On secure multi-party computation in black-box groups

We study the natural problem of secure n-party computation (in the passive, computationally unbounded attack model) of the n-product function f G (x 1,...,x n ) = x 1 ·x 2 ⋯ x n in an arbitrary finite group (G,·), where the input of party P i is x i  ∈ G for i = 1,...,n. For flexibility, we are interested in protocols for f G which require only black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our results are as follows. First, on the negative side, we show that if (G,·) is non-abelian and n ≥ 4, then no ⌈n/2⌉-private protocol for computing f G exists. Second, on the positive side, we initiate an approach for construction of black-box protocols for f G based on k-of-k threshold secret sharing schemes, which are efficiently implementable over any black-box group G. We reduce the problem of constructing such protocols to a combinatorial colouring problem in planar graphs. We then give two constructions for such graph colourings. Our first colouring construction gives a protocol with optimal collusion resistance t < n/2, but has exponential communication complexity O(n*2t+1^2/t) group elements (this construction easily extends to general adversary structures). Our second probabilistic colouring construction gives a protocol with (close to optimal) collusion resistance t < n/μ for a graph-related constant μ ≤ 2.948, and has efficient communication complexity O(n*t^2) group elements. Furthermore, we believe that our results can be improved by further study of the associated combinatorial problems.

Structure-mediated thermal transport of monolayer graphene allotropes nanoribbons

We report the study of the thermal transport management of monolayer graphene allotrope nanoribbons (size ∼20 × 4 nm2) by the modulation of their structures via molecular dynamics simulations. The thermal conductivity of graphyne (GY)-like geometries is observed to decrease monotonously with increasing number of acetylenic linkages between adjacent hexagons. Strikingly, by incorporating those GY or GY-like structures, the thermal performance of graphene can be effectively engineered. The resulting hetero-junctions possess a sharp local temperature jump at the interface, and show a much lower effective thermal conductivity due to the enhanced phonon–phonon scattering. More importantly, by controlling the percentage, type and distribution pattern of the GY or GY-like structures, the hetero-junctions are found to exhibit tunable thermal transport properties (including the effective thermal conductivity, interfacial thermal resistance and rectification). This study provides a heuristic guideline to manipulate the thermal properties of 2D carbon networks, ideal for application in thermoelectric devices with strongly suppressed thermal conductivity.

Nonlinear Model Predictive Control for a multi-rotor with heavy slung load

In this paper a novel controller for stable and precise operation of multi-rotors with heavy slung loads is introduced. First, simplified equations of motions for the multi-rotor and slung load are derived. The model is then used to design a Nonlinear Model Predictive Controller (NMPC) that can manage the highly nonlinear dynamics whilst accounting for system constraints. The controller is shown to simultaneously track specified waypoints whilst actively damping large slung load oscillations. A Linear-quadratic regulator (LQR) controller is also derived, and control performance is compared in simulation. Results show the improved performance of the Nonlinear Model Predictive Control (NMPC) controller over a larger flight envelope, including aggressive maneuvers and large slung load displacements. Computational cost remains relatively small, amenable to practical implementation. Such systems for small Unmanned Aerial Vehicles (UAVs) may provide significant benefit to several applications in agriculture, law enforcement and construction.

BIM for sustainable whole-of-life transport infrastructure asset management

The US National Institute of Standards and Technology (NIST) showed that, in 2004, owners and operations managers bore two thirds of the total industry cost burden from inadequate interoperability in construction projects from inception to operation, amounting to USD10.6 billion. Building Information Modelling (BIM) and similar tools were identified by Engineers Australia in 2005 as potential instruments to significantly reduce this sum, which in Australia could amount to total industry-wide cost burden of AUD12 billion. Public sector road authorities in Australia have a key responsibility in driving initiatives to reduce greenhouse gas emissions from the construction and operations of transport infrastructure. However, as previous research has shown the Environmental Impact Assessment process, typically used for project approvals and permitting based on project designs available at the consent stage, lacks Key Performance Indicators (KPIs) that include long-term impact factors and transfer of information throughout the project life cycle. In the building construction industry, BIM is widely used to model sustainability KPIs such as energy consumption, and integrated with facility management systems. This paper proposes that a similar use of BIM in early design phases of transport infrastructure could provide: (i) productivity gains through improved interoperability and documentation; (ii) the opportunity to carry out detailed cost-benefit analyses leading to significant operational cost savings; (iii) coordinated planning of street and highway lighting with other energy and environmental considerations; iv) measurable KPIs that include long-term impact factors which are transferable throughout the project life cycle; and (v) the opportunity for integrating design documentation with sustainability whole-of-life targets.

Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

Towards a multi-element simulation of heavily over-consolidated bagasse using a material subroutine

A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process. There are opportunities to decrease bagasse moisture from a milling unit. The behaviour of bagasse in chutes is poorly understood. Previous investigations have shown that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Progress has been made in the last 11 years towards implementing a mechanical model for bagasse in finite element software. The objective is to be able to correctly simulate various simple mechanical loading conditions measured in the laboratory. Combining these behaviours together is thought to have a high probability of reproducing the complicated stress conditions in a milling unit. This paper reports on progress made towards modelling the fifth and final (and most challenging) of the simple loading conditions: the shearing of heavily over-consolidated bagasse, using a specific model for bagasse in a multi-element simulation.

A multi-level ecological model of psychotropic prescribing to adults with intellectual disability

Purpose – Simple linear accounts of prescribing do not adequately address reasons “why” doctors prescribe psychotropic medication to people with intellectual disability (ID). Greater understanding of the complex array of factors that influence decisions to prescribe is needed. Design/methodology/approach – After consideration of a number of conceptual frameworks that have potential to better understand prescribing of psychotropic medication to adults with ID, an ecological model of prescribing was developed. A case study is used to outline how the model can provide greater understanding of prescribing processes. Findings – The model presented aims to consider the complexity and multi-dimensional nature of community-based psychotropic prescribing to adults with ID. The utility of the model is illustrated through a consideration of the case study. Research limitations/implications – The model presented is conceptual and is as yet untested. Practical implications – The model presented aims to capture the complexity and multi-dimensional nature of community-based psychotropic prescribing to adults with ID. The model may provide utility for clinicians and researchers as they seek clarification of prescribing decisions. Originality/value – The paper adds valuable insight into factors influencing psychotropic prescribing to adults with ID. The ecological model of prescribing extends traditional analysis that focuses on patient characteristics and introduces multi-level perspectives that may provide utility for clinicians and researchers.

The educational design ladder : creation of a multi-discipline design thinking program

As global industries change and technology advances, traditional education systems may no longer be able to supply companies with graduates possessing an appropriate mix of skills and experience. The recent increased interest in Design Thinking as an approach to innovation has resulted in its adoption by non-design trained professionals. This necessitates a new method of teaching Design Thinking related skills and processes. This research investigates what (content) and how (assessment and learning modes) Design Thinking is being taught from fifty-one (51) selected courses across twenty-eight (28) international universities. Their approaches differ, with some universities specifically investing in design schools and programs, while others embed Design Thinking holistically throughout the university. Business, engineering and design schools are all expanding their efforts to teach students how to innovate, often through multi-disciplinary classes. This paper presents ‘The Educational Design Ladder’ a resource model, which suggests a process for the organisation and structuring of units for a multi-disciplinary Design Thinking program. The intention is to provide 21st century graduates with the right combination of skills and experience to solve workplace design problems regardless of their core discipline.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

The impact of prolonged hyperinsulinaemia on glucose transport in equine skeletal muscle and digital lamellae

REASONS FOR PERFORMING STUDY An increased incidence of metabolic disease in horses has led to heightened recognition of the pathological consequences of insulin resistance (IR). Laminitis, failure of the weight-bearing digital lamellae, is an important consequence. Altered trafficking of specialised glucose transporters (GLUTs) responsible for glucose uptake, are central to the dysregulation of glucose metabolism and may play a role in laminitis pathophysiology. OBJECTIVES We hypothesised that prolonged hyperinsulinaemia alters the regulation of glucose transport in insulin-sensitive tissue and digital lamellae. Our objectives were to compare the relative protein expression of major GLUT isoforms in striated muscle and digital lamellae in healthy horses and during hyperinsulinaemia. STUDY DESIGN Randomised, controlled study. METHODS Prolonged hyperinsulinaemia and lamellar damage were induced by a prolonged-euglycaemic hyperinsulinaemic clamp (p-EHC) or a prolonged-glucose infusion (p-GI) and results were compared to electrolyte-treated controls. GLUT protein expression was examined with immunoblotting. RESULTS Lamellar tissue contained more GLUT1 protein than skeletal muscle (p = 0.002) and less GLUT4 than the heart (p = 0.037). During marked hyperinsulinaemia and acute laminitis (induced by the p-EHC), GLUT1 protein expression was decreased in skeletal muscle (p = 0.029) but unchanged in the lamellae, while novel GLUTs (8; 12) were increased in the lamellae (p = 0.03), but not skeletal muscle. However, moderate hyperinsulinaemia and subclinical laminitis (induced by the p-GI) did not cause differential GLUT protein expression in the lamellae vs. control horses. CONCLUSIONS The results suggest that lamellar tissue functions independently of insulin and that IR may not be an essential component of laminitis aetiology. Marked differences in GLUT expression exist between insulin-sensitive and insulin-independent tissues during metabolic dysfunction in horses. The different expression profiles of novel GLUTs during acute and subclinical laminitis may be important to disease pathophysiology and require further investigation.