A noticeboard in "both worlds" unsurprising interfaces supporting easy bi-cultural content publication

We describe the design of a digital noticeboard to support communication within a remote Aboriginal community whose aspiration is to live in "both worlds", nurturing and extending their Aboriginal culture and actively participating in Western society and economy. Three bi-cultural aspects have emerged and are presented here: the need for a bi-lingual noticeboard to span both oral and written language traditions, the tension between perfunctory information exchange and social, embodied protocols of telling in person and the different ways in which time is represented in both cultures. The design approach, developed iteratively through consultation, demonstration and testing led to an "unsurprising interface", aimed at maximizing use and appropriation across cultures by unifying visual, text and spoken contents in both passive and interactive displays in a modeless manner.

Cues in the environment: A design principle for ambient intelligence

The aim of this paper is to propose design principles for ambient intelligence (AmI) environments. The question we are investigating is how these environments can be designed to support a group to be able to carry out common goal-oriented activities. The approach we are taking in answering this question is informed by the concept of collective intelligence (CI). We are applying the concept of CI to AmI as we have found it works well in biological and social systems. Examples from nature demonstrate the power of CI stimulated by implicit cues in the environment. We use these examples to derive design principles for AmI environments. By applying these design principles to a concrete scenario, we are able to propose ways to help decrease environmental pollution within urban areas.

Cooperative game play with avatars and agents: Differences in brain activity and the experience of play

The current study sought to identify the impact of whether teammates in a cooperative videogame were controlled by other humans (avatars) or by the game (agents). The impact on player experience was explored through both subjective questionnaire measures and brain wave activity measurement (electroencephalography). Play with human teammates was associated with a greater sense of relatedness, but less competence and flow than play with other computer-controlled teammates. In terms of brain activity, play with human teammates was associated with greater activity in the alpha, theta and beta power bands than play with computer-controlled teammates. Overall, the results suggest that play with human teammates involves greater cognitive activity in terms of 'mentalising' than play with computer-controlled teammates. Additionally, the associations between subjective measures of player experience and brain activity are described. Limitations of the current study are identified and key directions for future research are discussed.

Predicting query reformulation during web searching

This paper reports results from a study in which we automatically classified the query reformulation patterns for 964,780 Web searching sessions (composed of 1,523,072 queries) in order to predict what the next query reformulation would be. We employed an n-gram modeling approach to describe the probability of searchers transitioning from one query reformulation state to another and predict their next state. We developed first, second, third, and fourth order models and evaluated each model for accuracy of prediction. Findings show that Reformulation and Assistance account for approximately 45 percent of all query reformulations. Searchers seem to seek system searching assistant early in the session or after a content change. The results of our evaluations show that the first and second order models provided the best predictability, between 28 and 40 percent overall, and higher than 70 percent for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance in real time.

Improved algebraic cryptanalysis of QUAD, Bivium and Trivium via graph partitioning on equation systems

We present a novel approach for preprocessing systems of polynomial equations via graph partitioning. The variable-sharing graph of a system of polynomial equations is defined. If such graph is disconnected, then the corresponding system of equations can be split into smaller ones that can be solved individually. This can provide a tremendous speed-up in computing the solution to the system, but is unlikely to occur either randomly or in applications. However, by deleting certain vertices on the graph, the variable-sharing graph could be disconnected in a balanced fashion, and in turn the system of polynomial equations would be separated into smaller systems of near-equal sizes. In graph theory terms, this process is equivalent to finding balanced vertex partitions with minimum-weight vertex separators. The techniques of finding these vertex partitions are discussed, and experiments are performed to evaluate its practicality for general graphs and systems of polynomial equations. Applications of this approach in algebraic cryptanalysis on symmetric ciphers are presented: For the QUAD family of stream ciphers, we show how a malicious party can manufacture conforming systems that can be easily broken. For the stream ciphers Bivium and Trivium, we nachieve significant speedups in algebraic attacks against them, mainly in a partial key guess scenario. In each of these cases, the systems of polynomial equations involved are well-suited to our graph partitioning method. These results may open a new avenue for evaluating the security of symmetric ciphers against algebraic attacks.

Women are people too : the problem of designing for gender

Cultural theory breaks with Modern analysis by rejecting traditional notions of race, gender, class and sexuality. In doing so, alternative frameworks such as Post-Feminism emerge which are useful for thinking about culture, technology and what our interactions with it mean. From a Post-Feminist perspective it can be seen how in our multi-cultural, post-industrial, digitized world, there is space to move beyond traditional ways of dividing up society such as ‘male’ and ‘female’. We are then free to re-construct our identity in light of a rich diversity of individually relevant experiences. Therefore, in order to get a better understanding of the highly nuanced cultural interactions that characterize our use of technology, this paper argues against using the inherently stereotyped lens of gender and allowing a new set of user needs to emerge.

Welcome to the jungle : HCI after dark

The transformation of urban spaces that occurs once darkness falls is simultaneously exhilarating and menacing, and over the past 20 months we have investigated the potential for mobile technology to help users manage their personal safety concerns in the city at night. Our findings subverted commonly held notions of vulnerability, with the threat of violence felt equally by men and women. But while women felt protected because of their mobile technology, men dismissed it as digital Man Mace. We addressed this macho design challenge by studying remote engineers in outback Australia to inspire our personal safety design prototype MATE (Mobile Artifact for Taming Environments).

Engaging energy saving through motivation-specific social comparison

Comparison is widely used in research projects and commercial products whose goal is to motivate energy saving at home. This research builds on fundamental theories from social psychology in an attempt to shed light on how to motivate consumers to conserve energy by providing relevant people for social comparison depending on consumer’s motivation to compare. To support the research process, the mobile application EnergyWiz was developed through a theory-driven design approach. Along with other features EnergyWiz provides users with three types of social comparison – normative, one-on-one and ranking. The results of interviews with prospective users are used to derive design suggestions for relevant people for comparison (comparison subjects).

An observational study of how objects support engineering design thinking and communication : implications for the design of tangible media

There has been an increasing interest in objects within the HCI field particularly with a view to designing tangible interfaces. However, little is known about how people make sense of objects and how objects support thinking. This paper presents a study of groups of engineers using physical objects to prototype designs, and articulates the roles that physical objects play in supporting their design thinking and communications. The study finds that design thinking is heavily dependent upon physical objects, that designers are active and opportunistic in seeking out physical props and that the interpretation and use of an object depends heavily on the activity. The paper discusses the trade-offs that designers make between speed and accuracy of models, and specificity and generality in choice of representations. Implications for design of tangible interfaces are discussed.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Discovering novel knowledge using granule mining

This paper presents an extended granule mining based methodology, to effectively describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other granules, it provides a kind of novel knowledge in databases. We also provide an algorithm to implement the proposed methodology. The experiments conducted to characterize a real network traffic data collection show that the proposed concepts and algorithm are promising.

Food and interaction design [Extended Abstract]

Food and interaction design presents an interesting challenge to the HCI community in attending to the pervasive nature of food, the socio-cultural differences in food practices and a changing global foodscape. To design for meaningful and positive interactions it is essential to identify daily food practices and the opportunities for the design of technology to support such practices. This workshop brings together a community of researchers and practitioners in human-food interaction to attend to the practical and theoretical difficulties in designing for human-food interactions in everyday life. Through a practical field study and workshop we explore themes of food experiences, health and wellbeing, sustainability and alternative food cultures.

Eigenvoice modeling for cross likelihood ratio based speaker clustering : a Bayesian approach

This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.