Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

On the recognition of abstract Markov policies

Abstraction plays an essential role in the way the agents plan their behaviours, especially to reduce the computational complexity of planning in large domains. However, the effects of abstraction in the inverse process – plan recognition – are unclear. In this paper, we present a method for recognising the agent’s behaviour in noisy and uncertain domains, and across multiple levels of abstraction. We use the concept of abstract Markov policies in abstract probabilistic planning as the model of the agent’s behaviours and employ probabilistic inference in Dynamic Bayesian Networks (DBN) to infer the correct policy from a sequence of observations. When the states are fully observable, we show that for a broad and often-used class of abstract policies, the complexity of policy recognition scales well with the number of abstraction levels in the policy hierarchy. For the partially observable case, we derive an efficient hybrid inference scheme on the corresponding DBN to overcome the exponential complexity.

Abstract singular terms and thin reference

The prevailing approach to the problem of the ontological status of mathematical entities such as numbers and sets is to ask in what sense it is legitimate to ascribe a reference to abstract singular terms; those expressions of our language which, taken at face value, denote abstract objects. On the basis of this approach, neo-Fregean Abstractionists such as Hale and Wright have argued that abstract singular terms may be taken to effect genuine reference towards objects, whereas nominalists such as Field have asserted that these apparent ontological commitments should not be taken at face value. In this article I argue for an intermediate position which upholds the legitimacy of ascribing a reference to abstract singular terms in an attenuated sense relative to the more robust ascription of reference applicable to names denoting concrete entities. In so doing I seek to clear up some confusions regarding the ramifications of such a thin notion of reference for ontological claims about mathematical objects.

Dummett and the problem of abstract objects

Dummett’s views on the problem of abstract objects shifted significantly over the course of his philosophical career, and an examination of his views on this issue not only provides insight into his development; it also serves to elucidate his contribution and significance as a philosopher of language and mathematics. In the paper I attempt to demonstrate the way in which Dummett’s treatment of the problem of abstract objects is instructive for a consideration of his philosophy as a whole. Section 1 sketches the development of Dummett’s views on the problem from his attack on nominalism in the mid-1950’s to his advocacy of a tolerant reductionist position in Frege: Philosophy of Mathematics. Section 2 then examines the significance of Dummett’s views on abstract objects for his philosophical project more generally.

Demo abstract: wind measurements for water quality studies in urban reservoirs

Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

Abstract & experimental animation – A century of innovation

This compact history of 100 years of abstract and experimental animation in Australia spans the earliest cameraless classics through to modern examples of what’s happening in the vibrant VJ scene. Australian animators and experimental filmmakers have been as innovative as anybody when it comes to creating abstract animation. This history is more elongated than many people believe, in part due to the inherent lack of commercial or popular screening opportunities for much of this sort of filmmaking. This program showcases a rich collection of films from this most elemental of all animation genres. It will be introduced by a small panel of filmmakers who will contextualise this history and explain its future.

Generating domain-specific visual language tools from abstract visual specifications

Domain-specific visual languages support high-level modeling for a wide range of application domains. However, building tools to support such languages is very challenging. We describe a set of key conceptual requirements for such tools and our approach to addressing these requirements, a set of visual language-based metatools. These support definition of metamodels, visual notations, views, modeling behaviors, design critics, and model transformations and provide a platform to realize target visual modeling tools. Extensions support collaborative work, human-centric tool interaction, and multiplatform deployment. We illustrate application of the metatoolset on tools developed with our approach. We describe tool developer and cognitive evaluations of our platform and our exemplar tools, and summarize key future research directions.

Husserl and the problem of abstract objects

One major difficulty confronting attempts to clarify the epistemological and ontological status of abstract objects is determining the sense, if any, in which such entities may be characterised as mind and language independent. Our contention is that the tolerant reductionist position of Michael Dummett can be strengthened by drawing on Husserl's mature account of the constitution of ideal objects and mathematical objectivity. According to the Husserlian position we advocate, abstract singular terms pick out weakly mind-independent sedimented meaning-contents. These meaning-contents serve as the 'thin' referents of abstract singular terms, but are ultimately founded in prior acts of meaning-constitution.

Cluster analysis and optimization in color-based clustering for image abstract

Cluster analysis has been identified as a core task in data mining. What constitutes a cluster, or a good clustering, may depend on the background of researchers and applications. This paper proposes two optimization criteria of abstract degree and fidelity in the field of image abstract. To satisfy the fidelity criteria, a novel clustering algorithm named Global Optimized Color-based DBSCAN Clustering (GOC-DBSCAN) is provided. Also, non-optimized local color information based version of GOC-DBSCAN, called HSV-DBSCAN, is given. Both of them are based on HSV color space. Clusters of GOC-DBSCAN are analyzed to find the factors that impact on the performance of both abstract degree and fidelity. Examples show generally the greater the abstract degree is, the less is the fidelity. It also shows GOC-DBSCAN outperforms HSV-DBSCAN when they are evaluated by the two optimization criteria.

TestMEReq : generating abstract tests for requirements validation

This paper introduces TestMEReq, an automated tool for early validation of requirements. TestMEReq supports requirements engineers (REs) in the validation of the correctness, completeness and consistency of elicited requirements with minimum effort and time through generated abstract tests components: test requirements and test cases, and a mock-up prototype of the user interface (UI). Abstract tests are derived from abstract models called Essential Use Cases (EUCs) and the Essential User Interface (EUI). Our evaluation results show that TestMEReq is useful in the requirements validation process: it reduces the effort and time spent to ensure good quality requirements.