Environmental modelling of the Chief Information Officer

Since the introduction of the term in the 1980’s, the role of the Chief Information Officer (CIO) has been widely researched. Various perceptions and dimensions of the role have been explored and debated. However, the explosion in data proliferation (and the inevitable resulting information fuelled change) further complicates organisational expectations of the CIOs role. If organisations are to competitively exploit the digital trend, then those charged with recruiting and developing CIOs now need to be more effective in determining (and shaping) CIO traits and attributes, within the context of their own organisational circumstances and in line with stakeholder expectations. CIOs also need to determine their own suitability and progression within their chosen organisation if they are to remain motivated and effective. Before modelling the role of the future CIO, it is necessary to synthesise our current knowledge (and the lessons learnt) about the CIO. This paper, therefore, aims to identify and summate the spectrum of key researched ‘themes’ pertaining to the role of the CIO. Summating previous research, themes are modelled around four key CIO ‘dimensions’, namely (1) Impacting factors, (2) Controlling factors (3) Responses and (4) CIO ‘attributes’. Having modelled the CIOs current environment, and recognising the evolving IT enabled information landscape, the authors call for further research to inform the recruitment and development of the future CIO in terms of personal attributes and the measurable impact such attributes will have on their respective organisation

Synthesis and properties of nickel-cobalt-boron nanoparticles

morphous cobalt nickel boride nanoparticles were synthesised by chemical reduction synthesis in aqueous solution. Careful control of synthesis conditions and post reaction oxidation enabled the nanoparticles to be converted into a core-shell structure comprising of an amorphous Co–Ni–B core and an outer metal oxide sheet. These particles had interesting magnetic properties including saturation magnetisations and coercivities of the order of 80 emu/g and 170 Oe respectively, making them suitable for a potential use as an exchange-pinned magnetic material

A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation

For high dimensional problems, such as approximation and integration, one cannot afford to sample on a grid because of the curse of dimensionality. An attractive alternative is to sample on a low discrepancy set, such as an integration lattice or a digital net. This article introduces a multivariate fast discrete Walsh transform for data sampled on a digital net that requires only $O(N \log N)$ operations, where $N$ is the number of data points. This algorithm and its inverse are digital analogs of multivariate fast Fourier transforms. This fast discrete Walsh transform and its inverse may be used to approximate the Walsh coefficients of a function and then construct a spline interpolant of the function. This interpolant may then be used to estimate the function's effective dimension, an important concept in the theory of numerical multivariate integration. Numerical results for various functions are presented

An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks

Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs

Simulation Modelling for Scenario Planning to Evaluate IVHM Benefit in Naval Ship Building

Naval ships are long life assets that could be called upon to perform missions not considered in their original design. The through life support arrangement is influenced by the military requirement as well as contracting practice. In navies that contract out the building and support of ships in different competitive packages, condition monitoring technology for through life health management may be stripped out to reduce ship building cost. This paper investigates the potential benefits of incorporating health management for the test and commissioning stages in naval shipbuilding to reduce the overall cost of a ship programme. Scenario planning using simulation suggests that for ships of high complexity in a multiple ships programme, health management is likely to enhance the lessons learnt process. The benefits to the follow on ships could justify the investment

The Size Distribution of Kuiper Belt Objects

We describe analytical and numerical collisional evolution calculations for the size distribution of icy bodies in the Kuiper Belt. For a wide range of bulk properties, initial masses, and orbital parameters, our results yield power-law cumulative size distributions, N_C propto r^{-q}, with q_L = 3.5 for large bodies with radii of 10-100 km, and q_s = 2.5-3 for small bodies with radii lesss than 0.1-1 km. The transition between the two power laws occurs at a break radius of 1-30 km. The break radius is more sensitive to the initial mass in the Kuiper Belt and the amount of stirring by Neptune than the bulk properties of individual Kuiper Belt objects (KBOs). Comparisons with observations indicate that most models can explain the observed sky surface density of KBOs for red magnitudes, R = 22-27. For R 28, the model surface density is sensitive to the amount of stirring by Neptune, suggesting that the size distribution of icy planets in the outer solar system provides independent constraints on the formation of Neptune.Comment: 24 pages of text, 12 figures; to appear in the Astronomical Journal, October 200

Gradients and anisotropies of high energy cosmic rays in the outer heliosphere

Previous studies at lower energies have shown that the cosmic ray density gradients vary in space and time, and many authors currently are suggesting that the radial gradient associated with solar cycle modulation is supported largely by narrow barriers which encircle the Sun and propagate outward with the solar wind. If so, the anisotropy is a desirable way to detect spatial gradients, because it can be associated with the local solar wind and magnetic field conditions. With this in mind, the anisotropy measurements made by the UCSD Cerenkov detectors on Pioneers 10 and 11 are studied. It is shown that the local anisotropy varies greatly, but that the long term average is consistent with the global radial gradient measured between two spacecraft over a baseline of many AU

Gradients and anisotropies of high energy cosmic rays in the outer heliosphere

Two cosmic rays which pass through the same point going in opposite directions will, in the absence of scattering and inhomogeneities in the magnetic field, trace helices about adjacent flux tubes, whose centerlines are separated by one gyrodiameter. A directional anisotropy at the point suggests a difference in the number of cosmic rays loading the two flux tubes; that is, a density gradient over the baseline of a gyrodiameter. Previous studies at lower energies have shown that the cosmic ray density gradients vary in time and space. It is suggested that the radial gradient associated with solar cycle modulation is supported largely by narrow barriers which encircle the sun and propagate outward with the solar wind. If so, the anisotropy is a desirable way to detect spatial gradients, because it can be associated with the local solar wind and magnetic field conditions. Anisotropic measurements made by Cerenkov detectors on Pioneers 10 and 11 were studied. It was found that local anisotropy varies greatly, but that the long term average is consistent with the global radial gradient measured between two spacecraft over a baseline of many AU

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency