Design and analysis of dual-rail circuits for security applications

Dual-rail encoding, return-to-spacer protocol, and hazard-free logic can be used to resist power analysis attacks by making energy consumed per clock cycle independent of processed data. Standard dual-rail logic uses a protocol with a single spacer, e.g., all-zeros, which gives rise to energy balancing problems. We address these problems by incorporating two spacers; the spacers alternate between adjacent clock cycles. This guarantees that all gates switch in every clock cycle regardless of the transmitted data values. To generate these dual-rail circuits, an automated tool has been developed. It is capable of converting synchronous netlists into dual-rail circuits and it is interfaced to industry CAD tools. Dual-rail and single-rail benchmarks based upon the advanced encryption standard (AES) have been simulated and compared in order to evaluate the method and the tool.

Design and Analysis of an Independent, Layer 2, Open-Access WiFi Monitoring Infrastructure in the Wild

While WiFi monitoring networks have been deployed in previous research, to date none have assessed live network data from an open access, public environment. In this paper we describe the construction of a replicable, independent WLAN monitoring system and address some of the challenges in analysing the resultant traffic. Analysis of traffic from the system demonstrates that basic traffic information from open-access networks varies over time (temporal inconsistency). The results also show that arbitrary selection of Request-Reply intervals can have a significant effect on Probe and Association frame exchange calculations, which can impact on the ability to detect flooding attacks.

Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

Power take-off and damping of an oscillating wave surge converter

The European Union has set a target of 20% for the share of renewable energy sources in gross final energy consumption in 2020. These renewable energy targets are priority objectives for the Europe 2020 strategy for inclusive growth. In line with the European Union renewable energy policies, the Northern Ireland Executive has a target to deliver 40% renewable electricity by 2020. Currently, Northern Ireland imports 98% of the energy it uses in the form of fossil fuels. Locally produced energy and electricity is needed to ensure sustainable development. The aim of this research is to develop part of a strategy for the mechanical power take-off system for a flap type wave energy converter. Aquamarine Power Ltd’s Oyster flap was the device used for simulation and testing purposes. In this paper the state-of-the-art of wave energy converters is reviewed and a 40th scale test model was developed and built.

Offshore wind power forecasting error and electricity market implications

Wind energy has been identified as key to the European Union’s 2050 low carbon economy. However, as wind is a variable resource and stochastic by nature, it is difficult to plan and schedule the power system under varying wind power generation. This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact of the magnitude and variance of the offshore wind power forecast error on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price is analysed. The main findings of this research are that the magnitude of the offshore wind power forecast error has the largest impact on system generation costs and dispatch-down of wind, but the variance of the offshore wind power forecast error has the biggest impact on emissions costs and system marginal price. Overall offshore wind power forecast error variance results in a system marginal price increase of 9.6% in 2050.

The Outcomes of Cross-Cultural Adjustment: A Case of British Expatriates Working on International Architectural, Engineering and Construction Assignments

The main aim of this study is to investigate the consequences of cross-cultural adjustment in an under researched sample of British expatriates working on International Architectural, Engineering and Construction (AEC) assignments. Adjustment is the primary outcome of an expatriate assignment. According to Bhaskar-Srinivas et al., (2005), Harrison et al., (2004) it is viewed to affect other work related outcomes which could eventually predict expatriate success. To address the scarcity of literature on expatriate management in the AEC sector, an exploratory design was adopted. Phase one is characterised by extensive review of extant literature, whereas phase two was qualitative exploration from British expatriates’ perspective; here seven unstructured interviews were carried out. Further, cognitive mapping analysis through Banaxia decision explorer software was conducted to develop a theoretical framework and propose various hypotheses. The findings imply that British AEC firms could sustain their already established competitive advantage in the global marketplace by acknowledging the complexity of international assignments, prioritising expatriate management and offering a well-rounded support to facilitate expatriate adjustment and ultimately achieve critical outcomes like performance, assignment completion and job satisfaction.

The outcomes of cross-cultural adjustment: A case of British expatriates working on international architectural, engineering and construction assignments

The main aim of this study is to investigate the consequences of cross-cultural adjustment in an under researched sample of British expatriates working on International Architectural, Engineering and Construction (AEC) assignments. Adjustment is the primary outcome of an expatriate assignment. According to Bhaskar-Srinivas et al., (2005), Harrison et al., (2004) it is viewed to affect other work related outcomes which could eventually predict expatriate success. To address the scarcity of literature on expatriate management in the AEC sector, an exploratory design was adopted. Phase one is characterised by extensive review of extant literature, whereas phase two was qualitative exploration from British expatriatesÕ perspective; here seven unstructured interviews were carried out. Further, cognitive mapping analysis through Banaxia decision explorer software was conducted to develop a theoretical framework and propose various hypotheses. The findings imply that British AEC firms could sustain their already established competitive advantage in the global marketplace by acknowledging the complexity of international assignments, prioritising expatriate management and offering a well-rounded support to facilitate expatriate adjustment and ultimately achieve critical outcomes like performance, assignment completion and job satisfaction.

A new performance based method for design and maintenance of reinforced concrete structures

Best concrete research paper by a student - Research has shown that the cost of managing structures puts high strain on the infrastructure budget, with
estimates of over 50% of the European construction budget being dedicated to repair and maintenance. If reinforced concrete
structures are not suitably designed and adequately maintained, their service life is compromised, resulting in the full economic
value of the investment not realised. The issue is more prevalent in coastal structures as a result of combinations of aggressive
actions, such as those caused by chlorides, sulphates and cyclic freezing and thawing.
It is a common practice nowadays to ensure durability of reinforced concrete structures by specifying a concrete mix and a
nominal cover at the design stage to cater for the exposure environment. This in theory should produce the performance required
to achieve a specified service life. Although the European Standard EN 206-1 specifies variations in the exposure environment,
it does not take into account the macro and micro climates surrounding structures, which have a significant influence on their
performance and service life. Therefore, in order to construct structures which will perform satisfactorily in different exposure
environments, the following two aspects need to be developed: a performance based specification to supplement EN 206-1
which will outline the expected performance of the structure in a given environment; and a simple yet transferrable procedure
for assessing the performance of structures in service termed KPI Theory. This will allow the asset managers not only to design
structures for the intended service life, but also to take informed maintenance decisions should the performance in service fall
short of what was specified. This paper aims to discuss this further.

Flexible fault ride through strategy for wind farm clusters in power systems with high wind power penetration

This paper investigates a flexible fault ride through strategy for power systems in China with high wind power penetration. The strategy comprises of adaptive fault ride through requirements and maximum power restrictions of the wind farms with weak fault ride through capabilities. The slight faults and moderate faults with high probability are the main defending objective of the strategy. The adaptive fault ride through requirement in the strategy consists of two sub fault ride through requirements, a temporary slight voltage ride through requirement corresponding to a slight fault incident, with a moderate voltage ride through requirement corresponding to a moderate fault. The temporary overloading capability of the wind farm is reflected in both requirements to enhance the capability to defend slight faults and to avoid tripping when the crowbar is disconnected after moderate faults are cleared. For those wind farms that cannot meet the adaptive fault ride through requirement, restrictions are put on the maximum power output. Simulation results show that the flexible fault ride through strategy increases the fault ride through capability of the wind farm clusters and reduces the wind power curtailment during faults.

Conceptual Design and Workspace Analysis of an Exechon-inspired Parallel Kinematic Machine

Inspired by the commercial application of the Exechon machine, this paper proposed a novel parallel kinematic machine (PKM) named Exe-Variant. By exchanging the sequence of kinematic pairs in each limb of the Exechon machine, the Exe-Variant PKM claims an arrangement of 2UPR/1SPR topology and consists of two identical UPR limbs and one SPR limb. The inverse kinematics of the 2UPR/1SPR parallel mechanism was firstly analyzed based on which a conceptual design of the Exe-Variant was carried out. Then an algorithm of reachable workspace searching for the Exe-Variant and the Exchon was proposed. Finally, the workspaces of two example systems of the Exechon and the Exe-Variant with approximate dimensions were numerically simulated and compared. The comparison shows that the Exe-Variant possesses a competitive workspace with the Exechon machine, indicating it can be used as a promising reconfigurable module in a hybrid 5-DOF machine tool system.

Gas generation in interconnected power systems with high wind power penetration

Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

Design and Analysis of Inexact Floating-Point Adders

Power has become a key constraint in nanoscale inte-grated circuit design due to the increasing demands for mobile computing and higher integration density. As an emerging compu-tational paradigm, an inexact circuit offers a promising approach to significantly reduce both dynamic and static power dissipation for error-tolerant applications. In this paper, an inexact floating-point adder is proposed by approximately designing an exponent sub-tractor and mantissa adder. Related operations such as normaliza-tion and rounding are also dealt with in terms of inexact computing. An upper bound error analysis for the average case is presented to guide the inexact design; it shows that the inexact floating-point adder design is dependent on the application data range. High dynamic range images are then processed using the proposed inexact floating-point adders to show the validity of the inexact design; comparison results show that the proposed inexact floating-point adders can improve the power consumption and power-delay product by 29.98% and 39.60%, respectively.

Design and physicochemical characterisation of novel dissolving polymeric microneedle arrays for transdermal delivery of high dose, low molecular weight drugs

We describe formulation and evaluation of novel dissolving polymeric microneedle (MN) arrays for the facilitated delivery of low molecular weight, high dose drugs. Ibuprofen sodium was used as the model here and was successfully formulated at approximately 50% w/w in the dry state using the copolymer poly(methylvinylether/maleic acid). These MNs were robust and effectively penetrated skin in vitro, dissolving rapidly to deliver the incorporated drug. The delivery of 1.5mg ibuprofen sodium, the theoretical mass of ibuprofen sodium contained within the dry MN alone, was vastly exceeded, indicating extensive delivery of the drug loaded into the baseplates. Indeed in in vitro transdermal delivery studies, approximately 33mg (90%) of the drug initially loaded into the arrays was delivered over 24h. Iontophoresis produced no meaningful increase in delivery. Biocompatibility studies and in vivo rat skin tolerance experiments raised no concerns. The blood plasma ibuprofen sodium concentrations achieved in rats (263μgml(-1) at the 24h time point) were approximately 20 times greater than the human therapeutic plasma level. By simplistic extrapolation of average weights from rats to humans, a MN patch design of no greater than 10cm(2) could cautiously be estimated to deliver therapeutically-relevant concentrations of ibuprofen sodium in humans. This work, therefore, represents a significant progression in exploitation of MN for successful transdermal delivery of a much wider range of drugs.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.