A Boundary-Oriented Chinese Segmentation Method Using NGram Mutual Information

This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We implemented an n-gram mutual information (NGMI) based segmentation algorithm with the mixed-up features from unsupervised, supervised and dictionarybased segmentation methods. This algorithm is also combined with a simple strategy for out-of-vocabulary (OOV) word recognition. The evaluation for both open and closed training shows encouraging results of our system. The results for OOV word recognition in closed training evaluation were however found unsatisfactory.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

Multi-level neural modelling : an application of object-oriented software engineering

Neu-Model, an ongoing project aimed at developing a neural simulation environment that is extremely computationally powerful and flexible, is described. It is shown that the use of good Software Engineering techniques in Neu-Model’s design and implementation is resulting in a high performance system that is powerful and flexible enough to allow rigorous exploration of brain function at a variety of conceptual levels.

Market segmentation : insights for changing children's physical activity behaviour

Market segmentation has received relatively limited attention in social marketing, particularly within the context of changing children’s physical activity behaviour. This is an important area of investigation given growing concern over childhood obesity globally. The present research aims to extend current understanding of the applicability of market segmentation within this context. The results of a two-step cluster analysis on data from 512 respondents of an online survey show three distinct segments of caregivers, each with unique beliefs about their primary school children walking to/from school. The results demonstrate the validity of employing the process of market segmentation within this social context and provide further insights for targeting the identified segments through tailored social marketing programs.

Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

A new model for airport passenger segmentation

Recent changes in the aviation industry and in the expectations of travellers have begun to alter the way we approach our understanding, and thus the segmentation, of airport passengers. The key to successful segmentation of any population lies in the selection of the criteria on which the partitions are based. Increasingly, the basic criteria used to segment passengers (purpose of trip and frequency of travel) no longer provide adequate insights into the passenger experience. In this paper, we propose a new model for passenger segmentation based on the passenger core value, time. The results are based on qualitative research conducted in-situ at Brisbane International Terminal during 2012-2013. Based on our research, a relationship between time sensitivity and degree of passenger engagement was identified. This relationship was used as the basis for a new passenger segmentation model, namely: Airport Enthusiast (engaged, non time sensitive); Time Filler (non engaged, non time sensitive); Efficiency Lover (non engaged, time sensitive) and Efficient Enthusiast (engaged, time sensitive). The outcomes of this research extend the theoretical knowledge about passenger experience in the terminal environment. These new insights can ultimately be used to optimise the allocation of space for future terminal planning and design.

Differential segmentation responses to an alcohol social marketing program

Objective This study seeks establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. Methodology This study is part of a larger cluster randomized controlled evaluation of the Game On: Know Alcohol (GOKA) program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, expectancies and refusal self-efficacy of identified segments was subsequently examined. Results Three segments were identified: (1) Abstainers (2) Bingers (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post participation were observed for the Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. Conclusions These findings provide preliminary empirical evidence supporting application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments is indicated to extend the social marketing footprint in alcohol education.

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Evaluation of object detection proposals under condition variations

Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.

A determinism and desire: Some neurological processes in perceiving the design object

The environment moderates behaviour using a subtle language of ‘affordances’ and ‘behaviour-settings’. Affordances are environmental offerings. They are objects that demand action; a cliff demands a leap and binoculars demand a peek. Behaviour-settings are ‘places;’ spaces encoded with expectations and meanings. Behaviour-settings work the opposite way to affordances; they demand inhibition; an introspective demeanour in a church or when under surveillance. Most affordances and behaviour-settings are designed, and as such, designers are effectively predicting brain reactions. • Affordances are nested within, and moderated by behaviour-settings. Both trigger automatic neural responses (excitation and inhibition). These, for the best part cancel each other out. This balancing enables object recognition and allows choice about what action should be taken (if any). But when excitation exceeds inhibition, instinctive action will automatically commence. In positive circumstances this may mean laughter or a smile. In negative circumstances, fleeing, screaming or other panic responses are likely. People with poor frontal function, due to immaturity (childhood or developmental disorders) or due to hypofrontality (schizophrenia, brain damage or dementia) have a reduced capacity to balance excitatory and inhibitory impulses. For these people, environmental behavioural demands increase with the decline of frontal brain function. • The world around us is not only encoded with symbols and sensory information. Opportunities and restrictions work on a much more primal level. Person/space interactions constantly take place at a molecular scale. Every space we enter has its own special dynamic, where individualism vies for supremacy between the opposing forces of affordance-related excitation and the inhibition intrinsic to behaviour-settings. And in this context, even a small change–the installation of a CCTV camera can turn a circus to a prison. • This paper draws on cutting-edge neurological theory to understand the psychological determinates of the everyday experience of the designed environment.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.

A perfusion fMRI investigation of thematic and categorical context effects in the spoken production of object names

The context in which objects are presented influences the speed at which they are named. We employed the blocked cyclic naming paradigm and perfusion functional magnetic resonance imaging (fMRI) to investigate the mechanisms responsible for interference effects reported for thematicallyand categorically related compared to unrelated contexts. Naming objects in categorically homogeneous contexts induced a significant interference effect that accumulated from the second cycle onwards. This interference effect was associated with significant perfusion signal decreases in left middle and posterior lateral temporal cortex and the hippocampus. By contrast, thematically homogeneous contexts facilitated naming latencies significantly in the first cycle and did not differ from heterogeneous contexts thereafter, nor were they associated with any perfusion signal changes compared to heterogeneous contexts. These results are interpreted as being consistent with an account in which the interference effect both originates and has its locus at the lexical level, with an incremental learning mechanism adapting the activation levels of target lexical representations following access. We discuss the implications of these findings for accounts that assume thematic relations can be active lexical competitors or assume mandatory involvement of top-down control mechanisms in interference effects during naming.

Interference from object part relations in spoken word production: Behavioural and fMRI evidence

Objects presented in categorically related contexts are typically named slower than objects presented in unrelated contexts, a phenomenon termed semantic interference. However, not all semantic relationships induce interference. In the present study, we investigated the influence of object part-relations in the blocked cyclic naming paradigm. In Experiment 1 we established that an object's parts do induce a semantic interference effect when named in context compared to unrelated parts (e.g., leaf, root, nut, bark; for tree). In Experiment 2) we replicated the effect during perfusion functional magnetic resonance imaging (fMRI) to identify the cerebral regions involved. The interference effect was associated with significant perfusion signal increases in the hippocampal formation and decreases in the dorsolateral prefrontal cortex. We failed to observe significant perfusion signal changes in the left lateral temporal lobe, a region that shows reliable activity for interference effects induced by categorical relations in the same paradigm and is proposed to mediate lexical-semantic processing. We interpret these results as supporting recent explanations of semantic interference in blocked cyclic naming that implicate working memory mechanisms. However, given the failure to observe significant perfusion signal changes in the left temporal lobe, the results provide only partial support for accounts that assume semantic interference in this paradigm arises solely due to lexical-level processes.