Saving bitrate vs. pleasing users : where is the break-even point in mobile video quality?

This paper presents a comprehensive study to find the most efficient bitrate requirement to deliver mobile video that optimizes bandwidth, while at the same time maintains good user viewing experience. In the study, forty participants were asked to choose the lowest quality video that would still provide for a comfortable and long-term viewing experience, knowing that higher video quality is more expensive and bandwidth intensive. This paper proposes the lowest pleasing bitrates and corresponding encoding parameters for five different content types: cartoon, movie, music, news and sports. It also explores how the lowest pleasing quality is influenced by content type, image resolution, bitrate, and user gender, prior viewing experience, and preference. In addition, it analyzes the trajectory of users’ progression while selecting the lowest pleasing quality. The findings reveal that the lowest bitrate requirement for a pleasing viewing experience is much higher than that of the lowest acceptable quality. Users’ criteria for the lowest pleasing video quality are related to the video’s content features, as well as its usage purpose and the user’s personal preferences. These findings can provide video providers guidance on what quality they should offer to please mobile users.

Effective hybrid recommendation combining users-searches correlations using tensors

Most recommendation methods employ item-item similarity measures or use ratings data to generate recommendations. These methods use traditional two dimensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective inter group recommendations. Web log data is multi-dimensional data. Unlike vector based methods, tensors have the ability to highly correlate and find latent relationships between such similar instances, consisting of users and searches. Non redundant rules from such associations of user-searches are then used for making recommendations to the users.

Improving web database search incorporating users query information

The growing importance and need of data processing for information extraction is vital for Web databases. Due to the sheer size and volume of databases, retrieval of relevant information as needed by users has become a cumbersome process. Information seekers are faced by information overloading - too many result sets are returned for their queries. Moreover, too few or no results are returned if a specific query is asked. This paper proposes a ranking algorithm that gives higher preference to a user’s current search and also utilizes profile information in order to obtain the relevant results for a user’s query.

Identifying interests of web users for effective recommendations

Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

Clustering of web users using the tensor decomposed models

We propose to use the Tensor Space Modeling (TSM) to represent and analyze the user’s web log data that consists of multiple interests and spans across multiple dimensions. Further we propose to use the decomposition factors of the Tensors for clustering the users based on similarity of search behaviour. Preliminary results show that the proposed method outperforms the traditional Vector Space Model (VSM) based clustering.

Convenience, loyal, and customising users : a survey of the behaviours and intentions of young online news users in Australia

The implications of the shift to online news consumption for journalism cultures and practices have attracted considerable scholarly attention and public debate. Less well considered are the implications of online news consumption for and by young people. This paper reports on research into the behaviours and intentions of online news consumers, 18-30 years of age, to propose three distinctive types of user (convenience, loyal and customising). Also opened up for discussion are questions about the strategic value to commercial news organisations of audience-centred empirical research that seeks to respond the crisis of professional journalism.

Automata modeling for cognitive interference in users' relevance judgement

Quantum theory has recently been employed to further advance the theory of information retrieval (IR). A challenging research topic is to investigate the so called quantum-like interference in users’ relevance judgement process, where users are involved to judge the relevance degree of each document with respect to a given query. In this process, users’ relevance judgement for the current document is often interfered by the judgement for previous documents, due to the interference on users’ cognitive status. Research from cognitive science has demonstrated some initial evidence of quantum-like cognitive interference in human decision making, which underpins the user’s relevance judgement process. This motivates us to model such cognitive interference in the relevance judgement process, which in our belief will lead to a better modeling and explanation of user behaviors in relevance judgement process for IR and eventually lead to more user-centric IR models. In this paper, we propose to use probabilistic automaton(PA) and quantum finite automaton (QFA), which are suitable to represent the transition of user judgement states, to dynamically model the cognitive interference when the user is judging a list of documents.

The ascendancy of oracy in university courses: Implications for teachers and second language users

This chapter reports on a study of oracy in a first-year university Business course, with particular interest in the oracy demands for second language-using international students. The research is relevant at a time when Higher Education is characterised by the confluence of increased international enrolments, more dialogic teaching and learning, and imperatives for teamwork and collaboration. Data sources for the study included videotaped lectures and tutorials, course documents, student surveys, and an interview with the lecturer. The findings pointed to a complex, oracy-laden environment where interactive talk fulfilled high-stakes functions related to social inclusion, the co-construction of knowledge, and the accomplishment of assessment tasks. The salience of talk posed significant challenges for students negotiating these core functions in their second language. The study highlights the oracy demands in university courses and foregrounds the need for university teachers, curriculum writers and speaking test developers to recognise these demands and explicate them for the benefit of all students.

Ad hoc innovation by users of social networks : the case of Twitter

Generic, flexible social media spaces such as Facebook and Twitter constitute an increasingly important element in our overall media repertoires. They provide a technological basis for instant and world-wide, ad hoc, many-to-many communication, and their effect on global communication patterns has already been highlighted. The short-messaging platform Twitter, for example, caters for uses ranging from interpersonal and quasi-private phatic exchanges to ‘ambient journalism’: ad hoc new reporting and dissemination as major events break. Many such uses have themselves emerged through user-driven processes: even standard Twitter conventions such as the @reply (to publicly address a fellow user) or the #hashtag(to collect related messages in an easily accessible space) are user inventions, in fact, and were incorporated into Twitter’s own infrastructure only subsequently. This demonstrates the substantial potential of social, user-led innovation in social media spaces.

Users adoption of web 2.0 for knowledge management : position paper

Web 2.0 is a new generation of online applications on the web that permit people to collaborate and share information online. The use of such applications by employees in organisations enhances knowledge management (KM) in organisations. Employee involvement is a critical success factor as the concept is based on openness, engagement and collaboration between people where organizational knowledge is derived from employees experience, skills and best practices. Consequently, the employee's perception is recognized as being an important factor in web 2.0 adoption for KM and worthy of investigation. There are few studies that define and explore employee's enterprise 2.0 acceptance for KM. This paper provides a systematic review of the literature prior to demonstrating the findings as part of a preliminary conceptual model that represents the first stage of an ongoing research project that will end up with an empirical study. Reviewing available studies in technology acceptance, knowledge management and enterprise 2.0 literatures aids obtaining all potential user acceptance factors of enterprise 2.0. The preliminary conceptual model is a refinement of the theory of planed behaviour (TPB) as the user acceptance factors has been mapped into the TPB main components including behaviour attitude, subjective norms and behaviour control which are the determinant of individual's intention to a particular behaviour.

Porous scaffold architecture guides tissue formation

Critical-sized bone defect regeneration is a remaining clinical concern. Numerous scaffold-based strategies are currently being investigated to enable in vivo bone defect healing. However, a deeper understanding of how a scaffold influences the tissue formation process and how this compares to endogenous bone formation or to regular fracture healing is missing. It is hypothesized that the porous scaffold architecture can serve as a guiding substrate to enable the formation of a structured fibrous network as a prerequirement for later bone formation. An ovine, tibial, 30-mm critical-sized defect is used as a model system to better understand the effect of the scaffold architecture on cell organization, fibrous tissue, and mineralized tissue formation mechanisms in vivo. Tissue regeneration patterns within two geometrically distinct macroscopic regions of a specific scaffold design, the scaffold wall and the endosteal cavity, are compared with tissue formation in an empty defect (negative control) and with cortical bone (positive control). Histology, backscattered electron imaging, scanning small-angle X-ray scattering, and nanoindentation are used to assess the morphology of fibrous and mineralized tissue, to measure the average mineral particle thickness and the degree of alignment, and to map the local elastic indentation modulus. The scaffold proves to function as a guiding substrate to the tissue formation process. It enables the arrangement of a structured fibrous tissue across the entire defect, which acts as a secondary supporting network for cells. Mineralization can then initiate along the fibrous network, resulting in bone ingrowth into a critical-sized defect, although not in complete bridging of the defect. The fibrous network morphology, which in turn is guided by the scaffold architecture, influences the microstructure of the newly formed bone. These results allow a deeper understanding of the mode of mineral tissue formation and the way this is influenced by the scaffold architecture. Copyright © 2012 American Society for Bone and Mineral Research.

Design process excludes users : the co-creation activities between user and designer

User needs are a fundamental element of design. If the design process does not properly reflect user needs, the design will be severely compromised. Therefore, it is worthwhile to investigate how the user is, and user needs are, understood in the design process. In this article, three accepted linear process models for web site and interactive media design are reviewed in terms of the designer and user participation. The article then proposes a user-evolving collaborative design process which is built on co-creation activities between designer and user. Co-creation activities across the entire design process structurally and ontologically reposition the users, and user needs, centrally, which allows the designers to holistically approach to the user needs through building a partnership with the users. Co-creation creates an equal evolving participatory process between user and designer towards sharing values and knowledge and creating new domains of collective creativity.