Optimally increasing secure connectivity in multihop wireless ad hoc networks

We consider the problem of how to maximize secure connectivity of multi-hop wireless ad hoc networks after deployment. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by secret keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one is based of increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We show that both problems are NP-hard and MAX-SNP (i.e., it is NP-hard to approximate them within a factor of 1 + e for e > 0 ) with a reduction to MAX3SAT problem. Thus, we design and implement a fully distributed algorithm for authenticated key establishment in wireless sensor networks where each sensor knows only its one- hop neighborhood. Our witness based approaches find witnesses in multi-hop neighborhood to authenticate the key establishment between two sensor nodes which do not share a key and which are not connected through a secure path.

Design and analysis of key management schemes for distributed wireless sensor networks

Secure communications in distributed Wireless Sensor Networks (WSN) operating under adversarial conditions necessitate efficient key management schemes. In the absence of a priori knowledge of post-deployment network configuration and due to limited resources at sensor nodes, key management schemes cannot be based on post-deployment computations. Instead, a list of keys, called a key-chain, is distributed to each sensor node before the deployment. For secure communication, either two nodes should have a key in common in their key-chains, or they should establish a key through a secure-path on which every link is secured with a key. We first provide a comparative survey of well known key management solutions for WSN. Probabilistic, deterministic and hybrid key management solutions are presented, and they are compared based on their security properties and re-source usage. We provide a taxonomy of solutions, and identify trade-offs in them to conclude that there is no one size-fits-all solution. Second, we design and analyze deterministic and hybrid techniques to distribute pair-wise keys to sensor nodes before the deployment. We present novel deterministic and hybrid approaches based on combinatorial design theory and graph theory for deciding how many and which keys to assign to each key-chain before the sensor network deployment. Performance and security of the proposed schemes are studied both analytically and computationally. Third, we address the key establishment problem in WSN which requires key agreement algorithms without authentication are executed over a secure-path. The length of the secure-path impacts the power consumption and the initialization delay for a WSN before it becomes operational. We formulate the key establishment problem as a constrained bi-objective optimization problem, break it into two sub-problems, and show that they are both NP-Hard and MAX-SNP-Hard. Having established inapproximability results, we focus on addressing the authentication problem that prevents key agreement algorithms to be used directly over a wireless link. We present a fully distributed algorithm where each pair of nodes can establish a key with authentication by using their neighbors as the witnesses.

Challenges facing carbon dioxide labelling of construction materials

In the absence of a benchmarking mechanism specifically designed for local requirements and characteristics, a carbon dioxide footprint assessment and labelling scheme for construction materials is urgently needed to promote carbon dioxide reduction in the construction industry. This paper reports on a recent interview survey of 18 senior industry practitioners in Hong Kong to elicit their knowledge and opinions concerning the potential of such a carbon dioxide labelling scheme. The results of this research indicate the following. A well-designed carbon dioxide label could stimulate demand for low carbon dioxide construction materials. The assessment of carbon dioxide emissions should be extended to different stages of material lifecycles. The benchmarks for low carbon dioxide construction materials should be based on international standards but without sacrificing local integrity. Administration and monitoring of the carbon dioxide labelling scheme could be entrusted to an impartial and independent certification body. The implementation of any carbon dioxide labelling schemes should be on a voluntary basis. Cost, functionality, quality and durability are unlikely to be replaced by environmental considerations in the absence of any compelling incentives or penalties. There are difficulties in developing and operating a suitable scheme, particularly in view of the large data demands involved, reluctance in using low carbon dioxide materials and limited environmental awareness.

A self-assessment tool for knowledge management implementation in the construction industry

Knowledge management (KM) provides a structured process to establish the link between knowledgebased assets within an organisation and its desired business objectives. Although KM issues are becoming increasingly important to the construction industry, there is currently no measurement tool for assessing the implementation of KM programmes. This paper reports on the development of such a tool which can be used as both a means of self-assessment and also for benchmarking purposes. Important practices needed for successful KM implementation were identified from the literature and via a self-administered survey targeting large and medium construction organisations in Hong Kong. Survey findings demonstrate the potential of the proposed self-assessment tool to measure the individual’s perception of the relative importance of KM antecedents and practices, also providing early insight of KM implementation by highlighting the negative gaps between what “is” and “should be” happening, thus identifying areas that need re alignment of KM strategies and tactics. The paper also suggests this tool could be further developed to help organisations to formulate and modify their KM programmes according to their own specific internal business environment, and the nature of their projects.

Visualising security incidents through event aggregation

Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

Complexity of increasing the secure connectivity in wireless ad hoc networks

We consider the problem of maximizing the secure connectivity in wireless ad hoc networks, and analyze complexity of the post-deployment key establishment process constrained by physical layer properties such as connectivity, energy consumption and interference. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by shared keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one extends the first problem by increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We prove that both problems are NP-hard and MAX-SNP with a reduction to MAX3SAT problem.

The place of higher education institutions in assessing student engagement, success and retention : a maturity model to guide practice

The perennial issues of student engagement, success and retention in higher education continue to attract attention as the salience of teaching and learning funding and performance measures has increased. This paper addresses the question of the responsibility or place of higher education institutions (HEIs) for initiating, planning, managing and evaluating their student engagement, success and retention programs and strategies. An evaluation of the current situation indicates the need for a sophisticated approach to assessing the ability of HEIs to proactively design programs and practices that enhance student engagement. An approach—the Student Engagement Success and Retention Maturity Model (SESR-MM)—is proposed and its development, current status, and relationship with and possible use in benchmarking are discussed.

Every One, Every Day

Creative Statement: “There are those who see Planet Earth as a gigantic living being, one that feeds and nurtures humanity and myriad other species – an entity that must be cared for. Then there are those who see it as a rock full of riches to be pilfered heedlessly in a short-term quest for over-abundance. This ‘cradle to grave’ mentality, it would seem, is taking its toll (unless you’re a virulent disbeliever in climate change). Why not, ask artists Priscilla Bracks and Gavin Sade, take a different approach? To this end they have set out on a near impossible task; to visualise the staggering quantity of carbon produced by Australia every year. Their eerie, glowing plastic cube resembles something straight out of Dr Who or The X Files. And, like the best science fiction, it has technical realities at its heart. Every One, Every Day tangibly illustrates our greenhouse gas output – its 27m3 volume is approximately the amount of green-house gas emitted per capita, daily. Every One, Every Dayis lit by an array of LED’s displaying light patterns representing energy use generated by data from the Australian Energy Market. Every One, Every Day was formed from recycled, polyethylene – used milk bottles – ‘lent’ to the artists by a Visy recycling facility. At the end of the Vivid Festival this plastic will be returned to Visy, where it will re-enter the stream of ‘technical nutrients.’ Could we make another world? One that emulates the continuing cycles of nature? One that uses our ‘technical nutrients’ such as plastic and steel in continual cycles, just like a deciduous tree dropping leaves to compost itself and keep it’s roots warm and moist?” (Ashleigh Crawford. Melbourne – April, 2013) Artistic Research Statement: The research focus of this work is on exploring how to represent complex statistics and data at a human scale, and how produce a work where a large percentage of the materials could be recycled. The surface of Every One, Every Day is clad in tiles made from polyethylene, from primarily recycled milk bottles, ‘lent’ to the artists by the Visy recycling facility in Sydney. The tiles will be returned to Visy for recycling. As such the work can be viewed as an intervention in the industrial ecology of polyethylene, and in the process demonstrates how to sustain cycles of technical materials – by taking the output of a recycling facility back to a manufacturer to produce usable materials. In terms of data visualisation, Every One, Every Day takes the form of a cube with a volume of 27 cubic meters. The annual per capita emissions figures for Australia are cited as ranging between 18 to 25 tons. Assuming the lower figure, 18tons per capital annually, the 27 cubic meters represents approximately one day per capita of CO2 emissions – where CO2 is a gas at 15C and 1 atmosphere of pressure. The work also explores real time data visualisation by using an array of 600 controllable LEDs inside the cube. Illumination patterns are derived from a real time data from the Australian Energy Market, using the dispatch interval price and demand graph for New South Wales. The two variables of demand and price are mapped to properties of the illumination - hue, brightness, movement, frequency etc. The research underpinning the project spanned industrial ecology to data visualization and public art practices. The result is that Every One, Every Day is one of the first public artworks that successfully bring together materials, physical form, and real time data representation in a unified whole.

Hydrogen bonding in two ammonium salts of 5-sulfosalicylic acid : ammonium 3-carboxy-4-hydroxybenzenesulfonate monohydrate and triammonium 3-carboxy-4-hydroxybenzenesulfonate 3-carboxylato-4-hydroxybenzenesulfonate

The structures of two ammonium salts of 3-carboxy-4-hydroxybenzenesulfonic acid (5-sulfosalicylic acid, 5-SSA) have been determined at 200 K. In the 1:1 hydrated salt, ammonium 3-carboxy-4-hydroxybenzenesulfonate monohydrate, NH4+·C7H5O6S-·H2O, (I), the 5-SSA- monoanions give two types of head-to-tail laterally linked cyclic hydrogen-bonding associations, both with graph-set R44(20). The first involves both carboxylic acid O-HOwater and water O-HOsulfonate hydrogen bonds at one end, and ammonium N-HOsulfonate and N-HOcarboxy hydrogen bonds at the other. The second association is centrosymmetric, with end linkages through water O-HOsulfonate hydrogen bonds. These conjoined units form stacks down c and are extended into a three-dimensional framework structure through N-HO and water O-HO hydrogen bonds to sulfonate O-atom acceptors. Anhydrous triammonium 3-carboxy-4-hydroxybenzenesulfonate 3-carboxylato-4-hydroxybenzenesulfonate, 3NH4+·C7H4O6S2-·C7H5O6S-, (II), is unusual, having both dianionic 5-SSA2- and monoanionic 5-SSA- species. These are linked by a carboxylic acid O-HO hydrogen bond and, together with the three ammonium cations (two on general sites and the third comprising two independent half-cations lying on crystallographic twofold rotation axes), give a pseudo-centrosymmetric asymmetric unit. Cation-anion hydrogen bonding within this layered unit involves a cyclic R33(8) association which, together with extensive peripheral N-HO hydrogen bonding involving both sulfonate and carboxy/carboxylate acceptors, gives a three-dimensional framework structure. This work further demonstrates the utility of the 5-SSA- monoanion for the generation of stable hydrogen-bonded crystalline materials, and provides the structure of a dianionic 5-SSA2- species of which there are only a few examples in the crystallographic literature.

Proton-transfer compounds with 4-amino-N-(4,6-dimethylpyrimidin-2-yl)benzenesulfonamide (sulfamethazine): the structures and hydrogen-bonding in the salts with 5-nitrosalicylic acid and picric acid

The structures of the anhydrous proton-transfer compounds of the sulfa drug sulfamethazine with 5-nitrosalicylic acid and picric acid, namely 2-(4-aminobenzenesulfonamido)-4,6-dimethylpyrimidinium 2-hydroxy-5-nitrobenzoate, C12H15N4O2S(+)·C7H4NO4(-), (I), and 2-(4-aminobenzenesulfonamido)-4,6-dimethylpyrimidinium 2,4,6-trinitrophenolate, C12H15N4O2S(+)·C6H2N3O7(-), (II), respectively, have been determined. In the asymmetric unit of (I), there are two independent but conformationally similar cation-anion heterodimer pairs which are formed through duplex intermolecular N(+)-H...Ocarboxylate and N-H...Ocarboxylate hydrogen-bond pairs, giving a cyclic motif [graph set R2(2)(8)]. These heterodimers form separate and different non-associated substructures through aniline N-H...O hydrogen bonds, one one-dimensional, involving carboxylate O-atom acceptors, the other two-dimensional, involving both carboxylate and hydroxy O-atom acceptors. The overall two-dimensional structure is stabilized by π-π interactions between the pyrimidinium ring and the 5-nitrosalicylate ring in both heterodimers [minimum ring-centroid separation = 3.4580 (8) Å]. For picrate (II), the cation-anion interaction involves a slightly asymmetric chelating N-H...O R2(1)(6) hydrogen-bonding association with the phenolate O atom, together with peripheral conjoint R1(2)(6) interactions between the same N-H groups and O atoms of the ortho-related nitro groups. An inter-unit amine N-H...Osulfone hydrogen bond gives one-dimensional chains which extend along a and inter-associate through π-π interactions between the pyrimidinium rings [centroid-centroid separation = 3.4752 (9) Å]. The two structures reported here now bring to a total of four the crystallographically characterized examples of proton-transfer salts of sulfamethazine with strong organic acids.

Sample size considerations and augmentation of computer experiments

Computer Experiments, consisting of a number of runs of a computer model with different inputs, are now common-place in scientific research. Using a simple fire model for illustration some guidelines are given for the size of a computer experiment. A graph is provided relating the error of prediction to the sample size which should be of use when designing computer experiments. Methods for augmenting computer experiments with extra runs are also described and illustrated. The simplest method involves adding one point at a time choosing that point with the maximum prediction variance. Another method that appears to work well is to choose points from a candidate set with maximum determinant of the variance covariance matrix of predictions.

Using a Bayesian network to model colonisation with Vancomycin Resistant Enterococcus (VRE)

Objective: Effective management of multi-resistant organisms is an important issue for hospitals both in Australia and overseas. This study investigates the utility of using Bayesian Network (BN) analysis to examine relationships between risk factors and colonization with Vancomycin Resistant Enterococcus (VRE). Design: Bayesian Network Analysis was performed using infection control data collected over a period of 36 months (2008-2010). Setting: Princess Alexandra Hospital (PAH), Brisbane. Outcome of interest: Number of new VRE Isolates Methods: A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). BN enables multiple interacting agents to be studied simultaneously. The initial BN model was constructed based on the infectious disease physician‟s expert knowledge and current literature. Continuous variables were dichotomised by using third quartile values of year 2008 data. BN was used to examine the probabilistic relationships between VRE isolates and risk factors; and to establish which factors were associated with an increased probability of a high number of VRE isolates. Software: Netica (version 4.16). Results: Preliminary analysis revealed that VRE transmission and VRE prevalence were the most influential factors in predicting a high number of VRE isolates. Interestingly, several factors (hand hygiene and cleaning) known through literature to be associated with VRE prevalence, did not appear to be as influential as expected in this BN model. Conclusions: This preliminary work has shown that Bayesian Network Analysis is a useful tool in examining clinical infection prevention issues, where there is often a web of factors that influence outcomes. This BN model can be restructured easily enabling various combinations of agents to be studied.

Private hospital emergency departments in Australia : challenges and opportunities

BACKGROUND: Public hospital EDs in Australia have become increasingly congested because of increasing demand and access block. Six per cent of ED patients attend private hospital EDs whereas 45% of the population hold private health insurance. OBJECTIVES: This study describes the patients attending a small selection of four private hospital EDs in Queensland and Victoria, and tests the feasibility of a private ED database. METHODS: De-identified routinely collected patient data were provided by the four participating private hospital and amalgamated into a single data set. RESULT: The mean age of private ED patients was 52 years. Males outnumbered females in all age groups except > 80 years. Attendance was higher on weekends and Mondays, and between 08.00 and 20.00 h. There were 6.6% of the patients triaged as categories 1 and 2, and 60% were categories 4 or 5. There were 36.4% that required hospital admission. Also, 96% of the patients had some kind of insurance. Furthermore, 72% were self-referred and 12% were referred by private medical practitioners. Approximately 25% arrived by ambulance. There were 69% that completed their ED treatment within 4 h. CONCLUSION: This study is the first public description of patients attending private EDs in Australia. Private EDs have a significant role to play in acute medical care and in providing access to private hospitals which could alleviate pressure on public EDs. This study demonstrates the need for consolidated data based on a consistent data set and data dictionary to enable system-wide analysis, benchmarking and evaluation

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.