An Innovative Approach to Evaluating Organisational Change

This paper addresses the difficult problem of how to improve the process of evaluating organisational change. Given that the data emergent from an evaluative exercise will strongly influence the subsequent strategic and operational decisions taken by organisational managers, it is critical that the evaluation approach itself is capable of delivering high quality, accurate and timely data. The aim of this paper is to examine the role of the IT-based Optionfinder Technology used in conjunction with focus groups, in generating management decision-making data, and reflecting the changes in key performance indicators in a utility organisation. The case study research evaluates the innovative integrative approach adopted by the utility organisation and concludes that the proposed approach contributes to improvements in the decision-making capability of managers.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Amplitude banded RLS approach to time variant channel equalization

This paper proposes a non-linear adaptive algorithm, the amplitude banded RLS (ABRLS) algorithm, as an adaptation procedure for time variant channel equalizers. In the ABRLS algorithm, a coefficient matrix is updated based on the amplitude level of the received sequence. To enhance the capability of tracking for the ABRLS algorithm, a parallel adaptation scheme is utilized which involves the structures of decision feedback equalizer (DFE). Computer simulations demonstrate that the novel ABRLS based equalizer provides a significant improvement relative to the conventional RLS DFE on a rapidly time variant communication channel.

Whole-Life Costing for Capability

In recent years, there has been growing emphasis on the need to provide transparency in the costs of engineering programmes, leading to growing emphasis on Whole Life Cost (WLC) modelling techniques. This has arisen largely due to the increased interested in longer timescale projects and programmes, combined with the emergence of system-of-systems and network enabled capability concepts. This change in the implementation and management of large scale projects has necessitated the development of alternative methods of evaluating performance. This work seeks to address the shortfalls in current costing methodologies when applied to these highly flexible environments, and to propose a conceptual model for dealing with the encountered complexities. The approach has a fundamental role and potential significance in the future of whole life costing for Network Enabled Capability (NEC) but can also offer a potential paradigm shift for costing in traditional engineering environments.

An evaluation of the capability of a biolayer interferometry biosensor to detect low-molecular-weight food contaminants

The safety of our food is an essential requirement of society. One well-recognised threat is that of chemical contamination of our food, where low-molecular-weight compounds such as biotoxins, drug residues and pesticides are present. Low-cost, rapid screening procedures are sought to discriminate the suspect samples from the population, thus selecting only these to be forwarded for confirmatory analysis. Many biosensor assays have been developed as screening tools in food contaminant analysis, but these tend to be electrochemical, fluorescence or surface plasmon resonance based. An alternative approach is the use of biolayer interferometry, which has become established in drug discovery and life science studies but is only now emerging as a potential tool in the analysis of food contaminants. A biolayer interferometry biosensor was assessed using domoic acid as a model compound. Instrument repeatability was tested by simultaneously producing six calibration curves showing replicate repeatability (n = 2) ranging from 0.1 to 6.5 % CV with individual concentration measurements (n = 12) ranging from 4.3 to 9.3 % CV, giving a calibration curve midpoint of 7.5 ng/ml (2.3 % CV (n = 6)). Reproducibility was assessed by producing three calibration curves on different days, giving a midpoint of 7.5 ng/ml (3.4 %CV (n = 3)). It was further shown, using assay development techniques, that the calibration curve midpoint could be adjusted from 10.4 to 1.9 ng/ml by varying assay parameters before the simultaneous construction of three calibration curves in matrix and buffer. Sensitivity of the assay compared favourably with previously published biosensor data for domoic acid. © 2013 Springer-Verlag Berlin Heidelberg.

Generalized Langevin equation: An efficient approach to nonequilibrium molecular dynamics of open systems

The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e. g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

Predicting invasive species impacts: a community module functional response approach reveals context dependencies

Summary
-Predatory functional responses play integral roles in predator–prey dynamics, and their assessment promises greater understanding and prediction of the predatory impacts of invasive species.
-Other interspecific interactions, however, such as parasitism and higher-order predation, have the potential to modify predator–prey interactions and thus the predictive capability of the comparative functional response approach.
-We used a four-species community module (higher-order predator; focal native or invasive predators; parasites of focal predators; native prey) to compare the predatory functional responses of native Gammarus duebeni celticus and invasive Gammarus pulex amphipods towards three invertebrate prey species (Asellus aquaticus, Simulium spp., Baetis rhodani), thus, quantifying the context dependencies of parasitism and a higher-order fish predator on these functional responses.
-Our functional response experiments demonstrated that the invasive amphipod had a higher predatory impact (lower handling time) on two of three prey species, which reflects patterns of impact observed in the field. The community module also revealed that parasitism had context-dependent influences, for one prey species, with the potential to further reduce the predatory impact of the invasive amphipod or increase the predatory impact of the native amphipod in the presence of a higher-order fish predator.
-Partial consumption of prey was similar for both predators and occurred increasingly in the order A. aquaticus, Simulium spp. and B. rhodani. This was associated with increasing prey densities, but showed no context dependencies with parasitism or higher-order fish predator.
-This study supports the applicability of comparative functional responses as a tool to predict and assess invasive species impacts incorporating multiple context dependencies.

Directional Modulation Far-field Pattern Separation Synthesis Approach

In this study, a far-field power pattern separation approach is proposed for the synthesis of directional modulation (DM) transmitter arrays. Separation into information patterns and interference patterns is enabled by far-field pattern null steering. Compared with other DM synthesis methods, for example, bit error rate-driven DM optimisation and orthogonal vector injection, the approach developed in this study facilitates manipulation of artificial interference spatial distributions. With such capability more interference power can be projected into those spatial directions most vulnerable to eavesdropping, that is, the information side lobes. In such a fashion, information leaked through radiation side lobes can be effectively mitigated in a transmitter power efficient manner. Furthermore, for the first time, the authors demonstrate how multi-beam DM transmitters can be synthesised via this approach.

Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

Orthogonal Vector Approach for Synthesis of Multi-beam Directional Modulation Transmitters

An orthogonal vector approach is proposed for the synthesis of multi-beam directional modulation (DM) transmitters. These systems have the capability of concurrently projecting independent data streams into different specified spatial directions while simultaneously distorting signal constellations in all other directions. Simulated bit error rate (BER) spatial distributions are presented for various multi-beam system configurations in order to illustrate representative examples of physical layer security performance enhancement that can be achieved.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Developing management capability within a horizontal supply chain in performance measurement deployment and evolution: A Dynamic Capabilities and Goal Theory perspective

Complex collaboration in rapidly changing business environments create challenges for management capability in Utility Horizontal Supply Chains (UHSCs) involving the deploying and evolving of performance measures. The aim of the study is twofold. First, there is a need to explore how management capability can be developed and used to deploy and evolve Performance Measurement (PM), both across a UHSC and within its constituent organisations, drawing upon a theoretical nexus of Dynamic Capability (DC) theory and complementary Goal Theory. Second, to make a contribution to knowledge by empirically building theory using these constructs to show the management motivations and behaviours within PM-based DCs. The methodology uses an interpretive theory building, multiple case based approach (n=3) as part of a USHC. The data collection methods include, interviews (n=54), focus groups (n=10), document analysis and participant observation (reflective learning logs) over a five-year period giving longitudinal data. The empirical findings lead to the development of a conceptual framework showing that management capabilities in driving PM deployment and evolution can be represented as multilevel renewal and incremental Dynamic Capabilities, which can be further understood in terms of motivation and behaviour by Goal-Theoretic constructs. In addition three interrelated cross cutting themes of management capabilities in consensus building, goal setting and resource change were identified. These management capabilities require carefully planned development and nurturing within the UHSC. 

A Far-field Pattern Separation Approach for the Synthesis of Directional Modulation Transmitter Arrays (Invited)

In this paper a far-field power pattern separation approach is proposed for the synthesis of directional modulation (DM) transmitter arrays. Separation into information pattern and interference patterns is enabled by far-field pattern null steering. Compared with other DM synthesis methods, e.g., BER-driven DM optimization and orthogonal vector injection, this approach facilitates manipulation of artificial interference spatial distributions. With such capability more interference power can be projected into those most vulnerable to eavesdropping spatial directions in free space, i.e., the information sidelobes. In such a fashion information leaked through radiation sidelobes can be effectively mitigated in a transmitter power efficient manner. The proposed synthesis approach is further validated via bit error rate (BER) simulations.

Defining the content and delivery of an intervention to Change AdhereNce to treatment in BonchiEctasis (CAN-BE): a qualitative approach incorporating the Theoretical Domains Framework, behavioural change techniques and stakeholder expert panels

Background
Low patient adherence to treatment is associated with poorer health outcomes in bronchiectasis. We sought to use the Theoretical Domains Framework (TDF) (a framework derived from 33 psychological theories) and behavioural change techniques (BCTs) to define the content of an intervention to change patients’ adherence in bronchiectasis (Stage 1 and 2) and stakeholder expert panels to define its delivery (Stage 3).

Methods
We conducted semi-structured interviews with patients with bronchiectasis about barriers and motivators to adherence to treatment and focus groups or interviews with bronchiectasis healthcare professionals (HCPs) about their ability to change patients’ adherence to treatment. We coded these data to the 12 domain TDF to identify relevant domains for patients and HCPs (Stage 1). Three researchers independently mapped relevant domains for patients and HCPs to a list of 35 BCTs to identify two lists (patient and HCP) of potential BCTs for inclusion (Stage 2). We presented these lists to three expert panels (two with patients and one with HCPs/academics from across the UK). We asked panels who the intervention should target, who should deliver it, at what intensity, in what format and setting, and using which outcome measures (Stage 3).

Results
Eight TDF domains were perceived to influence patients’ and HCPs’ behaviours: Knowledge, Skills, Beliefs about capability, Beliefs about consequences, Motivation, Social influences, Behavioural regulation and Nature of behaviours (Stage 1). Twelve BCTs common to patients and HCPs were included in the intervention: Monitoring, Self-monitoring, Feedback, Action planning, Problem solving, Persuasive communication, Goal/target specified:behaviour/outcome, Information regarding behaviour/outcome, Role play, Social support and Cognitive restructuring (Stage 2). Participants thought that an individualised combination of these BCTs should be delivered to all patients, by a member of staff, over several one-to-one and/or group visits in secondary care. Efficacy should be measured using pulmonary exacerbations, hospital admissions and quality of life (Stage 3).

Conclusions
Twelve BCTs form the intervention content. An individualised selection from these 12 BCTs will be delivered to all patients over several face-to-face visits in secondary care. Future research should focus on developing physical materials to aid delivery of the intervention prior to feasibility and pilot testing. If effective, this intervention may improve adherence and health outcomes for those with bronchiectasis in the future.