Management framework for corporate telecommunication and data centre information security

Network security, particularly Internet security, is at the forefront of business and government networks. This research has discovered weaknesses in current professional practice, particularly in mitigation strategies to reduce the impacts of security violations in corporate telecommunications and data centres. The importance of integrating security policies, processes and operational practice is demonstrated. Leadership models and innovation mechanisms best suited to improved security design are also identified.

Seeking the views of health professionals on translating chronic disease self-management models into practice

Abstract
Few studies have investigated the views of health professionals with respect to their use of chronic disease self-management (CDSM) in the workplace.
Objective
This qualitative study, conducted in an Australian health care setting, examined health professional's formal self-management (SM) training and their views and experiences on the use of SM techniques when working with people living with a chronic illness.
Methods
Purposive sample of 31 health care professionals from a range of service types participated in semi-structured interviews.
Results
The majority of participants (65%) had received no formal training in SM techniques. Participants reported a preference for an eclectic approach to SM, relying primarily on five elements: collaborative care, self-responsibility, client's individual situation, structured support and linking with community agencies. Problems with CDSM centred on medication management, complex measuring devices and limited efficacy with some patient groups.
Conclusion
This study provides valuable information with respect to the use of CDSM within the workplace from the unique perspective of a range of healthcare providers within an Australian health care setting.
Practice implications
Training implications, with respect to CDSM and patient care, are discussed, together with how these findings contribute to the debate concerning how SM principles are translated into healthcare settings.

An parallel information retrieval method for e-commerce

An online transaction always retrieves a large amount of information before making decisions. Currently, the parallel methods for retrieving such information can only provide a similar performance to serial methods. In this paper we first perform an analysis to determine the factors that affect the performance of exiting methods, i.e., HQR and EHQR, and show that the several of these factors are not considered by these methods. Motivated by this, we propose a new dispatch scheme called AEHQR, which takes into account the features of parallel dispatching. In addition, we provide cost models that determine the optimal performance achievable by any parallel dispatching method. Using experimental comparison, we illustrate that the AEHQR is significantly outperforms the HQR and EHQR under all conditions.

Simulation models of obesity : a review of the literature and implications for research and policy

Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research.

Multi-market industrial organizational economic models for the internationalization process by small and medium enterprise construction design service firms

Small and medium enterprises (SMEs) are critical to strategic initiatives in an economy; however, their contribution to foreign trade is not as significant. SMEs are one of the principal driving forces in economic development. One of the greatest challenges is the internationalization process for longevity rather than seeing the process as initial market entry. The internationalization process research has typically involved four key constructs: market selection, decision to enter, entry modes and factors affecting entry modes. Past research has focused on large manufacturing firms. The export of architectural, engineering and construction (AEC) firms has undergone growth, yet there is still significant opportunity for further growth. The majority of AEC firms are SMEs. Notwithstanding assistance provided through international trade missions, organized export firm support networks and information packages by a burgeoning number of government agencies, there are still perceived barriers to market entry and long-term economic sustainability for SMEs. There are a number of problems faced by SMEs acting in foreign trade. This investigation explores the successful initial internationalization process constructs and identifies unique project-oriented sector characteristics. The study identified similarities and differences between two firms that have been exporting to various localities, including Eastern Europe, Africa, Middle East, UK, Asia and South America, for more than two decades. The similarities and differences were identified within eight major constructs: purpose, firm type, market image and design philosophy, entry mode strategy, institutional arrangement, factors affecting mode of entry, market selection and firm strategy in relation to project selection. The primary reasons for internationalization were associated with the firms' motivations related to growth and financial viability. This article discusses the various internationalization processes and strategies intrinsic to each case study and establishes a detailed set of empirical observations from which to develop further a grounded theoretical model of reflexive capability for the internationalization process. This study contributes to the body of knowledge around the SME AEC design service firm's internationalization process, as a dynamic, evolving and continuously adaptable construct for project-based sectors.

Models of trust in business-to-consumer electronic commerce : a review of multi-disciplinary approaches

The issue of trust in Internet-based business-to-consumer electronic commerce has been explored from a number of difference perspectives. The current body of research is diverse and fragmented. This paper critically reviews recently published models pertaining to trust in business to consumer e-commerce. For analytical purposes we categorize the literature in three main streams: technological, design and sociological/psychological. Based on our analysis and our own empirical observations we raise four main areas of concern that warrant further research attention: an oversimplification of the trust concept, a uni-directional view of trust, discipline centered approaches to modelling trust and a lack of empirical grounding and testing. In the light of these concerns we recommend avenues for further research.

Scaling connectionist compositional representations

The Recursive Auto-Associative Memory (RAAM) has come to dominate connectionist investigations into representing compositional structure. Although an adequate model when dealing with limited data, the capacity of RAAM to scale-up to real-world tasks has been frequently questioned. RAAM networks are difficult to train (due to the moving target effect) and as such training times can be lengthy. Investigations into RAAM have produced many variants in an attempt to overcome such limitations. We outline how one such model ((S)RAAM) is able to quickly produce context-sensitive representations that may be used to aid a deterministic parsing process. By substituting a symbolic stack in an existing hybrid parser, we show that (S)RAAM is more than capable of encoding the real-world data sets employed. We conclude by suggesting that models such as (S)RAAM offer valuable insights into the features of connectionist compositional representations.

A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change

1. Informative Bayesian priors can improve the precision of estimates in ecological studies or estimate parameters for which little or no information is available. While Bayesian analyses are becoming more popular in ecology, the use of strongly informative priors remains rare, perhaps because examples of informative priors are not readily available in the published literature.
2. Dispersal distance is an important ecological parameter, but is difficult to measure and estimates are scarce. General models that provide informative prior estimates of dispersal distances will therefore be valuable.
3. Using a world-wide data set on birds, we develop a predictive model of median natal dispersal distance that includes body mass, wingspan, sex and feeding guild. This model predicts median dispersal distance well when using the fitted data and an independent test data set, explaining up to 53% of the variation.
4. Using this model, we predict a priori estimates of median dispersal distance for 57 woodland-dependent bird species in northern Victoria, Australia. These estimates are then used to investigate the relationship between dispersal ability and vulnerability to landscape-scale changes in habitat cover and fragmentation.
5. We find evidence that woodland bird species with poor predicted dispersal ability are more vulnerable to habitat fragmentation than those species with longer predicted dispersal distances, thus improving the understanding of this important phenomenon.
6. The value of constructing informative priors from existing information is also demonstrated. When used as informative priors for four example species, predicted dispersal distances reduced the 95% credible intervals of posterior estimates of dispersal distance by 8-19%. Further, should we have wished to collect information on avian dispersal distances and relate it to species' responses to habitat loss and fragmentation, data from 221 individuals across 57 species would have been required to obtain estimates with the same precision as those provided by the general model.

Modelling optimal risk allocation in PPP projects using artificial neural networks

This paper aims to establish, train, validate, and test artificial neural network (ANN) models for modelling risk allocation decision-making process in public-private partnership (PPP) projects, mainly drawing upon transaction cost economics. An industry-wide questionnaire survey was conducted to examine the risk allocation practice in PPP projects and collect the data for training the ANN models. The training and evaluation results, when compared with those of using traditional MLR modelling technique, show that the ANN models are satisfactory for modelling risk allocation decision-making process. The empirical evidence further verifies that it is appropriate to utilize transaction cost economics to interpret risk allocation decision-making process. It is recommended that, in addition to partners' risk management mechanism maturity level, decision-makers, both from public and private sectors, should also seriously consider influential factors including partner's risk management routines, partners' cooperation history, partners' risk management commitment, and risk management environmental uncertainty. All these factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects.

Active surface shaping for artificial skins

Artificial skins exhibit different mechanical properties in compare to natural skins. This drawback makes physical interaction with artificial skins to be different from natural skin. Increasing the performance of the artificial skins for robotic hands and medical applications is addressed in the present paper. The idea is to add active controls within artificial skins in order to improve their dynamic or static behaviors. This directly results into more interactivity of the artificial skins. To achieve this goal, a piece-wise linear anisotropic model for artificial skins is derived. Then a model of matrix of capacitive MEMS actuators for the control purpose is coupled with the model of artificial skin. Next an active surface shaping control is applied through the control of the capacitive MEMS actuators which shapes the skin with zero error and in a desired time. A simulation study is presented to validate the idea of using MEMS actuator for active artificial skins. In the simulation, we actively control 128 capacitive micro actuators for an artificial fingertip. The fingertip provides the required shape in a required time which means the dynamics of the skin is improved.

Detection of curved edges at subpixel accuracy using deformable models

One approach to the detection of curves at subpixel accuracy involves the reconstruction of such features from subpixel edge data points. A new technique is presented for reconstructing and segmenting curves with subpixel accuracy using deformable models. A curve is represented as a set of interconnected Hermite splines forming a snake generated from the subpixel edge information that minimizes the global energy functional integral over the set. While previous work on the minimization was mostly based on the Euler-Lagrange transformation, the authors use the finite element method to solve the energy minimization equation. The advantages of this approach over the Euler-Lagrange transformation approach are that the method is straightforward, leads to positive m-diagonal symmetric matrices, and has the ability to cope with irregular geometries such as junctions and corners. The energy functional integral solved using this method can also be used to segment the features by searching for the location of the maxima of the first derivative of the energy over the elementary curve set.

Hypothesis verification using parametric models and active vision strategies

This paper proposes a methodology for determining the shape and ultimately the functionality of objects from intensity images; 2D analytic functions are used to track 3D features during known camera motions. Three analytic functions are proposed that describe the relationship between pairs of points that are either stationary or moving depending on whether the points are on occluding boundaries or otherwise. Many of the problems of correspondence are reduced by using foveation, known camera motion, and active vision methods. The three analytic functions are shown to enable hypothesis refinement of the functionality of a number of 3D objects without full 3D information about the shape.

Spatial reasoning via active observation

This paper presents a model for space in which an autonomous agent acquires information about its environment. The agent uses a predefined exploration strategy to build a map allowing it to navigate and deduce relationships between points in space. The shapes of objects in the environment are represented qualitatively. This shape information is deduced from the agent's motion. Normally, in a qualitative model, directional information degrades under transitive deduction. By reasoning about the shape of the environment, the agent can match visual events to points on the objects. This strengthens the model by allowing further relationships to be deduced. In particular, points that are separated by long distances, or complex surfaces, can be related by line-of-sight. These relationships are deduced without incorporating any metric information into the model. Examples are given to demonstrate the use of the model.