Book review "Moving Innovation: A History of Computer Animation by Tom Sito , The MIT Press: Cambridge, MA, 2013"

As a Lecturer of Animation History and 3D Computer Animator, I received a copy of Moving Innovation: A History of Computer Animation by Tom Sito with an element of anticipation in the hope that this text would clarify the complex evolution of Computer Graphics (CG). Tom Sito did not disappoint, as this text weaves together the multiple development streams and convergent technologies and techniques throughout history that would ultimately result in modern CG. Universities now have students who have never known a world without computer animation and many students are younger than the first 3D CG animated feature film, Toy Story (1996); this text is ideal for teaching computer animation history and, as I would argue, it also provides a model for engaging young students in the study of animation history in general. This is because Sito places the development of computer animation within the context of its pre-digital ancestry and throughout the text he continues to link the discussion to the broader history of animation, its pioneers, technologies and techniques...

Advanced computer simulation of the milling process

Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

Diagnostic potential of saliva : state of the art and future applications [Potenziale diagnostico della saliva: stato dell’arte e applicazioni future]

Over the past 10 years, the use of saliva as a diagnostic fluid has gained attention and has become a translational research success story. Some of the current nanotechnologies have been demonstrated to have the analytical sensitivity required for the use of saliva as a diagnostic medium to detect and predict disease progression. However, these technologies have not yet been integrated into current clinical practice and work flow. As a diagnostic fluid, saliva offers advantages over serum because it can be collected noninvasively by individuals with modest training, and it offers a cost-effective approach for the screening of large populations. Gland-specific saliva can also be used for diagnosis of pathology specific to one of the major salivary glands. There is minimal risk of contracting infections during saliva collection, and saliva can be used in clinically challenging situations, such as obtaining samples from children or handicapped or anxious patients, in whom blood sampling could be a difficult act to perform. In this review we highlight the production of and secretion of saliva, the salivary proteome, transportation of biomolecules from blood capillaries to salivary glands, and the diagnostic potential of saliva for use in detection of cardiovascular disease and oral and breast cancers. We also highlight the barriers to application of saliva testing and its advancement in clinical settings. Saliva has the potential to become a first-line diagnostic sample of choice owing to the advancements in detection technologies coupled with combinations of biomolecules with clinical relevance.

“Conversations Before the End of Time” : Refuturing Applications of a New Media Praxis

This chapter examines how the methods, outcomes and transformative potentials of my new media arts praxis have been understood by a range of critical commentators from disciplinary perspectives outside of my own ‘home territory’ of media arts. By drawing upon perspectives from Human Computer Interface Design, Engineering, Sustainability Design, Tertiary Education, Communication Design and Public Librarianship I demonstrate how ideas from my arts disciplines have had tangible ‘external’ significance and application.

Processes of transformation : art into pop and back again

This research project was a case study for managing and innovating an interdisciplinary practice: specifically across music, performance and contemporary art. Key works included painting/sound/video installation, experimental performance, electronic pop music, music video and electronic pop music performance. An idiosyncratic and transformative use of colour emerged as an underlying theme and strategy for cohesion. The project offers strategies for the challenges of interdisciplinary practice specifically addressing the limitations related to institutionalised value systems, aesthetic traditions and disciplinary languages.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Biologically inspired SLAM using Wi-Fi

Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi-Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi-Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

Design for creative activity : a framework for analyzing the creative potential of computer games

This paper describes a design framework intended to conceptually map the influence that game design has on the creative activity people engage in during gameplay. The framework builds on behavioral and verbal analysis of people playing puzzle games. The analysis was designed to better understand the extent to which gameplay activities within different games facilitate creative problem solving. We have used an expert review process to evaluate these games in terms of their game design elements and have taken a cognitive action approach to this process to investigate how particular elements produce the potential for creative activity. This paper proposes guidelines that build upon our understanding of the relationship between the creative processes that players undertake during a game and the components of the game that allow these processes to occur. These guidelines may be used in the game design process to better facilitate creative gameplay activity.

BOSTER : an efficient algorithm for mining frequent unordered induced subtrees

Extracting frequent subtrees from the tree structured data has important applications in Web mining. In this paper, we introduce a novel canonical form for rooted labelled unordered trees called the balanced-optimal-search canonical form (BOCF) that can handle the isomorphism problem efficiently. Using BOCF, we define a tree structure guided scheme based enumeration approach that systematically enumerates only the valid subtrees. Finally, we present the balanced optimal search tree miner (BOSTER) algorithm based on BOCF and the proposed enumeration approach, for finding frequent induced subtrees from a database of labelled rooted unordered trees. Experiments on the real datasets compare the efficiency of BOSTER over the two state-of-the-art algorithms for mining induced unordered subtrees, HybridTreeMiner and UNI3. The results are encouraging.

BEST : an efficient algorithm for mining frequent unordered embedded subtrees

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.

Adapting “8-bit” motion style to 3D computer animation for Wreck-it Ralph

Tangled (2011) demonstrated that Walt Disney Animation has successfully extended the traditional Disney animation aesthetic to the 3D medium. The very next film produced by the studio however, Wreck-it Ralph (2012), required the animators (trained in the traditional Disney style) to develop a limited style of animation inspired by the 8-bit motion of 1980s video games. This paper examines the 8-bit style motion in Wreck-it Ralph to understand if and how the principles of animation were adapted for the film.

Manuel Aires Mateus : an architecture for the art of life [曼努埃尔·艾利斯·马特乌斯：建筑，为了生活的艺术]

This text is the outcome of a conversation with Manuel Aires Mateus (Aires Mateus Arquitectos) and discusses the importance of architecture and memory in contemporary architectural productions

Memory management and parallelization of data intensive all-to-all comparison in shared-memory systems

This thesis presents a novel program parallelization technique incorporating with dynamic and static scheduling. It utilizes a problem specific pattern developed from the prior knowledge of the targeted problem abstraction. Suitable for solving complex parallelization problems such as data intensive all-to-all comparison constrained by memory, the technique delivers more robust and faster task scheduling compared to the state-of-the art techniques. Good performance is achieved from the technique in data intensive bioinformatics applications.

Text mining with semantic annotation : using enriched text representation for entity-oriented retrieval, semantic relation identification and text clustering

This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.