890 resultados para Time Trade Off


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Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.

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Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

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Using analysis-by-synthesis (AbS) approach, we develop a soft decision based switched vector quantization (VQ) method for high quality and low complexity coding of wideband speech line spectral frequency (LSF) parameters. For each switching region, a low complexity transform domain split VQ (TrSVQ) is designed. The overall rate-distortion (R/D) performance optimality of new switched quantizer is addressed in the Gaussian mixture model (GMM) based parametric framework. In the AbS approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (NN) TrSVQs and splitting the transform domain vector into higher number of subvectors. Compared to the current LSF quantization methods, the new method is shown to provide competitive or better trade-off between R/D performance and complexity.

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Reef-building corals are an example of plastic photosynthetic organisms that occupy environments of high spatiotemporal variations in incident irradiance. Many phototrophs use a range of photoacclimatory mechanisms to optimize light levels reaching the photosynthetic units within the cells. In this study, we set out to determine whether phenotypic plasticity in branching corals across light habitats optimizes potential light utilization and photosynthesis. In order to do this, we mapped incident light levels across coral surfaces in branching corals and measured the photosynthetic capacity across various within-colony surfaces. Based on the field data and modelled frequency distribution of within-colony surface light levels, our results show that branching corals are substantially self-shaded at both 5 and 18 m, and the modal light level for the within-colony surface is 50 mu mol photons m(-2) s(-1). Light profiles across different locations showed that the lowest attenuation at both depths was found on the inner surface of the outermost branches, while the most self-shading surface was on the bottom side of these branches. In contrast, vertically extended branches in the central part of the colony showed no differences between the sides of branches. The photosynthetic activity at these coral surfaces confirmed that the outermost branches had the greatest change in sun- and shade-adapted surfaces; the inner surfaces had a 50 % greater relative maximum electron transport rate compared to the outer side of the outermost branches. This was further confirmed by sensitivity analysis, showing that branch position was the most influential parameter in estimating whole-colony relative electron transport rate (rETR). As a whole, shallow colonies have double the photosynthetic capacity compared to deep colonies. In terms of phenotypic plasticity potentially optimizing photosynthetic capacity, we found that at 18 m, the present coral colony morphology increased the whole-colony rETR, while at 5 m, the colony morphology decreased potential light utilization and photosynthetic output. This result of potential energy acquisition being underutilized in shallow, highly lit waters due to the shallow type morphology present may represent a trade-off between optimizing light capture and reducing light damage, as this type morphology can perhaps decrease long-term costs of and effect of photoinhibition. This may be an important strategy as opposed to adopting a type morphology, which results in an overall higher energetic acquisition. Conversely, it could also be that maximizing light utilization and potential photosynthetic output is more important in low-light habitats for Acropora humilis.

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In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

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Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

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The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

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In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

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A now procedure for the design of sensitivity-reduced control for linear regulators is described. The control is easily computable and implementable since it requires neither the solution of an increased-order augmented system nor the generation and feedback of a trajectory sensitivity vector. The method provides a trade-off between reduction in sensitivity measure and increase in performance index.

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This dissertation consists of an introductory section and three essays investigating the effects of economic integration on labour demand by using theoretical models and by empirical analysis. The essays adopt an intra-industry trade approach to specify a theoretical framework of estimation for determining the effects of economic integration on employment. In all the essays the empirical aim is to explore the labour demand consequences of European integration. The first essay analyzes how labour-demand elasticities with own price have changed during the process of economic integration. As a theoretical result, intensified trade competition increases labour-demand elasticity, whereas better advantage of economies of scale decreases labour-demand elasticity by decreasing the elasticity of substitution between differentiated products. Furthermore, if integration gives rise to an increase in input-substitutability and/or outsourcing activities, labour demand will become more elastic. Using data from the manufacturing sector from 1975 to 2002, the empirical results provide support for the hypothesis that European integration has contributed to increased elasticities of total labour demand in Finland. The second essay analyzes how economic integration affects the impact of welfare poli-cies on employment. The essay considers the viability of financing the public sector, i.e. public consumption and social security expenses, by general labour taxation in an economy which has become more integrated into international product markets. The theoretical results of the second essay indicate that, as increased trade competition crowds out better economies of scale, it becomes more costly to maintain welfare systems financed by labour taxation. Using data from European countries for the years 1975 to 2004, the empirical results provide inconsistent evidence for the hypothesis that economic integration has contributed to the distortion effects of welfare policies on employment. The third essay analyzes the impact of profit sharing on employment as a way to introduce wage flexibility into the process of economic integration. The results of the essay suggest that, in theory, the effects of economic integration on the impact of profit sharing on employment clearly depend on a trade-off between intensified competition and better advantage of economies of scale. If product market competition increases, the ability of profit sharing to improve employment through economic integration increases with moderated wages. While, the economic integration associating with market power in turn decrease the possibilities of profit sharing with higher wages to improve employment. Using data from the manufacturing sector for the years 1996 to 2004, the empirical results show that profit-sharing has a positive impact on employment during the process of European integration, but can have ambiguous effects on the stability of employment in Finland.

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Objective The objectives of this study were to investigate (1) the attitudes and behaviours of Australian consumers in antibiotic use, and (2) their understanding of antibiotic resistance. Methods Semi-structured interviews were conducted with consumers in May/June 2015. Convenience sampling was used to recruit consumers between 18–54 years old. Thirty-two consumers were interviewed. Transcripts were analysed to identify themes. Lessons Learned Dominant themes for attitudes and behaviours regarding antibiotics were (a) avoidance of antibiotic use unless clinically warranted; (b) antibiotics were useful but “weakened the body”; and (c) use of complementary medicines as adjuncts to antibiotics or to strengthen the immune system. Key information needs were (a) unambiguous instructions from GPs when prescribed antibiotics, to avoid inappropriate medicine-taking behaviour; (b) rationale for antibiotic selection; and (c) treatment duration. Antibiotic resistance was conceptualised in three ways: as a property of the body (body becomes resistant to antibiotics); the medication (antibiotic no longer effective); and the bacteria (bacteria is resistant). Antibiotic resistance was perceived as an issue that would only affect the wider community in the future, although most recognised that it is a current challenge for hospitals. Personal good health and/or avoidance of antibiotics were perceived as insurance against being adversely affected by antibiotic resistance. Implications A structured survey (discrete choice experiment) will be developed from these findings to investigate how consumers trade-off on factors influencing antibiotic use. Public health campaigns promoting conservation of antibiotics can benefit from these findings.

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Productivity is predicted to drive the ecological and evolutionary dynamics of predator-prey interaction through changes in resource allocation between different traits. However, resources are seldom constantly available and thus temporal variation in productivity could have considerable effect on the species' potential to evolve. To study this, three long-term microbial laboratory experiments were established where Serratia marcescens prey bacteria was exposed to predation of protist Tetrahymena thermophila in different prey resource environments. The consequences of prey resource availability for the ecological properties of the predator-prey system, such as trophic dynamics, stability, and virulence, were determined. The evolutionary changes in species traits and prey genetic diversity were measured. The prey defence evolved stronger in high productivity environment. Increased allocation to defence incurred cost in terms of reduced prey resource use ability, which probably constrained prey evolution by increasing the effect of resource competition. However, the magnitude of this trade-off diminished when measured in high resource concentrations. Predation selected for white, non-pigmented, highly defensive prey clones that produced predation resistant biofilm. The biofilm defence was also potentially accompanied with cytotoxicity for predators and could have been traded off with high motility. Evidence for the evolution of predators was also found in one experiment suggesting that co-evolutionary dynamics could affect the evolution and ecology of predator-prey interaction. Temporal variation in resource availability increased variation in predator densities leading to temporally fluctuating selection for prey defences and resource use ability. Temporal variation in resource availability was also able to constrain prey evolution when the allocation to defence incurred high cost. However, when the magnitude of prey trade-off was small and the resource turnover was periodically high, temporal variation facilitated the formation of predator resistant biofilm. The evolution of prey defence constrained the transfer of energy from basal to higher trophic levels, decreasing the strength of top-down regulation on prey community. Predation and temporal variation in productivity decreased the stability of populations and prey traits in general. However, predation-induced destabilization was less pronounced in the high productivity environment where the evolution of prey defence was stronger. In addition, evolution of prey defence weakened the environmental variation induced destabilization of predator population dynamics. Moreover, protozoan predation decreased the S. marcescens virulence in the insect host moth (Parasemia plantaginis) suggesting that species interactions outside the context of host-pathogen relationship could be important indirect drivers for the evolution of pathogenesis. This thesis demonstrates that rapid evolution can affect various ecological properties of predator-prey interaction. The effect of evolution on the ecological dynamics depended on the productivity of the environment, being most evident in the constant environments with high productivity.

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Defence against pathogens is a vital need of all living organisms that has led to the evolution of complex immune mechanisms. However, although immunocompetence the ability to resist pathogens and control infection has in recent decades become a focus for research in evolutionary ecology, the variation in immune function observed in natural populations is relatively little understood. This thesis examines sources of this variation (environmental, genetic and maternal effects) during the nestling stage and its fitness consequences in wild populations of passerines: the blue tit (Cyanistes caeruleus) and the collared flycatcher (Ficedula albicollis). A developing organism may face a dilemma as to whether to allocate limited resources to growth or to immune defences. The optimal level of investment in immunity is shaped inherently by specific requirements of the environment. If the probability of contracting infection is low, maintaining high growth rates even at the expense of immune function may be advantageous for nestlings, as body mass is usually a good predictor of post-fledging survival. In experiments with blue tits and haematophagous hen fleas (Ceratophyllus gallinae) using two methods, methionine supplementation (to manipulate nestlings resource allocation to cellular immune function) and food supplementation (to increase resource availability), I confirmed that there is a trade-off between growth and immunity and that the abundance of ectoparasites is an environmental factor affecting allocation of resources to immune function. A cross-fostering experiment also revealed that environmental heterogeneity in terms of abundance of ectoparasites may contribute to maintaining additive genetic variation in immunity and other traits. Animal model analysis of extensive data collected from the population of collared flycatchers on Gotland (Sweden) allowed examination of the narrow-sense heritability of PHA-response the most commonly used index of cellular immunocompetence in avian studies. PHA-response is not heritable in this population, but is subject to a non-heritable origin (presumably maternal) effect. However, experimental manipulation of yolk androgen levels indicates that the mechanism of the maternal effect in PHA-response is not in ovo deposition of androgens. The relationship between PHA-response and recruitment was studied for over 1300 collared flycatcher nestlings. Multivariate selection analysis shows that it is body mass, not PHA-response, that is under direct selection. PHA-response appears to be related to recruitment because of its positive relationship with body mass. These results imply that either PHA-response fails to capture the immune mechanisms that are relevant for defence against pathogens encountered by fledglings or that the selection pressure from parasites is not as strong as commonly assumed.

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In aquatic systems, the ability of both the predator and prey to detect each other may be impaired by turbidity. This could lead to significant changes in the trophic interactions in the food web of lakes. Most fish use their vision for predation and the location of prey can be highly influenced by light level and clarity of the water environment. Turbidity is an optical property of water that causes light to be scattered and absorbed by particles and molecules. Turbidity is highly variable in lakes, due to seasonal changes in suspended sediments, algal blooms and wind-driven suspension of sediments especially in shallow waters. There is evidence that human activity has increased erosion leading to increased turbidity in aquatic systems. Turbidity could also play a significant role in distribution of fish. Turbidity could act as a cover for small fish and reduce predation risk. Diel horizontal migration by fish is common in shallow lakes and is considered as consequences of either optimal foraging behaviour for food or as a trade-off between foraging and predator avoidance. In turbid lakes, diel horizontal migration patterns could differ since turbidity can act as a refuge itself and affect the predator-prey interactions. Laboratory experiments were conducted with perch (Perca fluviatilis L.) and white bream (Abramis björkna (L.)) to clarify the effects of turbidity on their feeding. Additionally to clarify the effects of turbidity on predator preying on different types of prey, pikeperch larvae (Sander lucioperca (L.)), Daphnia pulex (Leydig), Sida crystallina (O.F. Müller), and Chaoborus flavicans (Meigen) were used as prey in different experiments. To clarify the role of turbidity in distribution and diel horizontal migration of perch, roach (Rutilus rutilus (L.)) and white bream, field studies were conducted in shallow turbid lakes. A clear and a turbid shallow lake were compared to investigate distribution of perch and roach in these two lakes in a 15-year study period. Feeding efficiency of perch and white bream was not significantly affected with increasing clay turbidity up to 50 NTU. The perch experiments with pikeperch larvae suggested that clay turbidity could act as a refuge especially at turbidity levels higher than 50 NTU. Perch experiments with different prey types suggested that pikeperch larvae probably use turbidity as a refuge better compared to Daphnia. Increase in turbidity probably has stronger affect on perch predating on plant-attached prey. The main findings of the thesis show that turbidity can play a significant role in distribution of fish. Perch and roach could use turbidity as refuge when macrophytes disappear while small perch may also use high turbidity as refuge when macrophytes are present. Floating-leaved macrophytes are probably good refuges for small fish in clay-turbid lakes and provide a certain level of turbidity and not too complex structure for refuge. The results give light to the predator-prey interactions in turbid environments. Turbidity of water should be taken in to account when studying the diel horizontal migrations and distribution of fish in shallow lakes.

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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.