with average radius of 1.1km. For most transport applications, OD matrix at medium zone coding is sufficient for transport management. From this study it can be drawn that GPS with error range between 2 and 5m, and at medium zone coding (average radius of 5km) would provide OD estimates greater than 90% of the expected value. However, for a typical mobile phone operating error range at medium zone coding the expected value would be lower than 85%. This paper assumes transmission of one origin and one destination positions from the probe. However, if multiple positions within the origin and destination zones are transmitted, map matching to transport network could be performed and it would greatly improve the accuracy of the probe data.

Decision support system for contractor pre-qualification : artificial neural network model

The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

Mapping a suburb with a single camera using a biologically inspired SLAM system

This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms. The core SLAM system, dubbed RatSLAM, is based on computational models of the rodent hippocampus, and is coupled with a lightweight vision system that provides odometry and appearance information. RatSLAM builds a map in an online manner, driving loop closure and relocalization through sequences of familiar visual scenes. Visual ambiguity is managed by maintaining multiple competing vehicle pose estimates, while cumulative errors in odometry are corrected after loop closure by a map correction algorithm. We demonstrate the mapping performance of the system on a 66 km car journey through a complex suburban road network. Using only a web camera operating at 10 Hz, RatSLAM generates a coherent map of the entire environment at real-time speed, correctly closing more than 51 loops of up to 5 km in length.

Simultaneous localisation and mapping from natural landmarks using RatSLAM

This paper describes the current state of RatSLAM, a Simultaneous Localisation and Mapping (SLAM) system based on models of the rodent hippocampus. RatSLAM uses a competitive attractor network to fuse visual and odometry information. Energy packets in the network represent pose hypotheses, which are updated by odometry and can be enhanced or inhibited by visual input. This paper shows the effectiveness of the system in real robot tests in unmodified indoor environments using a learning vision system. Results are shown for two test environments; a large corridor loop and the complete floor of an office building.