The geometric modelling of social frames and contexts

How do humans respond to their social context? This question is becoming increasingly urgent in a society where democracy requires that the citizens of a country help to decide upon its policy directions, and yet those citizens frequently have very little knowledge of the complex issues that these policies seek to address. Frequently, we find that humans make their decisions more with reference to their social setting, than to the arguments of scientists, academics, and policy makers. It is broadly anticipated that the agent based modelling (ABM) of human behaviour will make it possible to treat such social effects, but we take the position here that a more sophisticated treatment of context will be required in many such models. While notions such as historical context (where the past history of an agent might affect its later actions) and situational context (where the agent will choose a different action in a different situation) abound in ABM scenarios, we will discuss a case of a potentially changing context, where social effects can have a strong influence upon the perceptions of a group of subjects. In particular, we shall discuss a recently reported case where a biased worm in an election debate led to significant distortions in the reports given by participants as to who won the debate (Davis et al 2011). Thus, participants in a different social context drew different conclusions about the perceived winner of the same debate, with associated significant differences among the two groups as to who they would vote for in the coming election. We extend this example to the problem of modelling the likely electoral responses of agents in the context of the climate change debate, and discuss the notion of interference between related questions that might be asked of an agent in a social simulation that was intended to simulate their likely responses. A modelling technology which could account for such strong social contextual effects would benefit regulatory bodies which need to navigate between multiple interests and concerns, and we shall present one viable avenue for constructing such a technology. A geometric approach will be presented, where the internal state of an agent is represented in a vector space, and their social context is naturally modelled as a set of basis states that are chosen with reference to the problem space.

Compact multiport antenna with isolated ports

The small element spacing of compact multiport arrays introduces strong mutual coupling between the antenna ports. Due to this coupling, the input impedance of the array changes when elements excitations are varied, and consequently, the array cannot be matched for an arbitrary excitation. Decoupling networks have in the past been used to provide an additional connection between antenna ports in order to cancel the coupling between elements. An alternative approach is to design the antenna so that each port does not excite a single element, but all elements simultaneously instead. The geometry of the antenna is optimized so that this direct excitation of elements counteracts the mutual coupling, thus yielding decoupled ports. This paper describes the design of such a 4-port antenna.

Frames of Anime: Culture and Image-Building

With the rising popularity of anime amongst animation students, audiences and scholars around the world, it has become increasingly important to critically analyse anime as being more than a ‘limited’ form of animation, and thematically as encompassing more than super robots and pocket monsters. Frames of Anime: Culture and Image-Building charts the development of Japanese animation from its indigenous roots within a native culture, through Japan’s experience of modernity and the impact of the Second World War. This text is the result of a rigorous study that recognises the heterogeneous and polymorphous background of anime. As such, Tze-Yue has adopted an ‘interdisciplinary and transnational’ (p. 7) approach to her enquiry, drawing upon face-to-face interviews, on-site visits and biographical writings of animators. Tze-Yue delineates anime from other forms of animation by linking its visual style to pre-modern Japanese art forms and demonstrating the connection it shares with an indigenous folk system of beliefs. Via the identification of traditional Japanese art forms and their visual connectedness to Japanese animation, Tze-Yue shows that the Japanese were already heavily engaged in what was destined to become anime once technology had enabled its production. Tze-Yue’s efforts to connect traditional Japanese art forms, and their artistic elements, to contemporary anime reveals that the Japanese already had a rich culture of visual storytelling that pre-dates modern animation. She identifies the Japanese form of the magic lantern at the turn of the 19th century, utsushi-e, as the pre-modern ancestor of Japanese animation, describing it as ‘Edo anime’ (p. 43). Along with utsushi-e, the Edo period also saw the woodblock print, ukiyo-e, being produced for the rising middle class (p. 32). Highlighting the ‘resurfacing’ of ‘realist’ approaches to Japanese art in ukiyo-e, Tze-Yue demonstrates the visual connection of ukiyo-e and anime in the …

ACE research vignette 018 : experiments in the MBA classroom : the case of time frames in project teams

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepeneurship researchers. In this vignette, Dr Rene Bakker considers project team dynamics and how executive education can be enriched by studying them in the classroom.

Towards spontaneous facial expression recognition in real-world video

Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

Forecasting success on large projects : developing reliable scales to predict multiple perspectives by multiple stakeholders over multiple time frames

Our aim is to develop a set of leading performance indicators to enable managers of large projects to forecast during project execution how various stakeholders will perceive success months or even years into the operation of the output. Large projects have many stakeholders who have different objectives for the project, its output, and the business objectives they will deliver. The output of a large project may have a lifetime that lasts for years, or even decades, and ultimate impacts that go beyond its immediate operation. How different stakeholders perceive success can change with time, and so the project manager needs leading performance indicators that go beyond the traditional triple constraint to forecast how key stakeholders will perceive success months or even years later. In this article, we develop a model for project success that identifies how project stakeholders might perceive success in the months and years following a project. We identify success or failure factors that will facilitate or mitigate against achievement of those success criteria, and a set of potential leading performance indicators that forecast how stakeholders will perceive success during the life of the project's output. We conducted a scale development study with 152 managers of large projects and identified two project success factor scales and seven stakeholder satisfaction scales that can be used by project managers to predict stakeholder satisfaction on projects and so may be used by the managers of large projects for the basis of project control.

Compact arrays for mobile platforms : trade-off between size and performance for SDMA and MIMO applications

Smart antenna receiver and transmitter systems consist of multi-port arrays with an individual receiver channel (including ADC) and an individual transmitter channel (including DAC)at every of the M antenna ports, respectively. By means of digital beamforming, an unlimited number of simultaneous complex-valued vector radiation patterns with M-1 degrees of freedom can be formed. Applications of smart antennas in communication systems include space-division multiple access. If both stations of a communication link are equipped with smart antennas (multiple-input-multiple-output, MIMO). multiple independent channels can be formed in a "multi-path-rich" environment. In this article, it will be shown that under certain circumstances, the correlation between signals from adjacent ports of a dense array (M + ΔM elements) can be kept as low as the correlation between signals from adjacent ports of a conventional array (M elements and half-wavelength pacing). This attractive feature is attained by means of a novel approach which employs a RF decoupling network at the array ports in order to form new ports which are decoupled and associated with mutually orthogonal (de-correlated) radiation patterns.

Maximal structuring of acyclic process models

This article addresses the transformation of a process model with an arbitrary topology into an equivalent structured process model. In particular, this article studies the subclass of process models that have no equivalent well-structured representation but which, nevertheless, can be partially structured into their maximally-structured representation. The transformations are performed under a behavioral equivalence notion that preserves the observed concurrency of tasks in equivalent process models. The article gives a full characterization of the subclass of acyclic process models that have no equivalent well-structured representation, but do have an equivalent maximally-structured one, as well as proposes a complete structuring method. Together with our previous results, this article completes the solution of the process model structuring problem for the class of acyclic process models.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

Analytical benchmark solutions for steel frame structures subject to local buckling effects

Application of "advanced analysis" methods suitable for non-linear analysis and design of steel frame structures permits direct and accurate determination of ultimate system strengths, without resort to simplified elastic methods of analysis and semi-empirical specification equations. However, the application of advanced analysis methods has previously been restricted to steel frames comprising only compact sections that are not influenced by the effects of local buckling. A research project has been conducted with the aim of developing concentrated plasticity methods suitable for practical advanced analysis of steel frame structures comprising non-compact sections. This paper contains a comprehensive set of analytical benchmark solutions for steel frames comprising non-compact sections, which can be used to verify the accuracy of simplified concentrated plasticity methods of advanced analysis. The analytical benchmark solutions were obtained using a distributed plasticity shell finite element model that explicitly accounts for the effects of gradual cross-sectional yielding, longitudinal spread of plasticity, initial geometric imperfections, residual stresses, and local buckling. A brief description and verification of the shell finite element model is provided in this paper.

Representing and discovering adversarial team behaviors using player roles

In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain. In comparison to other types of behavior, adversarial behavior is heavily structured as the location of a player (or agent) is dependent both on their teammates and adversaries, in addition to the tactics or strategies of the team. We present a method which can exploit this relationship through the use of a spatiotemporal basis model. As players constantly change roles during a match, we show that employing a "role-based" representation instead of one based on player "identity" can best exploit the playing structure. As vision-based systems currently do not provide perfect detection/tracking (e.g. missed or false detections), we show that our compact representation can effectively "denoise" erroneous detections as well as enabe temporal analysis, which was previously prohibitive due to the dimensionality of the signal. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labelled data.

Growing biodiverse carbon-rich forests

Regrowing forests on cleared land is a key strategy to achieve both biodiversity conservation and climate change mitigation globally. Maximizing these co-benefits, however, remains theoretically and technically challenging because of the complex relationship between carbon sequestration and biodiversity in forests, the strong influence of climate variability and landscape position on forest development, the large number of restoration strategies possible, and long time-frames needed to declare success. Through the synthesis of three decades of knowledge on forest dynamics and plant functional traits combined with decision science, we demonstrate that we cannot always maximize carbon sequestration by simply increasing the functional trait diversity of trees planted. The relationships between plant functional diversity, carbon sequestration rates above-ground and in the soil are dependent on climate and landscape positions. We show how to manage ‘identities’ and ‘complementarities’ between plant functional traits in order to achieve systematically maximal co-benefits in various climate and landscape contexts. We provide examples of optimal planting and thinning rules that satisfy this ecological strategy and guide the restoration of forests that are rich in both carbon and plant functional diversity. Our framework provides the first mechanistic approach for generating decision-making rules that can be used to manage forests for multiple objectives, and supports joined carbon credit and biodiversity conservation initiatives, such as Reducing Emissions from Deforestation and forest Degradation REDD+. The decision framework can also be linked to species distribution models and socio-economic models in order to find restoration solutions that maximize simultaneously biodiversity, carbon stocks and other ecosystem services across landscapes. Our study provides the foundation for developing and testing cost-effective and adaptable forest management rules to achieve biodiversity, carbon sequestration and other socio-economic co-benefits under global change.