Co-operating retrodirective system

Practical demonstration of the operational advantages gained through the use of a co-operating retrodirective array (RDA) basestation and Van Atta node arrangements is discussed. The system exploits a number of inherent RDA features to provide analogue real time multifunctional operation at low physical complexity. An active dual-conversion four element RDA is used as the power distribution source (basestation) while simultaneously achieving a receive sensitivity level of ??109 dBm and 3 dB automatic beam steering angle of ??45??. When mobile units are each equipped with a semi-passive four element Van Atta array, it is shown mobile device orientation issues are mitigated and optimal energy transfer can occur because of automatic beam formation resulting from retrodirective self-pointing action. We show that operation in multipath rich environments with or without line of sight acts to reduce average power density limits in the operating volume with high energy density occurring at mobile nodes sites only. The system described can be used as a full duplex ASK communications link, or, as a means for remote node charging by wireless means, thereby enhancing deployment opportunities between unstabilised moving platforms.

Evaluating a Computer System that Converses Fluently with People

The SAL system embodies a new kind of human-computer interaction, where a person and a computer carry out a fluent, emotionally coloured conversation. Because that kind of capability is new, evaluating systems that have it is a new challenge. This paper outlines techniques that have been developed to evaluate SAL interactions, and uses the case to highlight the range of variables that become relevant in dealing with systems of this order of complexity.

Rule-Based Intrusion Detection System for SCADA Networks

Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified using a ruled based method.

Intrusion Detection System for IEC 60870-5-104 Based SCADA Networks

Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified via Snort rules.

Multi-Attribute SCADA-Specific Intrusion Detection System for Power Networks

The increased interconnectivity and complexity of supervisory control and data acquisition (SCADA) systems in power system networks has exposed the systems to a multitude of potential vulnerabilities. In this paper, we present a novel approach for a next-generation SCADA-specific intrusion detection system (IDS). The proposed system analyzes multiple attributes in order to provide a comprehensive solution that is able to mitigate varied cyber-attack threats. The multiattribute IDS comprises a heterogeneous white list and behavior-based concept in order to make SCADA cybersystems more secure. This paper also proposes a multilayer cyber-security framework based on IDS for protecting SCADA cybersecurity in smart grids without compromising the availability of normal data. In addition, this paper presents a SCADA-specific cybersecurity testbed to investigate simulated attacks, which has been used in this paper to validate the proposed approach.

Low Complexity Spectral Analysis of Heart-Rate-Variability through a Wavelet based FFT

In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.

Complexity of concern: Social acceptance of wind energy and the inevitability of dissensus

This presentation will explore the  role that social acceptance of onshore wind can play in understanding and progressing the low carbon transition in Europe. Although this is commonly perceived as arising simply from the overall level of renewable energy generated (and ‘dirty’ energy displaced), its significance goes well beyond this as it helps us understand some of the key issues facing the electricity sector as a social-technical system.  As such it is not only a matter of delivering the necessary infrastructure, but requires the long term mediation of complex multi-governmental arrangements involving a very wide range of actors. The interests of these actors engage hugely different timescales, geographic scales of concern and rationalities that make the arena of social acceptance a cauldron of complexity, mediating between overlapping and incompatible concerns. The presentation will briefly review the nature of some of these relationships and discuss what this means for how we conceive and act on the social acceptance of wind, and what this means for the long term low carbon transition

The implausibility of ‘usual care’ in an open system: sedation and weaning practices in Paediatric Intensive Care Units (PICUs) in the United Kingdom (UK).

Background
The power of the randomised controlled trial depends upon its capacity to operate in a closed system whereby the intervention is the only causal force acting upon the experimental group and absent in the control group, permitting a valid assessment of intervention efficacy. Conversely, clinical arenas are open systems where factors relating to context, resources, interpretation and actions of individuals will affect implementation and effectiveness of interventions. Consequently, the comparator (usual care) can be difficult to define and variable in multi-centre trials. Hence outcomes cannot be understood without considering usual care and factors that may affect implementation and impact on the intervention.

Methods
Using a fieldwork approach, we describe PICU context, ‘usual’ practice in sedation and weaning from mechanical ventilation, and factors affecting implementation prior to designing a trial involving a sedation and ventilation weaning intervention. We collected data from 23 UK PICUs between June and November 2014 using observation, individual and multi-disciplinary group interviews with staff.

Results
Pain and sedation practices were broadly similar in terms of drug usage and assessment tools. Sedation protocols linking assessment to appropriate titration of sedatives and sedation holds were rarely used (9 % and 4 % of PICUs respectively). Ventilator weaning was primarily a medical-led process with 39 % of PICUs engaging senior nurses in the process: weaning protocols were rarely used (9 % of PICUs). Weaning methods were variably based on clinician preference. No formal criteria or use of spontaneous breathing trials were used to test weaning readiness. Seventeen PICUs (74 %) had prior engagement in multi-centre trials, but limited research nurse availability. Barriers to previous trial implementation were intervention complexity, lack of belief in the evidence and inadequate training. Facilitating factors were senior staff buy-in and dedicated research nurse provision.

Conclusions
We examined and identified contextual and organisational factors that may impact on the implementation of our intervention. We found usual practice relating to sedation, analgesia and ventilator weaning broadly similar, yet distinctively different from our proposed intervention, providing assurance in our ability to evaluate intervention effects. The data will enable us to develop an implementation plan; considering these factors we can more fully understand their impact on study outcomes.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

High-pressure phase equilibrium in the {carbon dioxide (1) + 1-chloropropane (2)} binary system

Abstract The current study reports original vapour-liquid equilibrium (VLE) for the system {CO2 (1) + 1-chloropropane (2)}. The measurements have been performed over the entire pressure-composition range for the (303.15, 313.15 and 328.15) K isotherms. The values obtained have been used for comparison of four predictive approaches, namely the equation of state (EoS) of Peng and Robinson (PR), the Soave modification of Benedict–Webb–Rubin (SBWR) EoS, the Critical Point-based Revised Perturbed-Chain Association Fluid Theory (CP-PC-SAFT) EoS, and the Conductor-like Screening Model for Real Solvents (COSMO-RS). It has been demonstrated that the three EoS under consideration yield similar and qualitatively accurate predictions of VLE, which is not the case for the COSMO-RS model examined. Although CP-PC-SAFT EoS exhibits only minor superiority in comparison with PR and SBWR EoS in predicting VLE in the system under consideration, its relative complexity can be justified when taking into account the entire thermodynamic phase space and, in particular, considering the liquid densities and sound velocities over a wider pressure-volume-temperature range.

Low complexity greedy detection method with generalized multicarrier index keying OFDM

Multicarrier Index Keying (MCIK) is a recently developed technique that modulates subcarriers but also indices of the subcarriers. In this paper a novel low-complexity detection scheme of subcarrier indices is proposed for an MCIK system and addresses a substantial reduction in complexity over the optimalmaximum likelihood (ML) detection. For the performance evaluation, a closed-form expression for the pairwise error probability (PEP) of an active subcarrier index, and a tight approximation of the average PEP of multiple subcarrier indices are derived in closed-form. The theoretical outcomes are validated usingsimulations, at a difference of less than 0.1dB. Compared to the optimal ML, the proposed detection achieves a substantial reduction in complexity with small loss in error performance (<= 0.6dB).

Preparing to prescribe: How do clerkship students learn in the midst of complexity?

Prescribing tasks, which involve pharmacological knowledge, clinical decision-making and practical skill, take place within unpredictable social environments and involve interactions within and between endlessly changing health care teams. Despite this, curriculum designers commonly assume them to be simple to learn and perform. This research used mixed methods to explore how undergraduate medical students learn to prescribe in the 'real world'. It was informed by cognitive psychology, sociocultural theory, and systems thinking. We found that learning to prescribe occurs as a dynamic series of socially negotiated interactions within and between individuals, communities and environments. As well as a thematic analysis, we developed a framework of three conceptual spaces in which learning opportunities for prescribing occur. This illustrates a complex systems view of prescribing education and defines three major system components: the "social space", where the environmental conditions influence or bring about a learning experience; the "process space", describing what happens during the learning experience; and the intra-personal "cognitive space", where the learner may develop aspects of prescribing expertise. This conceptualisation broadens the scope of inquiry of prescribing education research by highlighting the complex interplay between individual and social dimensions of learning. This perspective is also likely to be relevant to students' learning of other clinical competencies.

The role of complexity metrics in a multi-institutional dosimetry audit of VMAT

OBJECTIVE: To demonstrate the benefit of complexity metrics such as the modulation complexity score (MCS) and monitor units (MUs) in multi-institutional audits of volumetric-modulated arc therapy (VMAT) delivery.

METHODS: 39 VMAT treatment plans were analysed using MCS and MU. A virtual phantom planning exercise was planned and independently measured using the PTW Octavius(®) phantom and seven29(®) 2D array (PTW-Freiburg GmbH, Freiburg, Germany). MCS and MU were compared with the median gamma index pass rates (2%/2 and 3%/3 mm) and plan quality. The treatment planning systems (TPS) were grouped by VMAT modelling being specifically designed for the linear accelerator manufacturer's own treatment delivery system (Type 1) or independent of vendor for VMAT delivery (Type 2). Differences in plan complexity (MCS and MU) between TPS types were compared.

RESULTS: For Varian(®) linear accelerators (Varian(®) Medical Systems, Inc., Palo Alto, CA), MCS and MU were significantly correlated with gamma pass rates. Type 2 TPS created poorer quality, more complex plans with significantly higher MUs and MCS than Type 1 TPS. Plan quality was significantly correlated with MU for Type 2 plans. A statistically significant correlation was observed between MU and MCS for all plans (R = -0.84, p < 0.01).

CONCLUSION: MU and MCS have a role in assessing plan complexity in audits along with plan quality metrics. Plan complexity metrics give some indication of plan deliverability but should be analysed with plan quality.

ADVANCES IN KNOWLEDGE: Complexity metrics were investigated for a national rotational audit involving 34 institutions and they showed value. The metrics found that more complex plans were created for planning systems which were independent of vendor for VMAT delivery.

Appropriate complexity for the prediction of coastal and estuarine geomorphic behaviour at decadal to centennial scales

Coastal and estuarine landforms provide a physical template that not only accommodates diverse ecosystem functions and human activities, but also mediates flood and erosion risks that are expected to increase with climate change. In this paper, we explore some of the issues associated with the conceptualisation and modelling of coastal morphological change at time and space scales relevant to managers and policy makers. Firstly, we revisit the question of how to define the most appropriate scales at which to seek quantitative predictions of landform change within an age defined by human interference with natural sediment systems and by the prospect of significant changes in climate and ocean forcing. Secondly, we consider the theoretical bases and conceptual frameworks for determining which processes are most important at a given scale of interest and the related problem of how to translate this understanding into models that are computationally feasible, retain a sound physical basis and demonstrate useful predictive skill. In particular, we explore the limitations of a primary scale approach and the extent to which these can be resolved with reference to the concept of the coastal tract and application of systems theory. Thirdly, we consider the importance of different styles of landform change and the need to resolve not only incremental evolution of morphology but also changes in the qualitative dynamics of a system and/or its gross morphological configuration. The extreme complexity and spatially distributed nature of landform systems means that quantitative prediction of future changes must necessarily be approached through mechanistic modelling of some form or another. Geomorphology has increasingly embraced so-called ‘reduced complexity’ models as a means of moving from an essentially reductionist focus on the mechanics of sediment transport towards a more synthesist view of landform evolution. However, there is little consensus on exactly what constitutes a reduced complexity model and the term itself is both misleading and, arguably, unhelpful. Accordingly, we synthesise a set of requirements for what might be termed ‘appropriate complexity modelling’ of quantitative coastal morphological change at scales commensurate with contemporary management and policy-making requirements: 1) The system being studied must be bounded with reference to the time and space scales at which behaviours of interest emerge and/or scientific or management problems arise; 2) model complexity and comprehensiveness must be appropriate to the problem at hand; 3) modellers should seek a priori insights into what kind of behaviours are likely to be evident at the scale of interest and the extent to which the behavioural validity of a model may be constrained by its underlying assumptions and its comprehensiveness; 4) informed by qualitative insights into likely dynamic behaviour, models should then be formulated with a view to resolving critical state changes; and 5) meso-scale modelling of coastal morphological change should reflect critically on the role of modelling and its relation to the observable world.

Performance Analysis of a Low Complexity Detector for MCIK-OFDM over TWDP Fading

This letter analyzes the performance of a low complexity detection scheme for a multi-carrier index keying (MCIK) with orthogonal frequency division multiplexing (OFDM) system over two-wave with diffused power (TWDP) fading channels. A closed-form expression for the average pairwise error probability (PEP) over TWDP fading channels is derived. This expression is used to analyze the performance of MCIK-OFDM in moderate, severe and extreme fading conditions. The presented results provide an insight on the performance of MCIK-OFDM for wireless communication systems that operate in enclosed metallic structures such as in-vehicular device-to-device (D2D) wireless networks.