Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

Future Information Communication Technology and Applications : ICFICE 2013

Focuses on the various aspects of advances in future information communication technology and its applications Presents the latest issues and progress in the area of future information communication technology Applicable to both researchers and professionals These proceedings are based on the 2013 International Conference on Future Information & Communication Engineering (ICFICE 2013), which will be held at Shenyang in China from June 24-26, 2013. The conference is open to all over the world, and participation from Asia-Pacific region is particularly encouraged. The focus of this conference is on all technical aspects of electronics, information, and communications ICFICE-13 will provide an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of FICE. In addition, the conference will publish high quality papers which are closely related to the various theories and practical applications in FICE. Furthermore, we expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject. "This work was supported by the NIPA (National IT Industry Promotion Agency) of Korea Grant funded by the Korean Government (Ministry of Science, ICT & Future Planning)."

Multiliteracies and a new metalanguage for the moving image

Globalised communication in society today is characterised by multimodal forms of meaning making in a context of increased cultural and linguistic diversity, calling for the teaching of multiliteracies. This transformation requires the development of a new metalanguage or language of description for the burgeoning and hybridised variety of text forms associated with information and multimedia technologies. To continue to teach to a narrow band of print-based genres, grammars, and skills is to ignore the reality of textual practices outside of schools. This paper draws from classroom research in a multiliteracies classroom to provide a multimodal analysis of a claymation movie. The significance of the paper is the synthesis of a multimodal metalanguage for teachers and students to describe the features of work in the kineikonic (moving image) mode.

Novel channel tracking and equalization methods in MU-MIMO-OFDM systems

The methodology undertaken, the channel model and the system model created for developing a novel adaptive equalization method and a novel channel tracking method for uplink of MU-MIMO-OFDM systems is presented in this paper. The results show that the channel tracking method works with 97% accuracy, while the training-based initial channel estimation method shows poor performance in estimating the actual channel comparatively.

Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

Cost effectiveness of patient education for the prevention of falls in hospital : economic evaluation from a randomized controlled trial

Background Falls are one of the most frequently occurring adverse events that impact upon the recovery of older hospital inpatients. Falls can threaten both immediate and longer-term health and independence. There is need to identify cost-effective means for preventing falls in hospitals. Hospital-based falls prevention interventions tested in randomized trials have not yet been subjected to economic evaluation. Methods Incremental cost-effectiveness analysis was undertaken from the health service provider perspective, over the period of hospitalization (time horizon) using the Australian Dollar (A$) at 2008 values. Analyses were based on data from a randomized trial among n = 1,206 acute and rehabilitation inpatients. Decision tree modeling with three-way sensitivity analyses were conducted using burden of disease estimates developed from trial data and previous research. The intervention was a multimedia patient education program provided with trained health professional follow-up shown to reduce falls among cognitively intact hospital patients. Results The short-term cost to a health service of one cognitively intact patient being a faller could be as high as A$14,591 (2008). The education program cost A$526 (2008) to prevent one cognitively intact patient becoming a faller and A$294 (2008) to prevent one fall based on primary trial data. These estimates were unstable due to high variability in the hospital costs accrued by individual patients involved in the trial. There was a 52% probability the complete program was both more effective and less costly (from the health service perspective) than providing usual care alone. Decision tree modeling sensitivity analyses identified that when provided in real life contexts, the program would be both more effective in preventing falls among cognitively intact inpatients and cost saving where the proportion of these patients who would otherwise fall under usual care conditions is at least 4.0%. Conclusions This economic evaluation was designed to assist health care providers decide in what circumstances this intervention should be provided. If the proportion of cognitively intact patients falling on a ward under usual care conditions is 4% or greater, then provision of the complete program in addition to usual care will likely both prevent falls and reduce costs for a health service.

Knowledge based urban development lessons from a non-western country : the Malaysia experience

Knowledge based urban development (KBUD) is seen as a new paradigm in urban planning and development which is now being implemented across the globe in order to increase the competitiveness of cities and regions. The KBUD concept has been widely applied in western and more developed countries over the last decade, and many have been proven successful. This paper, however, aims to provide an overview of the KBUD exercise in a context of a non western country scenario—Malaysia. Literature suggests that the urban development process in non western countries is different and very much focusing on physical elements. Whether this is the case or otherwise, this paper scrutinises the project of Multimedia Super Corridor (MSC), Malaysia, which is regarded as one of the first large scale manifestations of KBUD exercise in South East Asia. Based on development policies analysis and results of the interviews with the major stakeholders, this paper investigates the application of KBUD concept within the Malaysian context by examining the development and evolution of the city of Cyberjaya—the leading intelligent city of the MSC project. In the light of the literature and case findings, the paper provides recommendations and lessons learned, on the orchestration of KBUD, for other non western cities and regions that are working hard to develop KBUD strategies, strengthening their sustainable socio-spatial policies and seeking a global recognition.

User-centred study on quality of mobile video services

Mobile video, as an emerging market and a promising research field, has attracted much attention from both industry and researchers. Considering the quality of user-experience as the crux of mobile video services, this chapter aims to provide a guide to user-centered studies of mobile video quality. This will benefit future research in better understanding user needs and experiences, designing effective research, and providing solid solutions to improve the quality of mobile video. This chapter is organized in three main parts: (1) a review of recent user studies from the perspectives of research focuses, user study methods, and data analysis methods; (2) an example of conducting a user study of mobile video research, together with the discussion on a series of relative issues, such as participants, materials and devices, study procedure, and analysis results, and; (3) a conclusion with an open discussion about challenges and opportunities in mobile video related research, and associated potential future improvements.

BioCondition assessment tool : a mobile application to aid vegetation assessment

Environmental degradation has become increasingly aggressive in recent years due to rapid urban development and other land use pressures. This chapter looks at BioCondition, a newly developed vegetation assessment framework by Queensland Department of Resource Management (DERM) and how mobile technology can assist beginners in conducting the survey. Even though BioCondition is designed to be simple, it is still fairly inaccessible to beginners due to its complex, time consuming, and repetitive nature. A Windows Phone mobile application, BioCondition Assessment Tool, was developed to provide on-site guidance to beginners and document the assessment process for future revision and comparison. The application was tested in an experiment at Samford Conservation Park with 12 students studying ecology in Queensland University of Technology.

Speaker attribution of Australian broadcast news data

Speaker attribution is the task of annotating a spoken audio archive based on speaker identities. This can be achieved using speaker diarization and speaker linking. In our previous work, we proposed an efficient attribution system, using complete-linkage clustering, for conducting attribution of large sets of two-speaker telephone data. In this paper, we build on our proposed approach to achieve a robust system, applicable to multiple recording domains. To do this, we first extend the diarization module of our system to accommodate multi-speaker (>2) recordings. We achieve this through using a robust cross-likelihood ratio (CLR) threshold stopping criterion for clustering, as opposed to the original stopping criterion of two speakers used for telephone data. We evaluate this baseline diarization module across a dataset of Australian broadcast news recordings, showing a significant lack of diarization accuracy without previous knowledge of the true number of speakers within a recording. We thus propose applying an additional pass of complete-linkage clustering to the diarization module, demonstrating an absolute improvement of 20% in diarization error rate (DER). We then evaluate our proposed multi-domain attribution system across the broadcast news data, demonstrating achievable attribution error rates (AER) as low as 17%.

ADMRG @ MediaEval 2013 Social Event Detection

This paper elaborates the approach used by the Applied Data Mining Research Group (ADMRG) for the Social Event Detection (SED) Tasks of the 2013 MediaEval Benchmark. We extended the constrained clustering algorithm to apply to the first semi-supervised clustering task, and we compared several classifiers with Latent Dirichlet Allocation as feature selector in the second event classification task. The proposed approach focuses on scalability and efficient memory allocation when applied to a high dimensional data with large clusters. Results of the first task show the effectiveness of the proposed method. Results from task 2 indicate that attention on the imbalance categories distributions is needed.

Developing cultural responsiveness in environmental design students through digital storytelling and photovoice

As the Latino population in the United States grows, it will become increasingly important for undergraduate students in environmental design and related disciplines to become more culturally responsive and learn how to understand and address challenges faced by population groups, such as Latino youth. To this end, we involved environmental design undergraduate students at the University of Colorado in a service-learning class to mentor Latino youth in the creation of multimedia narratives using photovoice and digital storytelling techniques. The introduction of technology was used as a bridge between the two groups and to provide a platform for the Latino youth to reveal their community experiences. Based on focus group results, we describe the impact on the undergraduate students and provide recommendations for similar programs that can promote cultural responsiveness through the use of digital technology and prepare environmental design students to work successfully in increasingly diverse communities.

Australian Research to Encourage School Students’ Positive Use of Technology to Reduce Cyberbullying

Information and Communications Technology (ICT) has spread rapidly in Australia. Mobile phones, which increasingly have advanced capabilities including Internet access, mobile television and multimedia storage, are owned by 22% of Australian children aged 9-11 years and 73% of those aged 12-14 years (Australian Bureau of Statistics, 2012b), as well as by over 90% of Australians aged 15 years and over(Australian Communications and Media Authority (ACMA), 2010). Nearly 80% of Australian households have access to the Internet and 73% have a broadband Internet connection, ensuring that Internet access is typically reliable and high-speed (Australian Bureau of Statistics, 2012a). Ninety percent of Australian children aged 5-14 years (comprising 79% of 5-8 year olds; 96% of 9-11 year olds; and 98% of 12-14 year olds) reported having accessed the Internet during 2011-2012, a significant increase from 79% in 2008-2009 (Australian Bureau of Statistics, 2012b). Approximately 90% of 5-14 year olds have accessed the Internet both from home and from school, with close to 49% accessing the Internet from other places (Australian Bureau of Statistics, 2012b). Young people often make use of borrowed Internet access (e.g. in friends’ homes), commercial access (e.g. cybercafés), public access (e.g. libraries), and mobile device access in areas offering free Wi-Fi (Lim, 2009).

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

Acceptability-based QoE models for mobile video

Quality of experience (QoE) measures the overall perceived quality of mobile video delivery from subjective user experience and objective system performance. Current QoE computing models have two main limitations: 1) insufficient consideration of the factors influencing QoE, and; 2) limited studies on QoE models for acceptability prediction. In this paper, a set of novel acceptability-based QoE models, denoted as A-QoE, is proposed based on the results of comprehensive user studies on subjective quality acceptance assessments. The models are able to predict users’ acceptability and pleasantness in various mobile video usage scenarios. Statistical regression analysis has been used to build the models with a group of influencing factors as independent predictors, including encoding parameters and bitrate, video content characteristics, and mobile device display resolution. The performance of the proposed A-QoE models has been compared with three well-known objective Video Quality Assessment metrics: PSNR, SSIM and VQM. The proposed A-QoE models have high prediction accuracy and usage flexibility. Future user-centred mobile video delivery systems can benefit from applying the proposed QoE-based management to optimize video coding and quality delivery decisions.