Joint Determination of the State Dimension and Autoregressive Order for Models with Markov Regime Switching

Abstract. This paper is concerned with the problem of joint determination of the state dimension and autoregressive order of models with Markov‐switching parameters. A model selection procedure is proposed which is based on optimization of complexity‐penalized likelihood criteria. The efficacy of the procedure is evaluated by means of Monte Carlo experiments.     

New conductive thermoplastic elastomers. Part II. Physical and chemical‐physical characterization

To overcome the problems relevant to the low processbility and scarce mechanical properties of polyaniline, in a previous work we have proposed the synthesis of elastomeric conducting copolymers prepared by grafting polyaniline (EB) or sulfonated polyaniline (SPAN) chains to the backbone of a carboxylated segmented polyurethane (PEUA). In the present work the physical and chemical‐physical properties of the copolymers are investigated. As evidenced by thermal (DSC) and dynamo‐mechanical (DMTA) characterization, the introduction of EB or SPAN in the matrix enhances the hard‐soft phase segregation effect, because of the strong tendency of the conductive polymer chains to aggregate. Moreover, the EB and SPAN chains, grafted to the polyurethane backbone, acting as reinforcing filler, give rise, compared with the mechanical properties of the insulating matrix, to an increase of the Young modulus and a decrease of the tensile set. When the copolymers are HCl doped their electrical conductivity increases many orders of magnitude, reaching values of about 10^?3 Ω^?1 cm^?1. The conductivity, measured along the deformation direction, may be further increased by stretching the copolymer films. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 1259–1264, 2002     

A systematic review of the potential hurdles of interoperability to the emergency services in major incidents: recommendations for solutions and alternatives

This study presents a narrative synthesis of a systematic literature review relating to multi-agency interoperability and major incident decision-making in high risk, high stake environments. The review methodology includes the identification of relevant studies, a critical appraisal of the concepts inherent in the main review question and a narrative synthesis of the central themes that relate to the study as a whole. The review firstly outlines what, currently, appear to be the perceived defining features of successful interoperability by using the SAFE-T phase model of major incident decision-making. It then considers whether these defining features are realistically achievable in major incident practice. Findings suggest that the current definition of an interoperable network is too demanding for the inherent complexity and dynamic nature of the major incident task environment. Individual teams tend to focus on agency-specific behaviour, as opposed to coordinated multi-team functioning, and so collective interoperability is not achieved. Inevitably, this reduces the ability to perform collaborative behaviours, including decision-making and action implementation. The paper concludes that aiming for the current conceptualisation of interoperability along a hierarchical command structure may actually inhibit effective decision-making. Instead, multi-agency systems would do better to work towards an improved understanding of a non-hierarchical and decentralised yet interoperable major incident management network. Recommendations include the need to relate theory and practice in the development of multi-agency decision-making via simulation-based training and to deepen our understanding of interoperability to prevent inertia in high risk, high stake major incident environments.     

Coping with uncertainty: police strategies for resilient decision-making and action implementation

This study uses a hostage negotiation setting to demonstrate how a team of strategic police officers can utilize specific coping strategies to minimize uncertainty at different stages of their decision-making in order to foster resilient decision-making to effectively manage a high-risk critical incident. The presented model extends the existing research on coping with uncertainty by (1) applying the RAWFS heuristic (Lipshitz and Strauss in Organ Behav Human Decis Process 69:149–163, 1997) of individual decision-making under uncertainty to a team critical incident decision-making domain; (2) testing the use of various coping strategies during “in situ” team decision-making by using a live simulated hostage negotiation exercise; and (3) including an additional coping strategy (“reflection-in-action”; Schön in The reflective practitioner: how professionals think in action. Temple Smith, London, 1983) that aids naturalistic team decision-making. The data for this study were derived from a videoed strategic command meeting held within a simulated live hostage training event; these video data were coded along three themes: (1) decision phase; (2) uncertainty management strategy; and (3) decision implemented or omitted. Results illustrate that, when assessing dynamic and high-risk situations, teams of police officers cope with uncertainty by relying on “reduction” strategies to seek additional information and iteratively update these assessments using “reflection-in-action” (Schön 1983) based on previous experience. They subsequently progress to a plan formulation phase and use “assumption-based reasoning” techniques in order to mentally simulate their intended courses of action (Klein et al. 2007), and identify a preferred formulated strategy through “weighing the pros and cons” of each option. In the unlikely event that uncertainty persists to the plan execution phase, it is managed by “reduction” in the form of relying on plans and standard operating procedures or by “forestalling” and intentionally deferring the decision while contingency planning for worst-case scenarios.     

A microfluidic optical beam steerer

This paper reports the fabrication and characterization of a prototype microfluidic device that can act as a periodic beam steerer. The prototype is formed by a simple T-junction followed by a serpentine channel that allows generation of a periodical segmented flow of air and water bubbles. If light hits the channel wall with a suitable angle, it can be either transmitted or reflected by the segmented flow, giving rise to an alternating beam steerer. The duty cycle, switching frequency, and overall stability and reproducibility of this prototype system are presented and discussed.     

Probabilistic consensus clustering using evidence accumulation

Machine Learning - Clustering ensemble methods produce a consensus partition of a set of data points by combining the results of a collection of base clustering algorithms. In the evidence...     

Time‐multiplexed tiled projection system with improved pixel and spatial resolution

We propose two methods to increase the pixel and spatial resolution of Digital Micromirror Devices (DMD)‐based projectors by utilizing the large bandwidth provided by their high pattern rates. By varying the intensity of the illumination for each binary pattern displayed on the DMD, the time required to display an 8‐bit grayscale image can be reduced by up to factor 32 compared to using constant illumination and binary pulse‐width modulation (BPWM). The high image rate projection is then spatially separated by either using a galvanometer scanner or sequentially illuminating the DMD from different directions, thus creating multiple independently addressable projections which are then tiled to form a larger, higher resolution image.     

Flow-based reputation with uncertainty: evidence-based subjective logic

The concept of reputation is widely used as a measure of trustworthiness based on ratings from members in a community. The adoption of reputation systems, however, relies on their ability to capture the actual trustworthiness of a target. Several reputation models for aggregating trust information have been proposed in the literature. The choice of model has an impact on the reliability of the aggregated trust information as well as on the procedure used to compute reputations. Two prominent models are flow-based reputation (e.g., EigenTrust, PageRank) and subjective logic-based reputation. Flow-based models provide an automated method to aggregate trust information, but they are not able to express the level of uncertainty in the information. In contrast, subjective logic extends probabilistic models with an explicit notion of uncertainty, but the calculation of reputation depends on the structure of the trust network and often requires information to be discarded. These are severe drawbacks. In this work, we observe that the ‘opinion discounting’ operation in subjective logic has a number of basic problems. We resolve these problems by providing a new discounting operator that describes the flow of evidence from one party to another. The adoption of our discounting rule results in a consistent subjective logic algebra that is entirely based on the handling of evidence. We show that the new algebra enables the construction of an automated reputation assessment procedure for arbitrary trust networks, where the calculation no longer depends on the structure of the network, and does not need to throw away any information. Thus, we obtain the best of both worlds: flow-based reputation and consistent handling of uncertainties.