Combining image regions and human activity for indirect object recognition in indoor wide-angle views

Traditional methods of object recognition are reliant on shape and so are very difficult to apply in cluttered, wideangle and low-detail views such as surveillance scenes. To address this, a method of indirect object recognition is proposed, where human activity is used to infer both the location and identity of objects. No shape analysis is necessary. The concept is dubbed 'interaction signatures', since the premise is that a human will interact with objects in ways characteristic of the function of that object - for example, a person sits in a chair and drinks from a cup. The human-centred approach means that recognition is possible in low-detail views and is largely invariant to the shape of objects within the same functional class. This paper implements a Bayesian network for classifying region patches with object labels, building upon our previous work in automatically segmenting and recognising a human's interactions with the objects. Experiments show that interaction signatures can successfully find and label objects in low-detail views and are equally effective at recognising test objects that differ markedly in appearance from the training objects.

Blairgowrie: the meaning of place

Defining the meaning of a specific place is difficult. Blairgowrie is a peaceful and naturally protected beach haven on the Nepean Peninsula on the tip of the Mornington Peninsula, in Victoria, Australia. When a major development is perceived as threatening the quality of place, it is perhaps already too late to begin to name its characteristics or particular attributes. The evocative and poetic qualities of Blairgowrie do not reveal themselves immediately. Only over a period of time, and by visiting at various times of the day in all seasons, can one begin to fathom its moods, its soul, its many colours; and to touch its memories. Here sea and sky can meet, or divide, totally unobstructed, depending on climatic conditions, seasonal weather patterns and diurnal changes. It is still possible to get a sense of scale and wide-angle limitless vision. When a Safe Boat Harbour was proposed for Blairgowrie, residents came out in force to voice their objections or their support. A tribunal hearing was put in place. In light of the dismissal of qualitative data, of reflective experiential material, of community opinion, of values of the 'other' in planning tribunal hearings, this paper attempts to build a case for putting into words 'the meaning of place'. The Safe Boat Harbour proposal was the catalyst for this exploration of 'meaning of place', and is not itself primarily the subject of this paper. This very personal paper begins to examine the meaning of this place. Through images, perceptions, and representations; through time; history, topography; flora and fauna: it attempts to find a way of coming to terms with this extraordinary land/seascape. In the long term this project aims to produce relevant, authoritative, and defensible research that provides the context and rationale for the selection and assessment of places of outstanding heritage significance. Further, it will provide a case study in support of new planning regulations for 'place' zones (Mant, 2001) rather than the generic land use zones, which are current in Victoria.

Effects of MWNT nanofillers on structures and properties of PVA electrospun nanofibres

In this study, we have electrospun poly(vinyl alcohol)(PVA) nanofibres and PVA composite nanofibres containing multi-wall carbon nanotubes (MWNTs) (4.5 wt%), and examined the effect of the carbon nanotubes and the PVA morphology change induced by post-spinning treatments on the tensile properties, surface hydrophilicity and thermal stability of the nanofibres. Through differential scanning calorimetry (DSC) and wide-angle x-ray diffraction (WAXD) characterizations, we have observed that the presence of the carbon nanotubes nucleated crystallization of PVA in the MWNTs/PVA composite nanofibres, and hence considerably improved the fibre tensile strength. Also, the presence of carbon nanotubes in PVA reduced the fibre diameter and the surface hydrophilicity of the nanofibre mat. The MWNTs/PVA composite nanofibres and the neat PVA nanofibres responded differently to post-spinning treatments, such as soaking in methanol and crosslinking with glutaric dialdehyde, with the purpose of increasing PVA crystallinity and establishing a crosslinked PVA network, respectively. The presence of carbon nanotubes reduced the PVA crystallization rate during the methanol treatment, but prevented the decrease of crystallinity induced by the crosslinking reaction. In comparison with the crosslinking reaction, the methanol treatment resulted in better improvement in the fibre tensile strength and less reduction in the tensile strain. In addition, the presence of carbon nanotubes reduced the onset decomposition temperature of the composite nanofibres, but stabilized the thermal degradation for the post-spinning treated nanofibres. The MWNTs/PVA composite nanofibres treated by both methanol and crosslinking reaction gave the largest improvement in the fibre tensile strength, water contact angle and thermal stability.

The effect of solvent uptake on the relaxation behaviour, morphology and mechanical properties of a poly(ether ether ketone)/poly(etherimide) blend

The effects of solvent uptake on the relaxation behaviour, morphology and mechanical properties of poly(ether ether ketone) (PEEK), poly(etherimide) (PEI) and a 50/50 PEEK/PEI blend have been investigated. Amorphous films were immersed in acetone at 25°C, 35°C and 45°C until equilibrium uptake was achieved. The films were then examined by wide angle X-ray scattering (WAXS), differential scanning calorimetry (d.s.c.), dynamic mechanical relaxation spectroscopy and mechanical testing. WAXS and d.s.c. revealed that the degree of solvent induced crystallinity in PEEK is constant with immersion temperature, whereas the degree of induced crystallinity in the 50/50 blend is strongly temperature dependent. The dynamic mechanical studies confirmed that a significant decrease in glass transition temperature results from the plasticizing effect of the solvent and that solvent and thermally crystallized samples have different relaxation characteristics. Mechanical property tests showed that the yield stress and tensile strength of the blend are dominated by PEEK and the degree of crystallinity, while the modulus is more sensitive to the extent of plasticization.

Resolution considerations in spatially variant sensors

Log polar transformations for space variant systems have been proposed and used in active vision research. The idea is to generate an image with a varying resolution over a wide angle field of view. The fovea is of high resolution and the periphery is of exponentially reduced resolution. The justifications for such a sensor are: (i) it provides high resolution and a wide viewing angle, (ii) feature invariance in the fovea simplifies foveation, and (iii) it allows multiresolution analysis. The receptor density of the human retina is very high, i.e. of the order of 106 receptors at the fovea. The question is, what resolution should space variant active vision systems have? Real visual sensors have been implemented but is the resolution produced high enough? This paper investigates the resolution requirements of a space variant sensor by simulation for a tracking system using raytracing

Tracking in a space variant active vision system

Without the ability to foveate on and maintain foveation, active vision for applications such as surveillance, object recognition and object tracking are difficult to build. Although foveation in cartesian coordinates is being actively pursued by many, multi-resolution high accuracy foveation in log polar space has not been given much attention. This paper addresses the use of foveation to track a single object as well as multiple objects for a simulated space variant active vision system. Complex logarithmic mapping is chosen firstly because it provides high resolution and wide angle viewing. Secondly, the spatially variant structure of log polar space leads to an object increasing in size as it moves towards the fovea. This is important as we know which object is closer to the fovea at any instant in time.

Characterization of the phase behaviour of a novel polymerizable lyotropic ionic liquid crystal

The development of new polymerizable lyotropic liquid crystals (LLCs) utilizing charged amphiphilic molecules such as those based on long chain imidazolium compounds, is a relatively new design direction for producing robust membranes with controllable nano-structures. Here we have developed a novel polymerizable ionic liquid based LLC, 1-hexadecyl-3-methylimidazolium acrylate (C16mimAcr), where the acrylate anion acts as the polymerizable moiety. The phase behaviour of the C16mimAcr upon the addition of water was characterized using small and wide angle X-ray scatterings, differential scanning calorimetry and polarized optical microscopy. We compare the phase behaviour of this new polymerizable LLC to that of the well known LLC chloride analogue, 1-hexadecyl-3-methylimidazolium chloride (C16mimCl). We find that the C16mimAcr system has a more complex phase behaviour compared to the C16mimCl system. Additional lyotropic liquid crystalline mesophases such as hexagonal phase (H1) and discontinuous cubic phase (I1) are observed at 20 °C for the acrylate system at 50 and 65 wt% water respectively. The appearance of the hexagonal phase (H1) and discontinuous cubic phase (I1) for the acrylate system is likely due to the strong hydrating nature of the acrylate anion, which increases the head group area. The formation of these additional mesophases seen for the acrylate system, especially the hexagonal phase (H1), coupled with the polymerization functionality offers great potential in the design of advanced membrane materials with selective and anisotropic transport properties.

Influence of processing conditions on polymorphic behavior, crystallinity, and morphology of electrospun poly(VInylidene fluoride) nanofibers

The polymorphism and crystallinity of poly(vinylidene fluoride) (PVDF) membranes, made from electrospinning of the PVDF in pure N,N-dimethylformamide (DMF) and DMF/acetone mixture solutions are studied. Influence of the processing and solution parameters such as flow rate, applied voltage, solvent system, and mixture ratio, on nanofiber morphology, total crystallinity, and crystal phase content of the nanofibers are investigated using scanning electron microscopy, wide-angle X-ray scattering, differential scanning calorimetric, and Fourier transform infrared spectroscopy. The results show that solutions of 20% w/w PVDF in two solvent systems of DMF and DMF/acetone (with volume ratios of 3/1 and 1/1) are electrospinnable; however, using DMF/acetone volume ratio of 1/3 led to blockage of the needle and spinning process was stopped. Very high fraction of β-phase (∼79%-85%) was obtained for investigated nanofiber, while degree of crystallinity increased to 59% which is quite high due to the strong influence of electrospinning on ordering the microstructure. Interestingly, ultrafine fibers with the diameter of 12 and 15 nm were obtained in this work. Uniform and bead free nanofiber was formed when a certain amount of acetone was added in to the electrospinning solution.

Machine learning for user modeling

At first blush, user modeling appears to be a prime candidate for straightforward application of standard machine learning techniques. Observations of the user's behavior can provide training examples that a machine learning system can use to form a model designed to predict future actions. However, user modeling poses a number of challenges for machine learning that have hindered its application in user modeling, including: the need for large data sets; the need for labeled data; concept drift; and computational complexity. This paper examines each of these issues and reviews approaches to resolving them.

Lifecycle environmental impact and cost analyses of steel bridge piers with seismic risk

Lifecycle approaches have found their wide applications in analyzing, evaluating and assessing technologies and management methods in the infrastructure systems. While environmental problems such as global warming have become a serious issue in the world, researchers and practicing engineers in civil engineering have to pay attention to environmental impacts as well as function, safety, cost and aesthetics in the
whole lifecycle of civil infrastructures. In addition to the normal lifecycle activities accompanied with operation and aging, the effects of natural hazards such as earthquakes with a low occurrence probability but a high
hazard loss require a full consideration in determining both lifecycle cost and lifecycle environmental impact. In this research, an approach is proposed to predetermine the lifecycle environmental impact and costs of bridges from their construction and maintenance as well as the losses and recovery after natural hazards. Based on this research, it becomes possible to quantitatively outline the roles of bridge construction, maintenance and earthquake in both environmental impact and cost in the whole lifetime of a bridge, especially their constituent parts from seismic losses and recoveries.

Microstructural modeling of dynamic recrystallization using irregular cellular automata

Cellular automaton (CA) was used to simulate dynamic recrystallization (DRX) during thermomechanical deformation. Initial grain size, initial grain orientation and dislocation density were used as input data to the CA model. Flow curve, dislocation density, final grain size and orientation, and DRX volume fraction were the output data which were compared with experimental data to validate the model. The model proposed in this work considered the thermomechanical parameters (e.g., temperature and strain rate) and their role on the nucleation and growth kinetics during DRX. It was shown that the CA model can predict the final microstructure and flow curve to a high degree of accuracy and was able to successfully simulate the volume fraction of DRX as a function of strain for a wide range of deformation conditions.

Modeling intelligent agents for web-based information gathering

The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.

Modeling of light propagation through biological tissues : a novel approach

An efficient numerical technique for modeling biological tissues using the radiative transfer equation is presented. Time dependence of the transient radiative transfer equation is approximated using Laguerre expansion. Azimuthal angle is discretized using the discrete ordinates method and the resulting set of ordinary differential equations is solved using the Runge-Kutta-Felhberg method.

Software reliability growth models based on local polynomial modeling with kernel smoothing

Software reliability growth models (SRGMs) are extensively employed in software engineering to assess the reliability of software before their release for operational use. These models are usually parametric functions obtained by statistically fitting parametric curves, using Maximum Likelihood estimation or Least–squared method, to the plots of the cumulative number of failures observed N(t) against a period of systematic testing time t. Since the 1970s, a very large number of SRGMs have been proposed in the reliability and software engineering literature and these are often very complex, reflecting the involved testing regime that often took place during the software development process. In this paper we extend some of our previous work by adopting a nonparametric approach to SRGM modeling based on local polynomial modeling with kernel smoothing. These models require very few assumptions, thereby facilitating the estimation process and also rendering them more relevant under a wide variety of situations. Finally, we provide numerical examples where these models will be evaluated and compared.

Modeling of shear ductile fracture considering a changeable cut-off value for stress triaxiality

 A macroscopic ductile fracture criterion is proposed based on micro-mechanism analysis of nucleation, growth and shear coalescence of voids from experimental observation of fracture surfaces. The proposed ductile fracture model endows a changeable cut-off value for the stress triaxiality to represent effect of micro-structures, the Lode parameter, temperature, and strain rate on ductility of metals. The proposed model is used to construct fracture loci of AA 2024- T351. The constructed fracture loci are compared with experimental data covering wide stress triaxiality ranging between –0.5 and 1.0. The comparison suggests that the proposed model can provide a satisfactory prediction of ductile fracture for metals from compressive upsetting tests to plane strain tension with slanted fracture surfaces. Moreover, it is expected that the proposed model reasonably describes ductile fracture behavior in high velocity perforation simulation since a reasonable cut-off value for the stress triaxiality is coupled with the proposed ductile fracture criterion.