Do androids dream of electric chimera?

This paper describes the use of the Chimera Architecture as the basis for a generative rhythmic improvisation system that is intended for use in ensemble contexts. This interactive soft- ware system learns in real time based on an audio input from live performers. The paper describes the components of the Chimera Architecture including a novel analysis engine that uses prediction to robustly assess the rhythmic salience of the input stream. Analytical results are stored in a hierarchical structure that includes multiple scenarios which allow ab- stracted and alternate interpretations of the current metrical context. The system draws upon this Chimera Architecture when generating a musical response. The generated rhythms are intended to have a particular ambiguity in relation to the music performance by other members of the ensemble. Ambi- guity is controlled through alternate interpretations of the Chimera. We describe an implementation of the Chimera Ar- chitecture that focuses on rhythmic material, and present and discuss initial experimental results of the software system playing along with recordings of a live performance.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

Design for Manufacturing (DFM) – A case study of repetitive measures

Design for Manufacturing (DFM) is a highly integral methodology in product development, starting from the concept development phase, with the aim of improving manufacturing productivity and maintaining product quality. While Design for Assembly (DFA) is focusing on elimination or combination of parts with other components (Boothroyd, Dewhurst and Knight, 2002), which in most cases relates to performing a function and manufacture operation in a simpler way, DFM is following a more holistic approach. During DFM, the considerable background work required for the conceptual phase is compensated for by a shortening of later development phases. Current DFM projects normally apply an iterative step-by-step approach and eventually transfer to the developer team. Although DFM has been a well established methodology for about 30 years, a Fraunhofer IAO study from 2009 found that DFM was still one of the key challenges of the German Manufacturing Industry. A new, knowledge based approach to DFM, eliminating steps of DFM, was introduced in Paul and Al-Dirini (2009). The concept focuses on a concurrent engineering process between the manufacturing engineering and product development systems, while current product realization cycles depend on a rigorous back-and-forth examine-and-correct approach so as to ensure compatibility of any proposed design to the DFM rules and guidelines adopted by the company. The key to achieving reductions is to incorporate DFM considerations into the early stages of the design process. A case study for DFM application in an automotive powertrain engineering environment is presented. It is argued that a DFM database needs to be interfaced to the CAD/CAM software, which will restrict designers to the DFM criteria. Consequently, a notable reduction of development cycles can be achieved. The case study is following the hypothesis that current DFM methods do not improve product design in a manner claimed by the DFM method. The critical case was to identify DFA/DFM recommendations or program actions with repeated appearance in different sources. Repetitive DFM measures are identified, analyzed and it is shown how a modified DFM process can mitigate a non-fully integrated DFM approach.

Optimal planning of electric-vehicle charging stations in distribution systems

With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

Observability analysis of electric networks considering branch impedance

This paper presents an analytical method to analyze the effect of X to R ratio as well as impedance value of branches on observability of a network based on un-decoupled formulation of state estimation (SE) and null space of matrices. The results showed that the X to R ratio of branches had no effect on the observability of networks. In addition, it was shown that observability of some networks was affected by impedance values while some others were not affected. In addition, for branch observability analysis of radial network, a simple and quick method is developed. Illustrative examples of the network under transmission and distribution voltages demonstrate the effectiveness of the proposed methods.

Clinical use of objective measures of physical activity

With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.

Proactive safety assessment in roadwork zones : a synthesis of surrogate measures of safety

Work zone safety studies have traditionally relied on historical crash records—an approach which is reactive in nature as it requires crashes to accumulate first before taking any preventive actions. However, detailed and accurate data on work zone crashes are often not available, as is the case for Australian road work zones. The lack of reliable safety records and the reactive nature of the crash-based safety analysis approach motivated this research to seek alternative and proactive measures of safety. Various surrogate measures of safety have been developed in the traffic safety literature including time to collision, time to accident, gap time, post encroachment time, required deceleration rate, proportion of stopping distances, lateral distance to departure, and time to departure. These measures express how close road-user(s) are from a potential crash by analysing their movement trajectories. A review of this fast-growing literature is presented in this paper from the viewpoint of applying the measures to untangle work zone safety issues. The review revealed that the use of the surrogate measures is very limited for analysing work zone safety, although numerous studies have used these measures for analysing safety in other parts of the road network, such as intersections and motorway ramps. There exist great opportunities for adopting this proactive safety assessment approach to transform work zone safety for both roadworkers and motorists.

On the (ir)relevance of rates of return measures of economic performance to small boats

A common measure of the economic performance of different fleet segments in fisheries is the rate of return on capital. However, in the English Channel (UK), observed changes in the fleet structure are at odds with expectations given the observed rates of return on capital. This disjunction between expected and observed behaviour raises the question as to the appropriateness of rate of return on capital as a measure of economic performance for small boats whose main input is often non-wage labour. In this paper, an alternative performance indicator is developed based on returns on owner-operator labour. This indicator appears to be of more relevance to small scale boats than the traditional returns on capital, and a better indicator of the direction of adjustment in the fishery.

Employee perceptions of alcohol and drug policy effectiveness: Policy features, concerns about drug testing, and the key role of preventative measures

As negative employee attitudes towards alcohol and other drug (AOD) policies may have serious consequences for organizations, the present study examined demographic and attitudinal dimensions leading to employees’ perceptions of AOD policy effectiveness. Survey responses were obtained from 147 employees in an Australian agricultural organization. Three dimensions of attitudes towards AOD policies were examined: knowledge of policy features, attitudes towards testing, and preventative measures such as job design and organizational involvement in community health. Demographic differences were identified, with males and blue-collar employees reporting significantly more negative attitudes towards the AOD policy. Attitude dimensions were stronger predictors of perceptions of policy effectiveness than demographics, and the strongest predictor was preventative measures. This suggests that organizations should do more than design adequate and fair AOD policies, and take a more holistic approach to AOD impairment by engaging in workplace design to reduce AOD use and promote a consistent health message to employees and the community.

Financially optimized scheduling of electric energy storage in presence of renewable energy resources

The increasing integration of Renewable Energy Resources (RER) and the role of Electric Energy Storage (EES) in distribution systems has created interest in using energy management strategies. EES has become a suitable resource to manage energy consumption and generation in smart grid. Optimize scheduling of EES can also maximize retailer’s profit by introducing energy time-shift opportunities. This paper proposes a new strategy for scheduling EES in order to reduce the impact of electricity market price and load uncertainty on retailers’ profit. The proposed strategy optimizes the cost of purchasing energy with the objective of minimizing surplus energy cost in hedging contract. A case study is provided to demonstrate the impact of the proposed strategy on retailers’ financial benefit.