Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

ADCS reaches adulthood : an analysis of the conference and its community over the last eighteen years

How influential is the Australian Document Computing Symposium (ADCS)? What do ADCS articles speak about and who cites them? Who is the ADCS community and how has it evolved? This paper considers eighteen years of ADCS, investigating both the conference and its community. A content analysis of the proceedings uncovers the diversity of topics covered in ADCS and how these have changed over the years. Citation analysis reveals the impact of the papers. The number of authors and where they originate from reveal who has contributed to the conference. Finally, we generate co-author networks which reveal the collaborations within the community. These networks show how clusters of researchers form, the effect geographic location has on collaboration, and how these have evolved over time.

Analysing governance categories used on project alliances in the construction industry

In Australia, collaborative contracts, and in particular, project alliances, have been increasingly used to govern infrastructure projects. These contracts use formal and informal governance mechanisms to manage the delivery of infrastructure projects. Formal mechanisms such as financial risk sharing are specified in the contract, while informal mechanisms such as integrated teams are not. Given that the literature contains a multiplicity of often untestable definitions, this paper reports on a review of the literature to operationalize the concepts of formal and informal governance. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operationalize formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; Williamson 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. A previous study by the authors identified that formal governance mechanisms can be classified into seven measurable categories: (1) negotiated cost, (2) competitive cost, (3) commercial framework, (4) risk and reward sharing, (5) qualitative performance, (6) collaborative multi-party agreement, and (7) early contractor involvement. Similarly, informal governance mechanisms can be classified into four measureable categories: (1) leadership structure, (2) integrated team, (3) team workshops, and (4) joint management system. This paper explores and further defines the key operational characteristics of each mechanism category, highlighting its impact on value for money in alliance project delivery. The paper’s contribution is that it provides the basis for future research to compare the impact of a range of individual mechanisms within each category, as a means of improving the performance of construction projects.

Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Mawson the astrobiologist rover : towards automatic recognition of stromatolites

This work aims at developing a planetary rover capable of acting as an assistant astrobiologist: making a preliminary analysis of the collected visual images that will help to make better use of the scientists time by pointing out the most interesting pieces of data. This paper focuses on the problem of detecting and recognising particular types of stromatolites. Inspired by the processes actual astrobiologists go through in the field when identifying stromatolites, the processes we investigate focus on recognising characteristics associated with biogenicity. The extraction of these characteristics is based on the analysis of geometrical structure enhanced by passing the images of stromatolites into an edge-detection filter and its Fourier Transform, revealing typical spatial frequency patterns. The proposed analysis is performed on both simulated images of stromatolite structures and images of real stromatolites taken in the field by astrobiologists.

Reliable automatic camera-laser calibration

Camera-laser calibration is necessary for many robotics and computer vision applications. However, existing calibration toolboxes still require laborious effort from the operator in order to achieve reliable and accurate results. This paper proposes algorithms that augment two existing trustful calibration methods with an automatic extraction of the calibration object from the sensor data. The result is a complete procedure that allows for automatic camera-laser calibration. The first stage of the procedure is automatic camera calibration which is useful in its own right for many applications. The chessboard extraction algorithm it provides is shown to outperform openly available techniques. The second stage completes the procedure by providing automatic camera-laser calibration. The procedure has been verified by extensive experimental tests with the proposed algorithms providing a major reduction in time required from an operator in comparison to manual methods.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

The mirror manoeuvre : telling the same story twice

The emerging field of ecopsychology is marked by two theoretical concerns which can be seen as mirror images of each other. One is the concern with what humans need, psychologically, from the non-human natural world (e.g. Wolsko & Lindberg 2013). The other is what nature needs from us (e.g. Swim 2013). Ecocriticism has been exploring these questions for at least two decades, but ecocritical theory examines ways of reading texts rather than ways of writing them (Bate 2000; Buell 2001; Garrard 2012). Undertaking theoretically-informed “creative manoeuvres”, and reflecting and reporting on the results, is one way for practice-led researchers in the field of creative writing to progress the knowledge claims of our discipline. This paper describes an ecowriting practice experiment based on the premise that specific techniques of narrative fiction writing can deepen reader engagement with ecopsychology’s twin concerns, and help motivate ecological action. Exploring this premise is time-critical given the current environmental crisis (Rust & Totton 2012), and emerging evidence that contemporary modes of representing the non-human natural world fail to elicit activist responses (Crompton & Kasser 2009; Joffe 2008). In the practice experiment reported here, a unique reading experience has been constructed such that the reader encounters from two different perspectives, through two different novels, a single story of humans benefiting from non-destructive interactions with non-human nature. This paper argues that the two novels create a complex and intense relationship between reader and story which generates specific psychological effects, and ultimately demands an activist response.

Towards robotic visual and acoustic stealth for outdoor dynamic target tracking

Covertly tracking mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms requires both visual and acoustic stealth. Whilst the use of robots for stealthy surveillance is not new, the majority only consider navigation for visual covertness. However, most fielded robotic systems have a non-negligible acoustic footprint arising from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. This time-varying acoustic signature can jeopardise any visual covertness and needs to be addressed in any stealthy navigation strategy. In previous work, we addressed the initial concepts for acoustically masking a tracking robot’s movements as it travels between observation locations selected to minimise its detectability by a dynamic natural target and ensuring con- tinuous visual tracking of the target. This work extends the overall concept by examining the utility of real-time acoustic signature self-assessment and exploiting shadows as hiding locations for use in a combined visual and acoustic stealth framework.

Benthic shift in a Solomon Islands' lagoon : corals to cyanobacteria

In June 2011 a large phytoplankton bloom resulted in a catastrophic mortality event that affected a large coastal embayment in the Solomon Islands. This consisted of an area in excess of 20 km2 of reef and soft sandy habitats in Marovo Lagoon, the largest double barrier lagoon in the world. This embayment is home to over 1200 people leading largely subsistence lifestyles depending on the impacted reefs for majority of their protein needs. A toxic diatom (Psuedo-nitzchia spp.) and toxic dinoflagellate (Pyrodinium bahamense var. compressum) reached concentrations of millions of cells per litre. The senescent phytoplankton bloom led to complete de-oxygenation of the water column that reportedly caused substantial mortality of marine animal life in the immediate area within a rapid timeframe (24 h). Groups affected included holothurians, crabs and reef and pelagic fish species. Dolphins, reptiles and birds were also found dead within the area, indicating algal toxin accumulation in the food chain. Deep reefs and sediments, whilst initially unaffected, have now been blanketed in large cyanobacterial mats which have negatively impacted live coral cover especially within the deep reef zone (> 6 m depth). Reef recovery within the deep zone has been extremely slow and may indicate an alternative state for the system.