Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Face recognition across pose on video using eigen light-fields

We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.

Designing and evaluating mobile multimedia user experiences in public urban places : Making sense of the field

The majority of the world’s population now lives in cities (United Nations, 2008) resulting in an urban densification requiring people to live in closer proximity and share urban infrastructure such as streets, public transport, and parks within cities. However, “physical closeness does not mean social closeness” (Wellman, 2001, p. 234). Whereas it is a common practice to greet and chat with people you cross paths with in smaller villages, urban life is mainly anonymous and does not automatically come with a sense of community per se. Wellman (2001, p. 228) defines community “as networks of interpersonal ties that provide sociability, support, information, a sense of belonging and social identity.” While on the move or during leisure time, urban dwellers use their interactive information communication technology (ICT) devices to connect to their spatially distributed community while in an anonymous space. Putnam (1995) argues that available technology privatises and individualises the leisure time of urban dwellers. Furthermore, ICT is sometimes used to build a “cocoon” while in public to avoid direct contact with collocated people (Mainwaring et al., 2005; Bassoli et al., 2007; Crawford, 2008). Instead of using ICT devices to seclude oneself from the surrounding urban environment and the collocated people within, such devices could also be utilised to engage urban dwellers more with the urban environment and the urban dwellers within. Urban sociologists found that “what attracts people most, it would appear, is other people” (Whyte, 1980, p. 19) and “people and human activity are the greatest object of attention and interest” (Gehl, 1987, p. 31). On the other hand, sociologist Erving Goffman describes the concept of civil inattention, acknowledging strangers’ presence while in public but not interacting with them (Goffman, 1966). With this in mind, it appears that there is a contradiction between how people are using ICT in urban public places and for what reasons and how people use public urban places and how they behave and react to other collocated people. On the other hand there is an opportunity to employ ICT to create and influence experiences of people collocated in public urban places. The widespread use of location aware mobile devices equipped with Internet access is creating networked localities, a digital layer of geo-coded information on top of the physical world (Gordon & de Souza e Silva, 2011). Foursquare.com is an example of a location based 118 Mobile Multimedia – User and Technology Perspectives social network (LBSN) that enables urban dwellers to virtually check-in into places at which they are physically present in an urban space. Users compete over ‘mayorships’ of places with Foursquare friends as well as strangers and can share recommendations about the space. The research field of Urban Informatics is interested in these kinds of digital urban multimedia augmentations and how such augmentations, mediated through technology, can create or influence the UX of public urban places. “Urban informatics is the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people networks and urban infrastructures” (Foth et al., 2011, p. 4). One possibility to augment the urban space is to enable citizens to digitally interact with spaces and urban dwellers collocated in the past, present, and future. “Adding digital layer to the existing physical and social layers could facilitate new forms of interaction that reshape urban life” (Kjeldskov & Paay, 2006, p. 60). This methodological chapter investigates how the design of UX through such digital placebased mobile multimedia augmentations can be guided and evaluated. First, we describe three different applications that aim to create and influence the urban UX through mobile mediated interactions. Based on a review of literature, we describe how our integrated framework for designing and evaluating urban informatics experiences has been constructed. We conclude the chapter with a reflective discussion on the proposed framework.

The rise of co-creative consumers : user experience sharing behaviour in online communities

This thesis examines consumer initiated value co-creation behaviour in the context of convergent mobile online services using a Service-Dominant logic (SD logic) theoretical framework. It focuses on non-reciprocal marketing phenomena such as open innovation and user generated content whereby new viable business models are derived and consumer roles and community become essential to the success of business. Attention to customers. roles and personalised experiences in value co-creation has been recognised in the literature (e.g., Prahalad & Ramaswamy, 2000; Prahalad, 2004; Prahalad & Ramaswamy, 2004). Similarly, in a subsequent iteration of their 2004 version of the foundations of SD logic, Vargo and Lusch (2006) replaced the concept of value co-production with value co-creation and suggested that a value co-creation mindset is essential to underpin the firm-customer value creation relationship. Much of this focus, however, has been limited to firm initiated value co-creation (e.g., B2B or B2C), while consumer initiated value creation, particularly consumer-to-consumer (C2C) has received little attention in the SD logic literature. While it is recognised that not every consumer wishes to make the effort to engage extensively in co-creation processes (MacDonald & Uncles, 2009), some consumers may not be satisfied with a standard product, instead they engage in the effort required for personalisation that potentially leads to greater value for themselves, and which may benefit not only the firm, but other consumers as well. Literature suggests that there are consumers who do, and as a result initiate such behaviour and expend effort to engage in co-creation activity (e.g., Gruen, Osmonbekov and Czaplewski, 2006; 2007 MacDonald & Uncles, 2009). In terms of consumers. engagement in value proposition (co-production) and value actualisation (co-creation), SD logic (Vargo & Lusch, 2004, 2008) provides a new lens that enables marketing scholars to transcend existing marketing theory and facilitates marketing practitioners to initiate service centric and value co-creation oriented marketing practices. Although the active role of the consumer is acknowledged in the SD logic oriented literature, we know little about how and why consumers participate in a value co-creation process (Payne, Storbacka, & Frow, 2008). Literature suggests that researchers should focus on areas such as C2C interaction (Gummesson 2007; Nicholls 2010) and consumer experience sharing and co-creation (Belk 2009; Prahalad & Ramaswamy 2004). In particular, this thesis seeks to better understand consumer initiated value co-creation, which is aligned with the notion that consumers can be resource integrators (Baron & Harris, 2008) and more. The reason for this focus is that consumers today are more empowered in both online and offline contexts (Füller, Mühlbacher, Matzler, & Jawecki, 2009; Sweeney, 2007). Active consumers take initiatives to engage and co-create solutions with other active actors in the market for their betterment of life (Ballantyne & Varey, 2006; Grönroos & Ravald, 2009). In terms of the organisation of the thesis, this thesis first takes a „zoom-out. (Vargo & Lusch, 2011) approach and develops the Experience Co-Creation (ECo) framework that is aligned with balanced centricity (Gummesson, 2008) and Actor-to-Actor worldview (Vargo & Lusch, 2011). This ECo framework is based on an extended „SD logic friendly lexicon. (Lusch & Vargo, 2006): value initiation and value initiator, value-in-experience, betterment centricity and betterment outcomes, and experience co-creation contexts derived from five gaps identified from the SD logic literature review. The framework is also designed to accommodate broader marketing phenomena (i.e., both reciprocal and non-reciprocal marketing phenomena). After zooming out and establishing the ECo framework, the thesis takes a zoom-in approach and places attention back on the value co-creation process. Owing to the scope of the current research, this thesis focuses specifically on non-reciprocal value co-creation phenomena initiated by consumers in online communities. Two emergent concepts: User Experience Sharing (UES) and Co-Creative Consumers are proposed grounded in the ECo framework. Together, these two theorised concepts shed light on the following two propositions: (1) User Experience Sharing derives value-in-experience as consumers make initiative efforts to participate in value co-creation, and (2) Co-Creative Consumers are value initiators who perform UES. Three research questions were identified underpinning the scope of this research: RQ1: What factors influence consumers to exhibit User Experience Sharing behaviour? RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part of value co-creation behaviour? RQ3: What are the characteristics of Co-Creative Consumers? To answer these research questions, two theoretical models were developed: the User Experience Sharing Behaviour Model (UESBM) grounded in the Theory of Planned Behaviour framework, and the Co-Creative Consumer Motivation Model (CCMM) grounded in the Motivation, Opportunity, Ability framework. The models use SD logic consistent constructs and draw upon multiple streams of literature including consumer education, consumer psychology and consumer behaviour, and organisational psychology and organisational behaviour. These constructs include User Experience Sharing with Other Consumers (UESC), User Experience Sharing with Firms (UESF), Enjoyment in Helping Others (EIHO), Consumer Empowerment (EMP), Consumer Competence (COMP), and Intention to Engage in User Experience Sharing (INT), Attitudes toward User Experience Sharing (ATT) and Subjective Norm (SN) in the UESBM, and User Experience Sharing (UES), Consumer Citizenship (CIT), Relating Needs of Self (RELS) and Relating Needs of Others (RELO), Newness (NEW), Mavenism (MAV), Use Innovativeness (UI), Personal Initiative (PIN) and Communality (COMU) in the CCMM. Many of these constructs are relatively new to marketing and require further empirical evidence for support. Two studies were conducted to underpin the corresponding research questions. Study One was conducted to calibrate and re-specify the proposed models. Study Two was a replica study to confirm the proposed models. In Study One, data were collected from a PC DIY online community. In Study Two, a majority of data were collected from Apple product online communities. The data were examined using structural equation modelling and cluster analysis. Considering the nature of the forums, the Study One data is considered to reflect some characteristics of Prosumers and the Study Two data is considered to reflect some characteristics of Innovators. The results drawn from two independent samples (N = 326 and N = 294) provide empirical support for the overall structure theorised in the research models. The results in both models show that Enjoyment in Helping Others and Consumer Competence in the UESBM, and Consumer Citizenship and Relating Needs in CCMM have significant impacts on UES. The consistent results appeared in both Study One and Study Two. The results also support the conceptualisation of Co-Creative Consumers and indicate Co-Creative Consumers are individuals who are able to relate the needs of themselves and others and feel a responsibility to share their valuable personal experiences. In general, the results shed light on "How and why consumers voluntarily participate in the value co-creation process?. The findings provide evidence to conceptualise User Experience Sharing behaviour as well as the Co-Creative Consumer using the lens of SD logic. This research is a pioneering study that incorporates and empirically tests SD logic consistent constructs to examine a particular area of the logic – that is consumer initiated value co-creation behaviour. This thesis also informs practitioners about how to facilitate and understand factors that engage with either firm or consumer initiated online communities.

Personalised search – a hybrid approach for web information retrieval and its evaluation

Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

Teachers' recognition and referral of anxiety disorders in primary school children

This study investigated the ability of primary school teachers to recognise and refer children with anxiety symptoms. Two hundred and ninety-nine primary school teachers completed a questionnaire exploring their recognition and referral responses to five hypothetical vignettes that described boys and girls with varying severity of anxiety symptoms. Results revealed that teachers were generally able to recognise and make the decision to refer children with severe levels of anxiety. However, they had difficulty distinguishing between children with moderate anxiety symptoms and a severe anxiety disorder. Female teachers were more likely to refer children than were male teachers. The implications and future research are discussed.

Understanding user experience of mobile video : framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study.

Beyond difference : reconfiguring education for the user-led age

In recent years, various observers have pointed to the shifting paradigms of cultural and societal participation and economic production in developed nations. These changes are facilitated (although, importantly, not solely driven) by the emergence of new, participatory technologies of information access, knowledge exchange, and content production, many of whom are associated with Internet and new media technologies. In an online context, such technologies are now frequently described as social software, social media, or Web2.0, but their impact is no longer confined to cyberspace as an environment that is somehow different and separate from ‘real life’: user-led content and knowledge production is increasingly impacting on media, economy, law, social practices, and democracy itself.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Voices of experience : opportunities to influence creatively the designing of school libraries

Using a critical ethnographic approach this study investigates the potential for multiple voices of experience, of educators, designers/architects, education facility planners and students/learners, to influence creatively the designing of school libraries. School libraries are considered as social and cultural entities within the contexts of school life and of wider society. It is proposed that school library designing is a social interaction of concern to those influenced by its practices and outcomes. School library designing is therefore of significance to educators and students as well as to those with professionally accredited involvement in school library designing, such as designers/architects and education facility planners. The study contends that current approaches to educational space designing, including school libraries, amplify the voices of accredited designers and diminish or silence the voices of the user participants. The study is conceptualised as creative processes of discovery, through which attention is paid to the voices of experience of user and designer participants, and is concerned with their understandings and experiences of school libraries and their understandings and experiences of designing. Grounded theory coding (Charmaz) is used for initial categorising of interview data. Critical discourse analysis (CDA, Fairclough) is used as analytical tool for reflection on the literature and for analysis of the small stories gathered through semi-structured interviews, field observations and documents. The critical interpretive stance taken through CDA, enables discussions of aspects of power associated with the understandings and experiences of participants, and for recognition of creative possibilities and creative influence within and beyond current conditions. Through an emphasis on prospects for educators and students as makers of the spaces and places of learning, in particular in school libraries, the study has the potential to inform education facility designing practices and design participant relationships, and to contribute more broadly to knowledge in the fields of education, design, architecture, and education facility planning.

Bariatric patients and the use of mobile hoists : user experiences from three hospitals in South Australia

Nursing personnel are consistently identified as one of the occupational groups most at risk of work-related musculoskeletal disorders. During the moving and handling of bariatric patients, the weight of the patient combined with atypical body mass contributes to a significant risk of injury to the care provider and patient. This is further compounded by the shape, mobility and co-operation of the patient. The aim of this study was determine user experiences and design requirements for mobile hoists with bariatric patients. Structured interviews were conducted with six experienced injury management staff from the Manual Task Services department of three hospitals in Adelaide, South Australia. All staff had experience in patient handling, the use of patient handling equipment and the provision of patient handling training. A series of open-ended questions were structured around five main themes: 1) patient factors; 2) building/vehicle space and design; 3) equipment and furniture; 4) communication; and 5) staff issues. Questions focussed on the use of mobile hoists for lifting and transferring bariatric patients. Interviews were supplemented with a walk-through of the hospital to view the types of mobile hoists used, and the location and storage of equipment. Across the three hospitals there were differing classification systems to define bariatric patients. Ensuring patient dignity, respect and privacy were viewed as important in the management and rehabilitation of bariatric patients. Storage and space constraints were considered factors restricting the use of mobile floor hoists, with ceiling hoists being the preferred method for patient transfers. When using mobile floor hoists, the forces required to push, pull and manoeuvre, as well as sudden unstable movements of the hoist were considered important risks factors giving rise to a risk of injury to the care provider. Record keeping and purchasing policies appeared to inhibit the effective use of patient handling equipment. The moving and handling of bariatric patients presents complex and challenging issues. A co-ordinated and collaborative approach for moving and handling bariatric patients is needed across the range of care providers. Designers must consider both user and patient requirements.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

Probabilistic matching of image sets for video-based face recognition

We address the problem of face recognition on video by employing the recently proposed probabilistic linear discrimi-nant analysis (PLDA). The PLDA has been shown to be robust against pose and expression in image-based face recognition. In this research, the method is extended and applied to video where image set to image set matching is performed. We investigate two approaches of computing similarities between image sets using the PLDA: the closest pair approach and the holistic sets approach. To better model face appearances in video, we also propose the heteroscedastic version of the PLDA which learns the within-class covariance of each individual separately. Our experi-ments on the VidTIMIT and Honda datasets show that the combination of the heteroscedastic PLDA and the closest pair approach achieves the best performance.