Automating computational proofs for public-key-based key exchange

We present an approach to automating computationally sound proofs of key exchange protocols based on public-key encryption. We show that satisfying the property called occultness in the Dolev-Yao model guarantees the security of a related key exchange protocol in a simple computational model. Security in this simpler model has been shown to imply security in a Bellare {Rogaway-like model. Furthermore, the occultness in the Dolev-Yao model can be searched automatically by a mechanisable procedure. Thus automated proofs for key exchange protocols in the computational model can be achieved. We illustrate the method using the well-known Lowe-Needham-Schroeder protocol.

Identifying key belief-based targets for promoting regular physical activity among mothers and fathers with young children

We investigated the key beliefs to target in interventions aimed at increasing physical activity (PA) among mothers and fathers of young children. Parents (288 mothers and 292 fathers) completed a Theory of Planned Behaviour belief-based questionnaire and a 1-week follow-up of PA behaviour. We found that a range of behavioural, normative, and control beliefs were significantly correlated with parents’ PA intentions and behaviour, with only a few differences observed in correlations between PA beliefs and intention and behaviour by gender. A range of key beliefs was identified as making independent contributions to parents’ PA intentions; however, the behavioural beliefs about improving parenting practices (β = 0.13), interfering with other commitments (β = −0.29); normative beliefs about people I exercise with (β = 0.20); and control beliefs about lack of time (β = −0.24), inconvenience (β = −0.14), lack of motivation (β = −0.34), were revealed as significant independent predictors of actual PA behaviour. Furthermore, we found that a limited amount of parents already hold these beliefs, suggesting that these key beliefs warrant changing and, therefore, are appropriate targets for subsequent intervention. The current study fills an empirical gap in the PA literature by investigating an at-risk group and using a well established theoretical framework to identify key beliefs that guide parents’ PA decision-making. Overall, we found support for parents being a unique group who hold distinctive behavioural, normative, and control beliefs toward PA. Attention to these key underlying beliefs will assist intervention work aimed at combating inactivity among this at-risk population.

Aircraft automation tasks requiring switching control

A key feature in future aircraft operations will be automation of various aircraft processes, such as air traffic separation management and the management of forced landing events. Automated versions of these processes will often involve consideration of multiple modes of operations and hence require consideration of automated decision processes able to switch between various available modes of operations. This paper proposes a switching algorithm on the basis of max-min decision theory. This algorithm is particularly suitable in situations where each operational mode has access to different set of partial information. We apply our proposed algorithm to the air traffic separation management problem. A simulation study is presented that illustrates the performance of the proposed switching algorithm.

The key to successful implementation : project management of sustainable infrastructure provision

Delivering infrastructure projects involves many stakeholders. Their responsibilities and authorities vary over the course of the project lifecycle - from establishing the project parameters and performance requirements, to operating and maintaining the completed infrastructure. To ensure the successful delivery of infrastructure projects, it is important for the project management team to identify and manage the stakeholders and their requirements. This chapter discusses the management of stakeholders in delivering infrastructure projects, from their conception to completion. It includes managing the stakeholders for project selection and involving them to improve project constructability, operability and maintainability.

A synthesizable hardware evolutionary algorithm design for unmanned aerial system real-time path planning

The main objective of this paper is to detail the development of a feasible hardware design based on Evolutionary Algorithms (EAs) to determine flight path planning for Unmanned Aerial Vehicles (UAVs) navigating terrain with obstacle boundaries. The design architecture includes the hardware implementation of Light Detection And Ranging (LiDAR) terrain and EA population memories within the hardware, as well as the EA search and evaluation algorithms used in the optimizing stage of path planning. A synthesisable Very-high-speed integrated circuit Hardware Description Language (VHDL) implementation of the design was developed, for realisation on a Field Programmable Gate Array (FPGA) platform. Simulation results show significant speedup compared with an equivalent software implementation written in C++, suggesting that the present approach is well suited for UAV real-time path planning applications.

A coupled meshless technique/molecular dynamics approach for deformation characterization of monocrystalline metal

This paper presents a multiscale study using the coupled Meshless technique/Molecular Dynamics (M2) for exploring the deformation mechanism of mono-crystalline metal (focus on copper) under uniaxial tension. In M2, an advanced transition algorithm using transition particles is employed to ensure the compatibility of both displacements and their gradients, and an effective local quasi-continuum approach is also applied to obtain the equivalent continuum strain energy density based on the atomistic poentials and Cauchy-Born rule. The key parameters used in M2 are firstly investigated using a benchmark problem. Then M2 is applied to the multiscale simulation for a mono-crystalline copper bar. It has found that the mono-crystalline copper has very good elongation property, and the ultimate strength and Young's modulus are much higher than those obtained in macro-scale.

A Taxonomy of image matching techniques for stereo vision

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.

Optimal voltage support mechanism in distribution networks

Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.

Luxury fashion: The role of innovation as a key contributing factor in the development of luxury fashion goods and sustainable fashion design

Luxury is a quality that is difficult to define as the historical concept of luxury appears to be both dynamic and culturally specific. The everyday definition explains a ‘luxury’ in relation to a necessity: a luxury (product or service) is defined as something that consumers want rather than need. However, the growth of global markets has seen a boom in what are now referred to as ‘luxury brands’. This branding of products as luxury has resulted in a change in the way consumers understand luxury goods and services. In their attempts to characterize a luxury brand, Fionda & Moore in their article “The anatomy of a Luxury Brand” summarize a range of critical conditions that are in addition to product branding “... including product and design attributes of quality, craftsmanship and innovative, creative and unique products” (Fionda & Moore, 2009). For the purposes of discussing fashion design however, quality and craftsmanship are inseparable while creativity and innovation exist under different conditions. The terms ‘creative’ and ‘innovative’ are often used inter-changeably and are connected with most descriptions of the design process, defining ‘design’ and ‘fashion’ in many cases. Christian Marxt and Fredrik Hacklin identify this condition in their paper “Design, product development, innovation: all the same in the end?”(Marxt & Hacklin, 2005) and suggest that design communities should be aware that the distinction between these terms, whilst once quite definitive, is becoming narrow to a point where they will mean the same thing. In relation to theory building in the discipline this could pose significant problems. Brett Richards (2003) identifies innovation as different from creativity in that innovation aims to transform and implement rather than simply explore and invent. Considering this distinction, in particular relation to luxury branding, may affect the way in which design can contribute to a change in the way luxury fashion goods might be perceived in a polarised fashion market, namely suggesting that ‘luxury’ is what consumers need rather than the ‘pile it high, sell it cheap’ fashion that the current market dynamic would indicate they want. This paper attempts to explore the role of innovation as a key contributing factor in luxury concepts, in particular the relationship between innovation and creativity, the conditions which enable innovation, the role of craftsmanship in innovation and design innovation in relation to luxury fashion products. An argument is presented that technological innovation can be demonstrated as a common factor in the development of luxury fashion product and that the connection between designer and maker will play an important role in the development of luxury fashion goods for a sustainable fashion industry.

Overview of the INEX 2010 XML mining track : clustering and classification of XML documents

The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.