A hierarchical security assessment model for object-oriented programs

We present a hierarchical model for assessing an object-oriented program's security. Security is quantified using structural properties of the program code to identify the ways in which `classified' data values may be transferred between objects. The model begins with a set of low-level security metrics based on traditional design characteristics of object-oriented classes, such as data encapsulation, cohesion and coupling. These metrics are then used to characterise higher-level properties concerning the overall readability and writability of classified data throughout the program. In turn, these metrics are then mapped to well-known security design principles such as `assigning the least privilege' and `reducing the size of the attack surface'. Finally, the entire program's security is summarised as a single security index value. These metrics allow different versions of the same program, or different programs intended to perform the same task, to be compared for their relative security at a number of different abstraction levels. The model is validated via an experiment involving five open source Java programs, using a static analysis tool we have developed to automatically extract the security metrics from compiled Java bytecode.

Do programs to improve business performance in small and medium manufacturing enterprise improve opportunity recognition?

Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies which participated in an holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Feature-domain super-resolution for IRIS recognition

Uncooperative iris identification systems at a distance suffer from poor resolution of the captured iris images, which significantly degrades iris recognition performance. Superresolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, all existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values. This paper considers transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. This is the first paper to investigate the possibility of feature domain super-resolution for iris recognition, and experiments confirm the validity of the proposed approach.

Analysis of Object-Specific Authorization Protocol (OSAP) using coloured petri nets - Version 1.0

Analyzing security protocols is an ongoing research in the last years. Different types of tools are developed to make the analysis process more precise, fast and easy. These tools consider security protocols as black boxes that can not easily be composed. It is difficult or impossible to do a low-level analysis or combine different tools with each other using these tools. This research uses Coloured Petri Nets (CPN) to analyze OSAP trusted computing protocol. The OSAP protocol is modeled in different levels and it is analyzed using state space method. The produced model can be combined with other trusted computing protocols in future works.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

The sun gives without ever receiving

YEAR: 2010 ROLE: Artist FORMAT: Miniature 3D Sculpture produced in resin using 3D printing technologies. WITH: International Touring Show ‘Inside Out’ WHAT: A miniature sculpture that contributes towards my ongoing explorations into how our collective ability to sustain (the future) is as much a cultural problematic as it is an economic or technological one. OVERVIEW: The curatorial brief was for each curated artist was to design a piece in CAD suitable for 3D resin printing - The object should be entirely generated through 3D visualisation and modelling tools and should be machined and shipped within the dimensions of 6cm x 6cm x 6cm. My design for this brief was influenced by recent research I had conducted in Mildura in the Sunraysia irrigated region of NW Victoria. Each name set within the work is an Australian soldier/settler – who, on returning from the ‘Great War’ was duly awarded a ‘block’ in Australia’s new inland irrigated settlements - with the explicit task of clearing it to plant and reap. Through their concerted and well-intentioned efforts, these workers began to profoundly re-shape Australia’s marginal country - inadvertently presaging the bleak future faced today by many of Australia’s inland lands and river systems. Furthermore, through that time's predominant colonial conception of ‘terra nullius’ (this land is unoccupied and therefore free to be claimed) they each played a small but formative part in building the profound cultural divide between land and peoples that still haunts Australia today. THE EXHIBITION: Inside Out is a compelling international touring exhibition featuring forty-six miniature sculptures produced in resin using 3D printing technologies. Developments in virtual computer visualisation and integrated digital technologies are giving contemporary makers new insight and opportunities to create objects and forms which were previously impossible to produce or difficult to envisage. The exhibition is the result of collaboration between the Art Technology Coalition, the University of Technology Sydney and RMIT University in Australia along with De Montfort University, Manchester Metropolitan University and Dartington College of Arts at University College Falmouth in the United Kingdom.

Use of 3D visualisation to enhance groundwater stable isotope data and its interpretation, Lockyer Valley, southeast Queensland

The use of stable isotope ratios δ18O and δ2H are well established in assessment of groundwater systems and their hydrology. The conventional approach is based on x/y plots and relation to various MWL’s, and plots of either ratio against parameters such as Clor EC. An extension of interpretation is the use of 2D maps and contour plots, and 2D hydrogeological vertical sections. An enhancement of presentation and interpretation is the production of “isoscapes”, usually as 2.5D surface projections. We have applied groundwater isotopic data to a 3D visualisation, using the alluvial aquifer system of the Lockyer Valley. The 3D framework is produced in GVS (Groundwater Visualisation System). This format enables enhanced presentation by displaying the spatial relationships and allowing interpolation between “data points” i.e. borehole screened zones where groundwater enters. The relative variations in the δ18O and δ2H values are similar in these ambient temperature systems. However, δ2H better reflects hydrological processes, whereas δ18O also reflects aquifer/groundwater exchange reactions. The 3D model has the advantage that it displays borehole relations to spatial features, enabling isotopic ratios and their values to be associated with, for example, bedrock groundwater mixing, interaction between aquifers, relation to stream recharge, and to near-surface and return irrigation water evaporation. Some specific features are also shown, such as zones of leakage of deeper groundwater (in this case with a GAB signature). Variations in source of recharging water at a catchment scale can be displayed. Interpolation between bores is not always possible depending on numbers and spacing, and by elongate configuration of the alluvium. In these cases, the visualisation uses discs around the screens that can be manually expanded to test extent or intersections. Separate displays are used for each of δ18O and δ2H and colour coding for isotope values.

Assessment of pre- and post-flood groundwater recharge via 3D visualisation, Lockyer Valley, southeast Queensland

The Lockyer Valley in southeast Queensland supports important and intensive irrigation which is dependant on the quality and availability of groundwater. Prolonged drought conditions from ~1997 resulted in a depletion of the alluvial aquifers, and concern for the long-term sustainability of this resource. By 2008, many areas of the valley were at < 20% of storage. Some relief occurred with rain events in early 2009, then in December 2010 - January 2011, most of southeast Queensland experienced unprecedented flooding. These storm-based events have caused a shift in research focus from investigations of drought conditions and mitigation to flood response analysis. For the alluvial aquifer system of the valley, a preliminary assessment of groundwater observation bore data, prior to and during the flood, indicates that there is a spatially variable aquifer response. While water levels in some bores screened in unconfined shallow aquifers have recovered by more than 10 m within a short period of time (months), others show only a small or moderate response. Measurements of pre- and post-flood groundwater levels and high-resolution time-series records from data loggers are considered within the framework of a 3D geological model of the Lockyer Valley using Groundwater Visualisation System(GVS). Groundwater level fluctuations covering both drought and flood periods are used to estimate groundwater recharge using the water table fluctuation method (WTF), supplemented by estimates derived using chloride mass balance. The presentation of hydraulic and recharge information in a 3D format has considerable advantages over the traditional 2D presentation of data. The 3D approach allows the distillation of multiple types of information(topography, geological, hydraulic and spatial) into one representation that provides valuable insights into the major controls of groundwater flow and recharge. The influence of aquifer lithology on the spatial variability of groundwater recharge is also demonstrated.