Exploration and optimization of user experience in viewing videos on a mobile phone

Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user’s viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user’s acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user’s assessment criteria and to support the quantitative results from a user’s perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user’s opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

Defending web services against denial of service attacks using client puzzles

The interoperable and loosely-coupled web services architecture, while beneficial, can be resource-intensive, and is thus susceptible to denial of service (DoS) attacks in which an attacker can use a relatively insignificant amount of resources to exhaust the computational resources of a web service. We investigate the effectiveness of defending web services from DoS attacks using client puzzles, a cryptographic countermeasure which provides a form of gradual authentication by requiring the client to solve some computationally difficult problems before access is granted. In particular, we describe a mechanism for integrating a hash-based puzzle into existing web services frameworks and analyze the effectiveness of the countermeasure using a variety of scenarios on a network testbed. Client puzzles are an effective defence against flooding attacks. They can also mitigate certain types of semantic-based attacks, although they may not be the optimal solution.

Consumers’ intentions to adopt 3G in regional cities in China : a comparative study

Rapid mobile technological evolution and the large economic stake in commercial development of mobile technological innovation make it necessary to understand consumers' motivations towards the latest advanced and updated technologies and services. 3G (the third generation of mobile communication technology) recently started its commercial development in the world‘s largest mobile communication market, China, after being delayed for a few years. Although China fell behind in commercially developing 3G, it is difficult to ignore studying this area, given the size of the market and promising future developments. This market deserves focused research attention, especially in terms of consumer behaviour towards the adoption of mobile technological innovation. Thus, the program of research in this thesis was designed to investigate how Chinese consumers respond to the use of this newly launched mobile technological innovation, with a focus on what factors affect their 3G adoption intentions. It aimed to yield important insights into Chinese consumers‘ innovation adoption behaviours and to contribute to marketing and innovation adoption research. Furthermore, it has been documented that Chinese consumers vary widely between regions in dialect, lifestyle, culture, purchasing power and consumption attitudes. Based on economic development and local culture, China can be divided geographically into distinctive regional consumer markets. Consequently, the results of consumer behaviour research in one region may not necessarily be extrapolated to other regions. In order to better understand Chinese consumers, the disparities between regions should not be overlooked. Therefore, another objective of this program of research was to examine regional variances in consumers' innovation adoption, specifically to identify the similarities and differences in factors influencing 3G adoption, contributing to intra-cultural studies. An extensive literature review identified two gaps: current China-based innovation adoption research studies are limited in providing adequate prediction and explanation of Chinese consumers' intentions to adopt 3G; and there was limited knowledge about the differences between regional Chinese consumers in innovation adoption. Two research questions therefore were developed to address these gaps: 1) What factors influence Chinese consumers' intentions to adopt 3G? 2) How do Chinese consumers differ between regional markets in the relative influence of the factors in determining their intentions to adopt 3G? In accordance with postpositivist research philosophy, two studies were designed to answer the research questions, using mixed methods. To meet the research objectives, the two studies were both conducted in three regional cities, namely Beijing, Shanghai and Wuhan, centred in the three regions of North China, East China and Central China respectively, with sufficient cultural and economical regional variances. Study One was an exploratory study with qualitative research methods. It involved 45 in-depth interviews in the three research cities to gain rich insights into the research context from natural settings. Eight important concepts related to 3G adoption were generated from analysis of the interview data, namely utilitarian expectation, hedonic expectation, status gains, status loss avoidance, normative influence, external influence, cost and quality concern. The concepts of social loss avoidance and quality concern were two unique findings, whereas the other concepts were similar to the findings in Western innovation adoption studies. Moreover, variances in 3G adoption between three groups of regional consumers were also identified, focusing on the perceptions of two concepts, namely status gains and normative influence. The conceptual research model was then developed incorporating the eight concepts plus the dependent variable of adoption intention. The hypothesized relationships between the nine constructs and hypotheses about the differences between regional consumers in 3G adoption were informed by the findings of Study One and the literature reviewed. Study Two was a quantitative study involving a web-based survey and statistical analysis procedure. The web-based survey attracted 800 residents from the three research cities, 270 from Beijing, 265 from Shanghai and 265 from Wuhan. They comprised three research samples for this study and consequently three sets of data were obtained. The data was analysed by Structural Equation Modelling together with Multi-group Analysis. The analysis confirmed that the concepts generated in Study One were influential factors affecting Chinese consumers' 3G adoption intention, with the exception of the concept external influence. Differences were found between the samples in the three research cities in the effect of hedonic expectation, status gains, status loss avoidance and normative influence on 3G adoption intention. The two Studies undertaken in this thesis contributed a better understanding of Chinese consumers' intentions to adopt advanced mobile technological innovation, namely 3G, in three regional markets. This knowledge contributes to innovation adoption and intra-cultural research, as well as consumer behaviour theory. It is also able to inform international and domestic telecommunication companies to develop and deliver more effective marketing strategies across Chinese regional markets. Limitations in the research were identified in terms of the sampling techniques used and the design of the two Studies. Future research was suggested in other Chinese regional markets and into consumer adoption of other types of mobile technological innovations.

Start playing with your food : fun food experiences with mobile social media

Healthy and sustainable food is gaining more attention from consumers, industry, and researchers. Yet many approaches to date are limited to information dissemination, advertisement or education. We have embarked on a three year collaborative research project (2011 – 2013) to explore urban food practices – eating, cooking, growing food – to support the well-being of people and the environment. Our overall goal is to employ a user-centred interaction design research approach to inform the development of entertaining, real-time, mobile and networked applications, engaging playful feedback to build motivation. Our aspiration for this study is to deliver usable and useful mobile and situated interaction prototypes that employ individual and group strategies to foster food cultures that provide new pathways to produce, share and enjoy food that is green, healthy, and fun.

Information extraction from web services : a comparison of Tokenisation algorithms

Most web service discovery systems use keyword-based search algorithms and, although partially successful, sometimes fail to satisfy some users information needs. This has given rise to several semantics-based approaches that look to go beyond simple attribute matching and try to capture the semantics of services. However, the results reported in the literature vary and in many cases are worse than the results obtained by keyword-based systems. We believe the accuracy of the mechanisms used to extract tokens from the non-natural language sections of WSDL files directly affects the performance of these techniques, because some of them can be more sensitive to noise. In this paper three existing tokenization algorithms are evaluated and a new algorithm that outperforms all the algorithms found in the literature is introduced.

GPFlow: an intuitive environment for web-based scientific workflow

Increasingly scientists are using collections of software tools in their research. These tools are typically used in concert, often necessitating laborious and error-prone manual data reformatting and transfer. We present an intuitive workflow environment to support scientists with their research. The workflow, GPFlow, wraps legacy tools, presenting a high level, interactive web-based front end to scientists. The workflow backend is realized by a commercial grade workflow engine (Windows Workflow Foundation). The workflow model is inspired by spreadsheets and is novel in its support for an intuitive method of interaction enabling experimentation as required by many scientists, e.g. bioinformaticians. We apply GPFlow to two bioinformatics experiments and demonstrate its flexibility and simplicity.

Online banking customization via tag-based interaction

In this paper, we describe ongoing work on online banking customization with a particular focus on interaction. The scope of the study is confined to the Australian banking context where the lack of customization is evident. This paper puts forward the notion of using tags to facilitate personalized interactions in online banking. We argue that tags can afford simple and intuitive interactions unique to every individual in both online and mobile environments. Firstly, through a review of related literature, we frame our work in the customization domain. Secondly, we define a range of taggable resources in online banking. Thirdly, we describe our preliminary prototype implementation with respect to interaction customization types. Lastly, we conclude with a discussion on future work.

Mobile banking customization via user-defined tags

In this paper, we describe on-going work on mobile banking customization, particularly in the Australian context. The use of user-defined tags to facilitate personalized interactions in the mobile context is explored. The aim of this research is to find ways to improve mobile banking interaction. Customization is more significant in the mobile context than online due to factors such as smaller screen sizes and limited software and hardware capabilities, placing an increased emphasis on usability. This paper explains how user-defined tags can aid different types of customization at the interaction level. A preliminary prototype has been developed to demonstrate the mechanics of the proposed approach. Potential implications, design decisions and limitations are discussed with an outline of future work.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

Approximate Membership Localization within a Web-Based Join Framework

In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.

Is there an App for that? : social media uses for road safety

The use of social media has increased dramatically in recent years in the areas of public health and injury prevention, with many organisations creating online and social media content. Despite the adoption of such media by modern society, research relating to the design and evaluation of social media for the promotion of health issues is very much in its infancy. A timely review of the available evidence in relation to the use of social media campaigns from both the road safety and broader public health context will be undertaken. In particular, this paper will address the questions of what social media should be developed, how it should be evaluated, as well as what should be the key measures of success and to what extent do these measures relate to practically significant outcomes, such as behaviour change. Much like more traditional media campaigns, social media may be best regarded as another approach within the array of potential approaches that a health advertising researcher or practitioner may utilise. With younger demographics becoming less likely to engage with more traditional advertising mediums relative to their preference for social media, social media‟s most important role in the road safety advertising context may be to offer the means of delivering road safety messages to high risk, younger road users.

Capturing affective experiences using the SMS experience sampling (SMS-ES) method

This paper reports the feasibility and methodological considerations of using the Short Message System Experience Sampling (SMS-ES) Method, which is an experience sampling research method developed to assist researchers to collect repeat measures of consumers’ affective experiences. The method combines SMS with web-based technology in a simple yet effective way. It is described using a practical implementation study that collected consumers’ emotions in response to using mobile phones in everyday situations. The method is further evaluated in terms of the quality of data collected in the study, as well as against the methodological considerations for experience sampling studies. These two evaluations suggest that the SMS-ES Method is both a valid and reliable approach for collecting consumers’ affective experiences. Moreover, the method can be applied across a range of for-profit and not-for-profit contexts where researchers want to capture repeated measures of consumers’ affective experiences occurring over a period of time. The benefits of the method are discussed to assist researchers who wish to apply the SMS-ES Method in their own research designs.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.