A conceptualization of complexity in IS-driven organizational transformations

Organizational transformations reliant on successful ICT system developments (continue to) fail to deliver projected benefits even when contemporary governance models are applied rigorously. Modifications to traditional program, project and systems development management methods have produced little material improvement to successful transformation as they are unable to routinely address the complexity and uncertainty of dynamic alignment of IS investments and innovation. Complexity theory provides insight into why this phenomenon occurs and is used to develop a conceptualization of complexity in IS-driven organizational transformations. This research-in-progress aims to identify complexity formulations relevant to organizational transformation. Political/power based influences, interrelated business rules, socio-technical innovation, impacts on stakeholders and emergent behaviors are commonly considered as characterizing complexity while the proposed conceptualization accommodates these as connectivity, irreducibility, entropy and/or information gain in hierarchically approximation and scaling, number of states in a finite automata and/or dimension of attractor, and information and/or variety.

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Facilitating local stories in post-disaster regional communities : evaluation in narrative-driven oral history projects

Cyclone Yasi struck the Cassowary Coast of Northern Queensland, Australia, in the early hours of February 3, 2011, destroying many homes and property, including the destruction of the Cardwell and district historical society’s premises. With their own homes flattened, many residents were forced to live in mobile accommodation, with extended family, or leave the area altogether. The historical society members seemed, however, particularly devastated by their flattened foreshore museum and loss of their precious collection of material. A call for assistance was made through the Oral History Association of Australia’s Queensland branch (OHAA Qld), which along with a Queensland University of Technology (QUT) research team sponsored a trip to best plan how they could start to pick up the pieces to rebuild the museum. This chapter highlights the need for communities to gather, preserve and present their own stories, in a way that is sustainable and meaningful to them – whether that be because of a disaster, or as they go about life in their contemporary communities – the key being that good advice, professional support and embedded evaluation practices at crucial moments along the way can be critically important.

Exploring schema-driven differences in situation awareness between road users : an on-road study of driver, cyclist and motorcyclist situation awareness

Collisions between different road users make a substantial contribution to road trauma. Although evidence suggests that different road users interpret the same road situations differently, it is not clear how road users' situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study conducted to examine driver, motorcyclist and cyclist situation awareness in different road environments. The findings suggest that, in addition to minor differences in the structure of different road users' situation awareness (i.e. amount of information and how it is integrated), the actual content of situation awareness in terms of road user schemata, the resulting interaction with the world and the information underpinning situation awareness is markedly different. Further examination indicates that the differences are likely to be compatible along arterial roads, shopping strips and at roundabouts, but that they may create conflicts between different road users at intersections. Interventions designed to support compatible situation awareness and behaviour between different road users are discussed. Practitioner Summary: Incompatible situation awareness plays a key role in collisions between different road users (e.g. drivers and motorcyclists). This on-road study examined situation awareness in drivers, motorcyclists and cyclists, identifying the key differences and potential conflicts that arise. The findings are used to propose interventions designed to enhance the compatibility of situation awareness between road users.

A demand-responsive decision support system for coal transportation

In this paper, a demand-responsive decision support system is proposed by integrating the operations of coal shipment, coal stockpiles and coal railing within a whole system. A generic and flexible scheduling optimisation methodology is developed to identify, represent, model, solve and analyse the coal transport problem in a standard and convenient way. As a result, the integrated train-stockpile-ship timetable is created and optimised for improving overall efficiency of coal transport system. A comprehensive sensitivity analysis based on extensive computational experiments is conducted to validate the proposed methodology. The mathematical proposition and proof are concluded as technical and insightful advices for industry practice. The proposed methodology provides better decision making on how to assign rail rolling-stocks and upgrade infrastructure in order to significantly improve capacity utilisation with the best resource-effectiveness ratio. The proposed decision support system with train-stockpile-ship scheduling optimisation techniques is promising to be applied in railway or mining industry, especially as a useful quantitative decision making tool on how to use more current rolling-stocks or whether to buy additional rolling-stocks for mining transportation.

Is recovery driven by central or peripheral factors? A role for the brain in recovery following intermittent-sprint exercise

Prolonged intermittent-sprint exercise (i.e., team sports) induce disturbances in skeletal muscle structure and function that are associated with reduced contractile function, a cascade of inflammatory responses, perceptual soreness, and a delayed return to optimal physical performance. In this context, recovery from exercise-induced fatigue is traditionally treated from a peripheral viewpoint, with the regeneration of muscle physiology and other peripheral factors the target of recovery strategies. The direction of this research narrative on post-exercise recovery differs to the increasing emphasis on the complex interaction between both central and peripheral factors regulating exercise intensity during exercise performance. Given the role of the central nervous system (CNS) in motor-unit recruitment during exercise, it too may have an integral role in post-exercise recovery. Indeed, this hypothesis is indirectly supported by an apparent disconnect in time-course changes in physiological and biochemical markers resultant from exercise and the ensuing recovery of exercise performance. Equally, improvements in perceptual recovery, even withstanding the physiological state of recovery, may interact with both feed-forward/feed-back mechanisms to influence subsequent efforts. Considering the research interest afforded to recovery methodologies designed to hasten the return of homeostasis within the muscle, the limited focus on contributors to post-exercise recovery from CNS origins is somewhat surprising. Based on this context, the current review aims to outline the potential contributions of the brain to performance recovery after strenuous exercise.

Regulating virtual worlds : considering participant-driven approaches

There are a number of pressing issues facing contemporary online environments that are causing disputes among participants and platform operators and increasing the likelihood of external regulation. A number of solutions have been proposed, including industry self-governance, top-down regulation and emergent self-governance such as EVE Online’s “Council of Stellar Management”. However, none of these solutions seem entirely satisfying; facing challenges from developers who fear regulators will not understand their platforms, or players who feel they are not sufficiently empowered to influence the platform, while many authors have raised concerns over the implementation of top-down regulation, and why the industry may be well-served to pre-empt such action. This paper considers case studies of EVE Online and the offshore gambling industry, and whether a version of self-governance may be suitable for the future of the industry.

Demand response for residential appliances via Customer Reward Scheme

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.

Tuning the surface structure of nitrogen-doped TiO2Nanofibres : an effective method to rnhance photocatalytic activities of visible-light-driven green synthesis and degradation

Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.

Numerical study of lid-driven square cavity with heat generation using LBM

In this study, the mixed convection heat transfer and fluid flow behaviors in a lid-driven square cavity filled with high Prandtl number fluid (Pr = 5400, ν = 1.2×10-4 m2/s) at low Reynolds number is studied using thermal Lattice Boltzmann method (TLBM) where ν is the viscosity of the fluid. The LBM has built up on the D2Q9 model and the single relaxation time method called the Lattice-BGK (Bhatnagar-Gross-Krook) model. The effects of the variations of non dimensional mixed convection parameter called Richardson number(Ri) with and without heat generating source on the thermal and flow behavior of the fluid inside the cavity are investigated. The results are presented as velocity and temperature profiles as well as stream function and temperature contours for Ri ranging from 0.1 to 5.0 with other controlling parameters that present in this study. It is found that LBM has good potential to simulate mixed convection heat transfer and fluid flow problem. Finally the simulation results have been compared with the previous numerical and experimental results and it is found to be in good agreement.

Retailer-driven agricultural restructuring - Australia, the UK and Norway in comparison

In recent decades, the governance of food safety, food quality, on-farm environmental management and animal welfare has been shifting from the realm of 'the government' to that of the private sector. Corporate entities, especially the large supermarkets, have responded to neoliberal forms of governance and the resultant 'hollowed-out' state by instituting private standards for food, backed by processes of certification and policed through systems of third party auditing. Today's food regime is one in which supermarkets impose 'private standards' along the food supply chain to ensure compliance with a range of food safety goals-often above and beyond those prescribed by government. By examining regulatory governance in Australia, Norway and the United Kingdom we highlight emerging trajectories of food governance. We argue that the imposition of the new private forms of monitoring and compliance continue the project of agricultural restructuring that began with government support for structural adjustment schemes in agriculture and that these are most evident in the UK and Australia where neoliberalism is an entrenched philosophy. However, despite Norway's identity as a social democracy, we also identify neoliberal 'creep' into the system of food governance. Small-scale producers in all three nations are finding themselves increasingly subject to governance through private, market-based mechanisms that, to varying degrees, are dominated by major supermarket chains. The result is agricultural restructuring not through the traditional avenues of elected governments, but via non-elected market operatives.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.