At breaking point? Challenges for Australian film policy through the lens of genre (horror) films

Cultural policy settings attempting to foster the growth and development of the Australian feature film industry in era of globalisation are coming under increasing pressure. Global forces and emerging production and distribution models are challenging the “narrowness” of cultural policy – mandating a particular film culture, circumscribing certain notions of value and limiting the variety of films produced through cultural policy driven subvention models. Australian horror film production is an important case study. Horror films are a production strategy well suited to the financial limitations of the Australian film industry with competitive advantages for producers against international competitors. However, emerging within a “national” cinema driven by public subsidy and social/cultural objectives, horror films – internationally oriented with a low-culture status – have been severely marginalised within public funding environments. This paper introduces Australian horror film production, and examines the limitations of cultural policy, and the impacts of these questions for the Producer Offset.

Optimal mission path planning (MPP) for an air sampling unmanned aerial system

This paper presents advanced optimization techniques for Mission Path Planning (MPP) of a UAS fitted with a spore trap to detect and monitor spores and plant pathogens. The UAV MPP aims to optimise the mission path planning search and monitoring of spores and plant pathogens that may allow the agricultural sector to be more competitive and more reliable. The UAV will be fitted with an air sampling or spore trap to detect and monitor spores and plant pathogens in remote areas not accessible to current stationary monitor methods. The optimal paths are computed using a Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimisers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and Hybrid Game are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The trajectories on a three-dimension terrain, which are generated off-line, are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of coupling a Hybrid-Game strategy to a MOEA for MPP tasks. The reduction of numerical cost is an important point as the faster the algorithm converges the better the algorithms is for an off-line design and for future on-line decisions of the UAV.

The ceiling to coproduction in university-industry research collaboration

The purpose of this paper is to provide insight into government attempts at bridging the divide between theory and practice through university-industry research collaboration modelled under engaged scholarship. The findings are based on data sourced from interviews with 47 academic and industry project leaders from 23 large scale research projects. The paper demonstrates a ceiling to the coproduction of knowledge arising from the preconceived beliefs of both academics and industry partners regarding project roles and responsibilities. The findings show that coproduction was constrained by academic partners assuming control over much of the research activities and industry partners failing to confront or challenge academic decision-making because both academics and industry partners placed a higher value on academic knowledge compared with applied or practical knowledge. It is argued the theory of engaged scholarship, and consequent initiatives to encourage engaged scholarship, fail to account for the superior status of academic knowledge.

Comparative performance of Corymbia hybrids and parental species in subtropical Queensland and implications for breeding and deployment.

Eighty six full-sib Corymbia F1 hybrid families (crosses between C. torelliana and four spotted gum taxa: C. citriodora subsp. variegata, C. citriodora subsp. citriodora, C. henryi and C. maculata), were planted in six trials across six disparate sites in south-eastern Queensland to evaluate their productivity and determine their potential utility for plantation forestry. In each trial, the best-growing 20% of hybrid families grew significantly faster (P=0.05) than open-pollinated seedlots of the parent species Corymbia citriodora subsp. variegata, ranging from 107% to 181% and 127% to 287% of the height and diameter respectively. Relative performance of hybrid families growing on more than one site displayed consistency in ranking for growth across sites and analysis showed low genotype-by-environment interaction. Heritability estimates based on female and male parents across two sites at age six years for height and diameter at breast height, were high (0.62±0.28 to 0.64±0.35 and 0.31±0.21 to 0.69±0.37 respectively), and low to moderate (0.03±0.04 to 0.33±0.22) for stem straightness, branch size, incidence of ramicorns, and frost and disease resistance traits at ages one to three years. The proportion of dominance variance for height and diameter had reduced to zero by age six years. Based on these promising results, further breeding and pilot-scale family forestry and clonal forestry deployment is being undertaken. These results have also provided insights regarding the choice of a future hybrid breeding strategy.

R-parameter: A local truncation error based adaptive framework for finite volume compressible flow solvers

A residual-based strategy to estimate the local truncation error in a finite volume framework for steady compressible flows is proposed. This estimator, referred to as the -parameter, is derived from the imbalance arising from the use of an exact operator on the numerical solution for conservation laws. The behaviour of the residual estimator for linear and non-linear hyperbolic problems is systematically analysed. The relationship of the residual to the global error is also studied. The -parameter is used to derive a target length scale and consequently devise a suitable criterion for refinement/derefinement. This strategy, devoid of any user-defined parameters, is validated using two standard test cases involving smooth flows. A hybrid adaptive strategy based on both the error indicators and the -parameter, for flows involving shocks is also developed. Numerical studies on several compressible flow cases show that the adaptive algorithm performs excellently well in both two and three dimensions.

Alejandro E. Bunge : una visión de la Argentina

Resumen: El autor describe la concepción económica del Ingeniero Alejandro Bunge, quien se destacó como una de las personalidades con mayor capacidad visionaria en la Argentina de la primera mitad del siglo XX. Formado en la escuela histórica alemana, Bunge comprendió muy tempranamente la necesidad de una nueva orientación para la estrategia de desarrollo de nuestro país. Orientado por los objetivos de un conocimiento exhaustivo de la realidad nacional, una nueva estrategia productiva de sesgo agroindustrial y una amplia reforma social basada en los valores cristianos, Bunge trazó un camino que, según el autor, sigue siendo un desafío pendiente para la Argentina.

Real-Time Spatio-Temporal Query Processing in Mobile Ad-Hoc Sensor Networks

Personal communication devices are increasingly equipped with sensors that are able to collect and locally store information from their environs. The mobility of users carrying such devices, and hence the mobility of sensor readings in space and time, opens new horizons for interesting applications. In particular, we envision a system in which the collective sensing, storage and communication resources, and mobility of these devices could be leveraged to query the state of (possibly remote) neighborhoods. Such queries would have spatio-temporal constraints which must be met for the query answers to be useful. Using a simplified mobility model, we analytically quantify the benefits from cooperation (in terms of the system's ability to satisfy spatio-temporal constraints), which we show to go beyond simple space-time tradeoffs. In managing the limited storage resources of such cooperative systems, the goal should be to minimize the number of unsatisfiable spatio-temporal constraints. We show that Data Centric Storage (DCS), or "directed placement", is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, "amorphous placement", in which sensory samples are cached locally, and shuffling of cached samples is used to diffuse the sensory data throughout the whole network. We evaluate conditions under which directed versus amorphous placement strategies would be more efficient. These results lead us to propose a hybrid placement strategy, in which the spatio-temporal constraints associated with a sensory data type determine the most appropriate placement strategy for that data type. We perform an extensive simulation study to evaluate the performance of directed, amorphous, and hybrid placement protocols when applied to queries that are subject to timing constraints. Our results show that, directed placement is better for queries with moderately tight deadlines, whereas amorphous placement is better for queries with looser deadlines, and that under most operational conditions, the hybrid technique gives the best compromise.

Robust fuzzy Gustafson-Kessel clustering for nonlinear system identification

This paper deals with Takagi-Sugeno (TS) fuzzy model identification of nonlinear systems using fuzzy clustering. In particular, an extended fuzzy Gustafson-Kessel (EGK) clustering algorithm, using robust competitive agglomeration (RCA), is developed for automatically constructing a TS fuzzy model from system input-output data. The EGK algorithm can automatically determine the 'optimal' number of clusters from the training data set. It is shown that the EGK approach is relatively insensitive to initialization and is less susceptible to local minima, a benefit derived from its agglomerate property. This issue is often overlooked in the current literature on nonlinear identification using conventional fuzzy clustering. Furthermore, the robust statistical concepts underlying the EGK algorithm help to alleviate the difficulty of cluster identification in the construction of a TS fuzzy model from noisy training data. A new hybrid identification strategy is then formulated, which combines the EGK algorithm with a locally weighted, least-squares method for the estimation of local sub-model parameters. The efficacy of this new approach is demonstrated through function approximation examples and also by application to the identification of an automatic voltage regulation (AVR) loop for a simulated 3 kVA laboratory micro-machine system.

Optimierung von Betriebsstrategien für elektrifizierte Antriebskonzepte

Im Rahmen dieser Arbeit wird eine gemeinsame Optimierung der Hybrid-Betriebsstrategie und des Verhaltens des Verbrennungsmotors vorgestellt. Die Übernahme von den im Steuergerät verwendeten Funktionsmodulen in die Simulationsumgebung für Fahrzeuglängsdynamik stellt eine effiziente Applikationsmöglichkeit der Originalparametrierung dar. Gleichzeitig ist es notwendig, das Verhalten des Verbrennungsmotors derart nachzubilden, dass das stationäre und das dynamische Verhalten, inklusive aller relevanten Einflussmöglichkeiten, wiedergegeben werden kann. Das entwickelte Werkzeug zur Übertragung der in Ascet definierten Steurgerätefunktionen in die Simulink-Simulationsumgebung ermöglicht nicht nur die Simulation der relevanten Funktionsmodule, sondern es erfüllt auch weitere wichtige Eigenschaften. Eine erhöhte Flexibilität bezüglich der Daten- und Funktionsstandänderungen, sowie die Parametrierbarkeit der Funktionsmodule sind Verbesserungen die an dieser Stelle zu nennen sind. Bei der Modellierung des stationären Systemverhaltens des Verbrennungsmotors erfolgt der Einsatz von künstlichen neuronalen Netzen. Die Auswahl der optimalen Neuronenanzahl erfolgt durch die Betrachtung des SSE für die Trainings- und die Verifikationsdaten. Falls notwendig, wird zur Sicherstellung der angestrebten Modellqualität, das Interpolationsverhalten durch Hinzunahme von Gauß-Prozess-Modellen verbessert. Mit den Gauß-Prozess-Modellen werden hierbei zusätzliche Stützpunkte erzeugt und mit einer verminderten Priorität in die Modellierung eingebunden. Für die Modellierung des dynamischen Systemverhaltens werden lineare Übertragungsfunktionen verwendet. Bei der Minimierung der Abweichung zwischen dem Modellausgang und den Messergebnissen wird zusätzlich zum SSE das 2σ-Intervall der relativen Fehlerverteilung betrachtet. Die Implementierung der Steuergerätefunktionsmodule und der erstellten Steller-Sensor-Streckenmodelle in der Simulationsumgebung für Fahrzeuglängsdynamik führt zum Anstieg der Simulationszeit und einer Vergrößerung des Parameterraums. Das aus Regelungstechnik bekannte Verfahren der Gütevektoroptimierung trägt entscheidend zu einer systematischen Betrachtung und Optimierung der Zielgrößen bei. Das Ergebnis des Verfahrens ist durch das Optimum der Paretofront der einzelnen Entwurfsspezifikationen gekennzeichnet. Die steigenden Simulationszeiten benachteiligen Minimumsuchverfahren, die eine Vielzahl an Iterationen benötigen. Um die Verwendung einer Zufallsvariablen, die maßgeblich zur Steigerung der Iterationanzahl beiträgt, zu vermeiden und gleichzeitig eine Globalisierung der Suche im Parameterraum zu ermöglichen wird die entwickelte Methode DelaunaySearch eingesetzt. Im Gegensatz zu den bekannten Algorithmen, wie die Partikelschwarmoptimierung oder die evolutionären Algorithmen, setzt die neu entwickelte Methode bei der Suche nach dem Minimum einer Kostenfunktion auf eine systematische Analyse der durchgeführten Simulationsergebnisse. Mit Hilfe der bei der Analyse gewonnenen Informationen werden Bereiche mit den bestmöglichen Voraussetzungen für ein Minimum identifiziert. Somit verzichtet das iterative Verfahren bei der Bestimmung des nächsten Iterationsschrittes auf die Verwendung einer Zufallsvariable. Als Ergebnis der Berechnungen steht ein gut gewählter Startwert für eine lokale Optimierung zur Verfügung. Aufbauend auf der Simulation der Fahrzeuglängsdynamik, der Steuergerätefunktionen und der Steller-Sensor-Streckenmodelle in einer Simulationsumgebung wird die Hybrid-Betriebsstrategie gemeinsam mit der Steuerung des Verbrennungsmotors optimiert. Mit der Entwicklung und Implementierung einer neuen Funktion wird weiterhin die Verbindung zwischen der Betriebsstrategie und der Motorsteuerung erweitert. Die vorgestellten Werkzeuge ermöglichten hierbei nicht nur einen Test der neuen Funktionalitäten, sondern auch eine Abschätzung der Verbesserungspotentiale beim Verbrauch und Abgasemissionen. Insgesamt konnte eine effiziente Testumgebung für eine gemeinsame Optimierung der Betriebsstrategie und des Verbrennungsmotorverhaltens eines Hybridfahrzeugs realisiert werden.

Estrategia organizacional y su relación con la adopción de prácticas saludables

Las organizaciones asumen en el mundo en el que vivimos el reto de transformarse permanentemente para evolucionar y prolongarse en el tiempo, y una alternativa es a través de actividades dirigidas hacia los distintos grupos de interés y hacia la propia organización. Es así, como surge el interés de realizar este estudio analizando la estrategia, desde los conceptos de algunos pensadores representativos, las tipologías y modelos existentes, así como el concepto de organizaciones saludables, las cuales a través de prácticas saludables logran llevar a cabo acciones dirigidas hacia el bienestar de los empleados, el medio ambiente, proveedores, compradores, y la comunidad. Con el propósito de establecer la relación existente entre las prácticas saludables y la estrategia empresarial, se tienen en cuenta algunos estudios académicos y empíricos relacionados con la aplicación de las prácticas saludables para contribuir a la estrategia de la organización. Para estudiar dicha relación, se llevó a cabo un trabajo de campo en una empresa de salud tomando como muestra a 134 empleados de la organización. Los resultados arrojados señalan que tres de las cuatro prácticas saludables, a saber: plan de desarrollo, empleados, medio ambiente, no poseen una relación significativa con la estrategia, siendo la práctica referente a la comunidad, proveedores y compradores la más relacionada con ésta. Resulta importante continuar con otras investigaciones acerca del tema, con el fin de seguir analizando cómo las prácticas saludables están o no relacionadas con la estrategia de la organización.

Haploids in flowering plants: origins and exploitation

The first haploid angiosperm, a dwarf form of cotton with half the normal chromosome complement, was discovered in 1920, and in the ninety years since then such plants have been identified in many other species. They can occur either spontaneously or can be induced by modified pollination methods in vivo, or by in vitro culture of immature male or female gametophytes. Haploids represent an immediate, one-stage route to homozygous diploids and thence to F(1) hybrid production. The commercial exploitation of heterosis in such F(1) hybrids leads to the development of hybrid seed companies and subsequently to the GM revolution in agriculture. This review describes the range of techniques available for the isolation or induction of haploids and discusses their value in a range of areas, from fundamental research on mutant isolation and transformation, through to applied aspects of quantitative genetics and plant breeding. It will also focus on how molecular methods have been used recently to explore some of the underlying aspects of this fascinating developmental phenomenon.

Predictive control using feedback linearization based on dynamic neural models

This paper presents a hybrid control strategy integrating dynamic neural networks and feedback linearization into a predictive control scheme. Feedback linearization is an important nonlinear control technique which transforms a nonlinear system into a linear system using nonlinear transformations and a model of the plant. In this work, empirical models based on dynamic neural networks have been employed. Dynamic neural networks are mathematical structures described by differential equations, which can be trained to approximate general nonlinear systems. A case study based on a mixing process is presented.

Doubled haploid ramets via embryogenesis of haploid tissue cultures

Tissue culture in the oil palm business is generally concerned with the multiplication (clonal production) of dura, pisifera and tenera palms. These are all normal diploids (2n=2x=36). Sumatra Bioscience has pioneered haploid tissue culture of oil palm (n=x=18). Haploid oil palm is the first step in producing doubled haploid palms which in turn provide parental lines for F1 hybrid production. Chromosome doubling is known to occur during embryogenesis in other haploid cultures, e.g. barley anther culture. Haploid tissue cultures in oil palm were therefore set up to investigate and exploit spontaneous chromosome doubling during embryogenesis. Flow cytometry of embryogenic tissue showed the presence of both haploid (n) and doubled haploid (2n) cells indicating spontaneous doubling. Completely doubled haploid ramets were regenerated suggesting that doubling occurred during the first mitoses of embryogenesis. This is the first report of doubled haploid production in oil palm via haploid tissue culture. The method provides a means of producing a range of doubled haploids in oil palm from the 1,000 plus haploids available at Sumatra Bioscience, in addition the method also produced doubled haploid (and haploid) clones. 1.