Rodent Scope: A User-Configurable Digital Wireless Telemetry System for Freely Behaving Animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

Technique for evaluating photo sharing interfaces with the early prototypes - group simulation

User evaluations using paper prototypes commonly lack social context. The Group simulation technique described in this paper offers a solution to this problem. The study introduces an early-phase participatory design technique targeted for small groups. The proposed technique is used for evaluating an interface, which enables group work in photo collection creation. Three groups of four users, 12 in total, took part in a simulation session where they tested a low-fidelity design concept that included their own personal photo content from an event that their group attended together. The users’ own content was used to evoke natural experiences. Our results indicate that the technique helped users to naturally engage with the prototype in the session. The technique is suggested to be suitable for evaluating other early-phase concepts and to guide design solutions, especially with the concepts that include users’ personal content and enable content sharing.

Active awareness : supporting the intentional disclosure of awareness information in collaborative systems

This thesis opens up the design space for awareness research in CSCW and HCI. By challenging the prevalent understanding of roles in awareness processes and exploring different mechanisms for actively engaging users in the awareness process, this thesis provides a better understanding of the complexity of these processes and suggests practical solutions for designing and implementing systems that support active awareness. Mutual awareness, a prominent research topic in the fields of Computer-Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI) refers to a fundamental aspect of a person’s work: their ability to gain a better understanding of a situation by perceiving and interpreting their co-workers actions. Technologically-mediated awareness, used to support co-workers across distributed settings, distinguishes between the roles of the actor, whose actions are often limited to being the target of an automated data gathering processes, and the receiver, who wants to be made aware of the actors’ actions. This receiver-centric view of awareness, focusing on helping receivers to deal with complex sets of awareness information, stands in stark contrast to our understanding of awareness as social process involving complex interactions between both actors and receivers. It fails to take into account an actors’ intimate understanding of their own activities and the contribution that this subjective understanding could make in providing richer awareness information. In this thesis I challenge the prevalent receiver-centric notion of awareness, and explore the conceptual foundations, design, implementation and evaluation of an alternative active awareness approach by making the following five contributions. Firstly, I identify the limitations of existing awareness research and solicit further evidence to support the notion of active awareness. I analyse ethnographic workplace studies that demonstrate how actors engage in an intricate interplay involving the monitoring of their co-workers progress and displaying aspects of their activities that may be of relevance to others. The examination of a large body of awareness research reveals that while disclosing information is a common practice in face-to-face collaborative settings it has been neglected in implementations of technically mediated awareness. Based on these considerations, I introduce the notion of intentional disclosure to describe the action of users actively and deliberately contributing awareness information. I consider challenges and potential solutions for the design of active awareness. I compare a range of systems, each allowing users to share information about their activities at various levels of detail. I discuss one of the main challenges to active awareness: that disclosing information about activities requires some degree of effort. I discuss various representations of effort in collaborative work. These considerations reveal that there is a trade-off between the richness of awareness information and the effort required to provide this information. I propose a framework for active awareness, aimed to help designers to understand the scope and limitations of different types of intentional disclosure. I draw on the identified richness/effort trade-off to develop two types of intentional disclosure, both of which aim to facilitate the disclosure of information while reducing the effort required to do so. For both of these approaches, direct and indirect disclosure, I delineate how they differ from related approaches and define a set of design criteria that is intended to guide their implementation. I demonstrate how the framework of active awareness can be practically applied by building two proof-of-concept prototypes that implement direct and indirect disclosure respectively. AnyBiff, implementing direct disclosure, allows users to create, share and use shared representations of activities in order to express their current actions and intentions. SphereX, implementing indirect disclosure, represents shared areas of interests or working context, and links sets of activities to these representations. Lastly, I present the results of the qualitative evaluation of the two prototypes and analyse the results with regard to the extent to which they implemented their respective disclosure mechanisms and supported active awareness. Both systems were deployed and tested in real world environments. The results for AnyBiff showed that users developed a wide range of activity representations, some unanticipated, and actively used the system to disclose information. The results further highlighted a number of design considerations relating to the relationship between awareness and communication, and the role of ambiguity. The evaluation of SphereX validated the feasibility of the indirect disclosure approach. However, the study highlighted the challenges of implementing cross-application awareness support and translating the concept to users. The study resulted in design recommendations aimed to improve the implementation of future systems.

Introduction to the special issue on next generation network architectures, protocols, theory, systems and applications

This special issue of Networking Science focuses on Next Generation Network (NGN) that enables the deployment of access independent services over converged fixed and mobile networks. NGN is a packet-based network and uses the Internet protocol (IP) to transport the various types of traffic (voice, video, data and signalling). NGN facilitates easy adoption of distributed computing applications by providing high speed connectivity in a converged networked environment. It also makes end user devices and applications highly intelligent and efficient by empowering them with programmability and remote configuration options. However, there are a number of important challenges in provisioning next generation network technologies in a converged communication environment. Some preliminary challenges include those that relate to QoS, switching and routing, management and control, and security which must be addressed on an urgent or emergency basis. The consideration of architectural issues in the design and pro- vision of secure services for NGN deserves special attention and hence is the main theme of this special issue.

Effective channel state information (CSI) feedback for MIMO systems in wireless broadband communications

This research has analysed both reciprocity and feedback mechanisms in multi-antenna wireless systems. It has presented the basis of an effective CSI feedback mechanism that efficiently provides the transmitter with the minimum information to allow the accurate knowledge of a rapidly changing channel. The simulations have been conducted using MATLAB to measure the improvement when the channel is estimated at the receiver in a 2 X 2 multi-antenna system and compared to the case of perfect channel knowledge at the receiver.

Tensor-based item recommendation using probabilistic ranking in social tagging systems

A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Multi-touch interfaces across a wide range of hardware platforms are becoming pervasive. This is due to the adoption of smart phones and tablets in both the consumer and corporate market place. This paper proposes a human-machine interface to interact with unmanned aerial systems based on the philosophy of multi-touch hardware-independent high-level interaction with multiple systems simultaneously. Our approach incorporates emerging development methods for multi-touch interfaces on mobile platforms. A framework is defined for supporting multiple protocols. An open source solution is presented that demonstrates: architecture supporting different communications hardware; an extensible approach for supporting multiple protocols; and the ability to monitor and interact with multiple UAVs from multiple clients simultaneously. Validation tests were conducted to assess the performance, scalability and impact on packet latency under different client configurations.

Participatory Data Analytics: Collaborative interfaces for data composition and visualisation

This research proposes the development of interfaces to support collaborative, community-driven inquiry into data, which we refer to as Participatory Data Analytics. Since the investigation is led by local communities, it is not possible to anticipate which data will be relevant and what questions are going to be asked. Therefore, users have to be able to construct and tailor visualisations to their own needs. The poster presents early work towards defining a suitable compositional model, which will allow users to mix, match, and manipulate data sets to obtain visual representations with little-to-no programming knowledge. Following a user-centred design process, we are subsequently planning to identify appropriate interaction techniques and metaphors for generating such visual specifications on wall-sized, multi-touch displays.

Controlling current and voltage type interfaces in power-hardware-in-the-loop simulations

The usual practice to study a large power system is through digital computer simulation. However, the impact of large scale use of small distributed generators on a power network cannot be evaluated strictly by simulation since many of these components cannot be accurately modelled. Moreover, the network complexity makes the task of practical testing on a physical network nearly impossible. This study discusses the paradigm of interfacing a real-time simulation of a power system to real-life hardware devices. This type of splitting a network into two parts and running a real-time simulation with a physical system in parallel is usually termed as power-hardware-in-the-loop (PHIL) simulation. The hardware part is driven by a voltage source converter that amplifies the signals of the simulator. In this paper, the effects of suitable control strategy on the performance of PHIL and the associated stability aspects are analysed in detail. The analyses are validated through several experimental tests using an real-time digital simulator.

Users’ perception of using web search engines and their impact on the perceived intention to reuse the systems

In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

Item reputation-aware recommender systems

Recommender systems provide personalized advice for customers online based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems use users’ ratings to generate their output. In this paper, we propose to combine reputation models with recommender systems to enhance the accuracy of recommendations. The main contributions include two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively, and a personalized reputation method to generate item reputations based on users’ interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.