Learning personalized tag ontology from user tagging information

The cross-sections of the Social Web and the Semantic Web has put folksonomy in the spot light for its potential in overcoming knowledge acquisition bottleneck and providing insight for "wisdom of the crowds". Folksonomy which comes as the results of collaborative tagging activities has provided insight into user's understanding about Web resources which might be useful for searching and organizing purposes. However, collaborative tagging vocabulary poses some challenges since tags are freely chosen by users and may exhibit synonymy and polysemy problem. In order to overcome these challenges and boost the potential of folksonomy as emergence semantics we propose to consolidate the diverse vocabulary into a consolidated entities and concepts. We propose to extract a tag ontology by ontology learning process to represent the semantics of a tagging community. This paper presents a novel approach to learn the ontology based on the widely used lexical database WordNet. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. We provide empirical evaluations by using the semantic information contained in the ontology in a tag recommendation experiment. The results show that by using the semantic relationships on the ontology the accuracy of the tag recommender has been improved.

Timed and Probabilistic Automata for Automatic Animal Call Recognition

Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

Fatalism, superstition, religion, and culture : road user beliefs and behaviour in Pakistan

Road traffic crashes have emerged as a major health problem around the world. Road crash fatalities and injuries have been reduced significantly in developed countries, but they are still an issue in low and middle-income countries. The World Health Organization (WHO, 2009) estimates that the death toll from road crashes in low- and middle-income nations is more than 1 million people per year, or about 90% of the global road toll, even though these countries only account for 48% of the world's vehicles. Furthermore, it is estimated that approximately 265,000 people die every year in road crashes in South Asian countries and Pakistan stands out with 41,494 approximately deaths per year. Pakistan has the highest rate of fatalities per 100,000 population in the region and its road crash fatality rate of 25.3 per 100,000 population is more than three times that of Australia's. High numbers of road crashes not only cause pain and suffering to the population at large, but are also a serious drain on the country's economy, which Pakistan can ill-afford. Most studies identify human factors as the main set of contributing factors to road crashes, well ahead of road environment and vehicle factors. In developing countries especially, attention and resources are required in order to improve things such as vehicle roadworthiness and poor road infrastructure. However, attention to human factors is also critical. Human factors which contribute to crashes include high risk behaviours like speeding and drink driving, and neglect of protective behaviours such as helmet wearing and seat belt wearing. Much research has been devoted to the attitudes, beliefs and perceptions which contribute to these behaviours and omissions, in order to develop interventions aimed at increasing safer road use behaviours and thereby reducing crashes. However, less progress has been made in addressing human factors contributing to crashes in developing countries as compared to the many improvements in road environments and vehicle standards, and this is especially true of fatalistic beliefs and behaviours. This is a significant omission, since in different cultures in developing countries there are strong worldviews in which predestination persists as a central idea, i.e. that one's life (and death) and other events have been mapped out and are predetermined. Fatalism refers to a particular way in which people regard the events that occur in their lives, usually expressed as a belief that an individual does not have personal control over circumstances and that their lives are determined through a divine or powerful external agency (Hazen & Ehiri, 2006). These views are at odds with the dominant themes of modern health promotion movements, and present significant challenges for health advocates who aim to avert road crashes and diminish their consequences. The limited literature on fatalism reveals that it is not a simple concept, with religion, culture, superstition, experience, education and degree of perceived control of one's life all being implicated in accounts of fatalism. One distinction in the literature that seems promising is the distinction between empirical and theological fatalism, although there are areas of uncertainty about how well-defined the distinction between these types of fatalism is. Research into road safety in Pakistan is scarce, as is the case for other South Asian countries. From the review of the literature conducted, it is clear that the descriptions given of the different belief systems in developing countries including Pakistan are not entirely helpful for health promotion purposes and that further research is warranted on the influence of fatalism, superstition and other related beliefs in road safety. Based on the information available, a conceptual framework is developed as a means of structuring and focusing the research and analysis. The framework is focused on the influence of fatalism, superstition, religion and culture on beliefs about crashes and road user behaviour. Accordingly, this research aims to provide an understanding of the operation of fatalism and related beliefs in Pakistan to assist in the development and implementation of effective and culturally appropriate interventions. The research examines the influence of fatalism, superstition, religious and cultural beliefs on risky road use in Pakistan and is guided by three research questions: 1. What are the perceptions of road crash causation in Pakistan, in particular the role of fatalism, superstition, religious and cultural beliefs? 2. How does fatalism, superstition, and religious and cultural beliefs influence road user behaviour in Pakistan? 3. Do fatalism, superstition, and religious and cultural beliefs work as obstacles to road safety interventions in Pakistan? To address these questions, a qualitative research methodology was developed. The research focused on gathering data through individual in-depth interviewing using a semi-structured interview format. A sample of 30 participants was interviewed in Pakistan in the cities of Lahore, Rawalpindi and Islamabad. The participants included policy makers (with responsibility for traffic law), experienced police officers, religious orators, professional drivers (truck, bus and taxi) and general drivers selected through a combination of purposive, criterion and snowball sampling. The transcripts were translated from Urdu and analysed using a thematic analysis approach guided by the conceptual framework. The findings were divided into four areas: attribution of crash causation to fatalism; attribution of road crashes to beliefs about superstition and malicious acts; beliefs about road crash causation linked to popular concepts of religion; and implications for behaviour, safety and enforcement. Fatalism was almost universally evident, and expressed in a number of ways. Fate was used to rationalise fatal crashes using the argument that the people killed were destined to die that day, one way or another. Related to this was the sense of either not being fully in control of the vehicle, or not needing to take safety precautions, because crashes were predestined anyway. A variety of superstitious-based crash attributions and coping methods to deal with road crashes were also found, such as belief in the role of the evil eye in contributing to road crashes and the use of black magic by rivals or enemies as a crash cause. There were also beliefs related to popular conceptions of religion, such as the role of crashes as a test of life or a source of martyrdom. However, superstitions did not appear to be an alternative to religious beliefs. Fate appeared as the 'default attribution' for a crash when all other explanations failed to account for the incident. This pervasive belief was utilised to justify risky road use behaviour and to resist messages about preventive measures. There was a strong religious underpinning to the statement of fatalistic beliefs (this reflects popular conceptions of Islam rather than scholarly interpretations), but also an overlap with superstitious and other culturally and religious-based beliefs which have longer-standing roots in Pakistani culture. A particular issue which is explored in more detail is the way in which these beliefs and their interpretation within Pakistani society contributed to poor police reporting of crashes. The pervasive nature of fatalistic beliefs in Pakistan affects road user behaviour by supporting continued risk taking behaviour on the road, and by interfering with public health messages about behaviours which would reduce the risk of traffic crashes. The widespread influence of these beliefs on the ways that people respond to traffic crashes and the death of family members contribute to low crash reporting rates and to a system which appears difficult to change. Fate also appeared to be a major contributing factor to non-reporting of road crashes. There also appeared to be a relationship between police enforcement and (lack of) awareness of road rules. It also appears likely that beliefs can influence police work, especially in the case of road crash investigation and the development of strategies. It is anticipated that the findings could be used as a blueprint for the design of interventions aimed at influencing broad-spectrum health attitudes and practices among the communities where fatalism is prevalent. The findings have also identified aspects of beliefs that have complex social implications when designing and piloting driver intervention strategies. By understanding attitudes and behaviours related to fatalism, superstition and other related concepts, it should be possible to improve the education of general road users, such that they are less likely to attribute road crashes to chance, fate, or superstition. This study also underscores the understanding of this issue in high echelons of society (e.g., policy makers, senior police officers) as their role is vital in dispelling road users' misconceptions about the risks of road crashes. The promotion of an evidence or scientifically-based approach to road user behaviour and road safety is recommended, along with improved professional education for police and policy makers.

The ethnographer as community manager : language translation and user negotiation

This article investigates the ethnographic methodological question of how the researcher observes objectively while being part of the problem they are observing. It uses a case study of ABC Pool to argue a cooperative approach that combines the roles of the ethnographer with that of a community manager who assists in constructing a true representation of the researched environment. By using reflexivity as a research tool, the ethnographer engages in a process to self-check their personal presumptions and prejudices, and to strengthen the constructed representation of the researched environment. This article also suggests combining management and expertise research from the social sciences with ethnography, to understand and engage with the research field participants more intimately - which, ultimately, assists in gathering and analysing richer qualitative data.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

The role of the internet and digital technologies in the struggle for recognition of the forgotten Australians

Our contemporary public sphere has seen the 'emergence of new political rituals, which are concerned with the stains of the past, with self disclosure, and with ways of remembering once taboo and traumatic events' (Misztal, 2005). A recent case of this phenomenon occurred in Australia in 2009 with the apology to the 'Forgotten Australians': a group who suffered abuse and neglect after being removed from their parents – either in Australia or in the UK - and placed in Church and State run institutions in Australia between 1930 and 1970. This campaign for recognition by a profoundly marginalized group coincides with the decade in which the opportunities of Web 2.0 were seen to be diffusing throughout different social groups, and were considered a tool for social inclusion. This paper examines the case of the Forgotten Australians as an opportunity to investigate the role of the internet in cultural trauma and public apology. As such, it adds to recent scholarship on the role of digital web based technologies in commemoration and memorials (Arthur, 2009; Haskins, 2007; Cohen and Willis, 2004), and on digital storytelling in the context of trauma (Klaebe, 2011) by locating their role in a broader and emerging domain of social responsibility and political action (Alexander, 2004).

Social cars : sensing, gathering, sharing and conveying social cues to road users

Intelligent Transport Systems (ITS) resembles the infrastructure for ubiquitous computing in the car. It encompasses a) all kinds of sensing technologies within vehicles as well as road infrastructure, b) wireless communication protocols for the sensed information to be exchanged between vehicles (V2V) and between vehicles and infrastructure (V2I), and c) appropriate intelligent algorithms and computational technologies that process these real-time streams of information. As such, ITS can be considered a game changer. It provides the fundamental basis of new, innovative concepts and applications, similar to the Internet itself. The information sensed or gathered within or around the vehicle has led to a variety of context-aware in-vehicular technologies within the car. A simple example is the Anti-lock Breaking System (ABS), which releases the breaks when sensors detect that the wheels are locked. We refer to this type of context awareness as vehicle/technology awareness. V2V and V2I communication, often summarized as V2X, enables the exchange and sharing of sensed information amongst cars. As a result, the vehicle/technology awareness horizon of each individual car is expanded beyond its observable surrounding, paving the way to technologically enhance such already advanced systems. In this chapter, we draw attention to those application areas of sensing and V2X technologies, where the human (driver), the human’s behavior and hence the psychological perspective plays a more pivotal role. The focal points of our project are illustrated in Figure 1: In all areas, the vehicle first (1) gathers or senses information about the driver. Rather than to limit the use of such information towards vehicle/technology awareness, we see great potential for applications in which this sensed information is then (2) fed back to the driver for an increased self-awareness. In addition, by using V2V technologies, it can also be (3) passed to surrounding drivers for an increased social awareness, or (4), pushed even further, into the cloud, where it is collected and visualized for an increased, collective urban awareness within the urban community at large, which includes all city dwellers.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Data transformations in custom digital workflows : property graphs as a data model for user-defined mappings

This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0.

Personalized recommender systems integrating tags and item taxonomy

The social tags in Web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

Towards a secure human-and-computer mutual authentication protocol

We blend research from human-computer interface (HCI) design with computational based crypto- graphic provable security. We explore the notion of practice-oriented provable security (POPS), moving the focus to a higher level of abstraction (POPS+) for use in providing provable security for security ceremonies involving humans. In doing so we high- light some challenges and paradigm shifts required to achieve meaningful provable security for a protocol which includes a human. We move the focus of security ceremonies from being protocols in their context of use, to the protocols being cryptographic building blocks in a higher level protocol (the security cere- mony), which POPS can be applied to. In order to illustrate the need for our approach, we analyse both a protocol proven secure in theory, and a similar proto- col implemented by a �nancial institution, from both HCI and cryptographic perspectives.

Improving the efficiency of RFID authentication with pre-computation

Security of RFID authentication protocols has received considerable interest recently. However, an important aspect of such protocols that has not received as much attention is the efficiency of their communication. In this paper we investigate the efficiency benefits of pre-computation for time-constrained applications in small to medium RFID networks. We also outline a protocol utilizing this mechanism in order to demonstrate the benefits and drawbacks of using thisapproach. The proposed protocol shows promising results as it is able to offer the security of untraceableprotocols whilst only requiring the time comparable to that of more efficient but traceable protocols.