983 resultados para Multi-robot cooperation


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Pratylenchus thornei is a root-lesion nematode (RLN) of economic significance in the grain growing regions of Australia. Chickpea (Cicer arietinum) is a significant legume crop grown throughout these regions, but previous testing found most cultivars were susceptible to P. thornei. Therefore, improved resistance to P. thornei is an important objective of the Australian chickpea breeding program. A glasshouse method was developed to assess resistance of chickpea lines to P. thornei, which requires relatively low labour and resource input, and hence is suited to routine adoption within a breeding program. Using this method, good differentiation of chickpea cultivars for P. thornei resistance was measured after 12 weeks. Nematode multiplication was higher for all genotypes than the unplanted control, but of the 47 cultivars and breeding lines tested, 17 exhibited partial resistance, allowing less than two fold multiplication. The relative differences in resistance identified using this method were highly heritable (0.69) and were validated against P. thornei data from seven field trials using a multi-environment trial analysis. Genetic correlations for cultivar resistance between the glasshouse and six of the field trials were high (>0.73). These results demonstrate that resistance to P. thornei in chickpea is highly heritable and can be effectively selected in a limited set of environments. The improved resistance found in a number of the newer chickpea cultivars tested shows that some advances have been made in the P. thornei resistance of Australian chickpea cultivars, and that further targeted breeding and selection should provide incremental improvements.

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A new automata model Mr,k, with a conceptually significant innovation in the form of multi-state alternatives at each instance, is proposed in this study. Computer simulations of the Mr,k, model in the context of feature selection in an unsupervised environment has demonstrated the superiority of the model over similar models without this multi-state-choice innovation.

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Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

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Background Malnutrition and unintentional weight loss are major clinical issues in people with dementia living in residential aged care facilities (RACFs) and are associated with serious adverse outcomes. However, evidence regarding effective interventions is limited and strategies to improve the nutritional status of this population are required. This presentation describes the implementation and results of a pilot randomised controlled trial of a multi-component intervention for improving the nutritional status of RACF residents with dementia. Method Fifteen residents with moderate-severe dementia living in a secure long-term RACF participated in a five week pilot study. Participants were randomly allocated to either an Intervention (n=8) or Control group (n=7). The intervention comprised four elements delivered in a separate dining room at lunch and dinner: the systematic reinforcement of residents’ eating behaviors using a specific communication protocol; family-style dining; high ambiance table presentation; and routine Dietary-Nutrition Champion supervision. Control group participants ate their meals according to the facility’s standard practice. Baseline and follow-up assessments of nutritional status, food consumption, and body mass index were obtained by qualified nutritionists. Additional assessments included measures of cognitive functioning, mealtime agitation, depression, wandering status and multiple measures of intervention fidelity. Results No participant was malnourished at study commencement and participants in both groups gained weight from follow-up to baseline which was not significantly different between groups (t=0.43; p=0.67). A high degree of treatment fidelity was evident throughout the intervention. Qualitative data from staff indicate the intervention was perceived to be beneficial for residents. Conclusions This multi-component nutritional intervention was well received and was feasible in the RACF setting. Participants’ sound nutritional status at baseline likely accounts for the lack of an intervention effect. Further research using this protocol in malnourished residents is recommended. For success, a collaborative approach between researchers and facility staff, particularly dietary staff, is essential.

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The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.

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In order to fully understand the process of European integration it is of paramount importance to consider developments at the sub-national and local level. EU integration scholars shifted their attention to the local level only at the beginning of the 1990s with the concept of multi-level governance (MLG). While MLG is the first concept to scrutinise the position of local levels of public administration and other actors within the EU polity, I perceive it as too optimistic in the degree of influence it ascribes to local levels. Thus, learning from and combining MLG with other concepts, such as structural constructivism, helps to reveal some of the hidden aspects of EU integration and paint a more realistic picture of multi-level interaction. This thesis also answers the call for more case studies in order to conceptualise MLG further. After a critical study of theories and concepts of European integration, above all, MLG, I will analyse sub-national and local government in Finland and Germany. I show how the sub-national level and local governments are embedded in the EU s multi-level structure of governance and how, through EU integration, those levels have been empowered but also how their scope of action has partially decreased. After theoretical and institutional contextualisation, I present the results of my empirical study of the EU s Community Initiative LEADER+. LEADER stands for Liaison Entre Actions de Développement de l'Économie Rurale , and aims at improving the economic conditions in Europe s rural areas. I was interested in how different actors construct and shape EU financed rural development, especially in how local actors organised in so-called local action groups (LAGs) cooperate with other administrative units within the LEADER+ administrative chain. I also examined intra-institutional relations within those groups, in order to find out who are the most influential and powerful actors within them. Empirical data on the Finnish and German LAGs was first gathered through a survey, which was then supplemented and completed by interviewing LAG members, LAG-managers, several civil servants from Finnish and German decision-making and managing authorities and a civil servant from the EU Commission. My main argument is that in both Germany and Finland, the Community Initiative LEADER+ offered a space for multi-level interaction and local-level involvement, a space that on the one hand consists of highly motivated people actively contributing to the improvement of the quality of life and economy in Europe s countryside but which is dependent and also restricted by national administrative practices, implementation approaches and cultures on the other. In Finland, the principle of tri-partition (kolmikantaperiaatte) in organising the executive committees of LAGs is very noticeable. In comparison to Germany, for instance, the representation of public administration in those committees is much more limited due to this principle. Furthermore, the mobilisation of local residents and the bringing together of actors from the local area with different social and institutional backgrounds to become an active part of LEADER+ was more successful in Finland than in Germany. Tri-partition as applied in Finland should serve as a model for similar policies in other EU member states. EU integration changed the formal and informal inter-institutional relations linking the different levels of government. The third sector including non-governmental institutions and interest groups gained access to policy-making processes and increasingly interact with government institutions at all levels of public administration. These developments do not necessarily result in the empowering of the local level.

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This paper proposes a new multi-stage mine production timetabling (MMPT) model to optimise open-pit mine production operations including drilling, blasting and excavating under real-time mining constraints. The MMPT problem is formulated as a mixed integer programming model and can be optimally solved for small-size MMPT instances by IBM ILOG-CPLEX. Due to NP-hardness, an improved shifting-bottleneck-procedure algorithm based on the extended disjunctive graph is developed to solve large-size MMPT instances in an effective and efficient way. Extensive computational experiments are presented to validate the proposed algorithm that is able to efficiently obtain the near-optimal operational timetable of mining equipment units. The advantages are indicated by sensitivity analysis under various real-life scenarios. The proposed MMPT methodology is promising to be implemented as a tool for mining industry because it is straightforwardly modelled as a standard scheduling model, efficiently solved by the heuristic algorithm, and flexibly expanded by adopting additional industrial constraints.

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This paper reviews the recent research progress on multi-layer composite structures composed of variety of materials. The utilization of multi-layer composite system is found to be common in metal structures and pavement systems. The layer of composite structure designed to encounter heavy dynamic energy should have sufficient ductility to counteract the intensity of energy. Therefore, the selection of materials and enhancement of interface bonding become crucial and both are discussed in this paper. The failure modes have also been explored in conjunction with stresses at failures and inferred solutions are also revealed. The paper attempts to reveal all technical facts on multi-layer composite structure in a broad field.

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In this paper a strategy for controlling a group of agents to achieve positional consensus is presented. The proposed technique is based on the constraint that every agents must be given the same control input through a broadcast communication mechanism. Although the control command is computed using state information in a global framework, the control input is implemented by the agents in a local coordinate frame. We propose a novel linear programming formulation that is computationally less intensive than earlier proposed methods. Moreover, we introduce a random perturbation input in the control command that helps us to achieve perfect consensus even for a large number of agents, which was not possible with the existing strategy in the literature. Moreover, we extend the method to achieve positional consensus at a pre-specified location. The effectiveness of the approach is illustrated through simulation results.

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Taking a more integrated approach to planning our neighbourhoods for the continuum of inhabitants’ ages and abilities makes sense given our current and future population composition. Seldom are the built environment requirements of diverse groups (e.g. children, seniors, and people with disability) synthesised, resulting in often unfriendly and exclusionary neighbourhoods. This often means people experience barriers or restriction on their freedom to move about and interact within their neighbourhood. Applying universal design to neighbourhoods may provide a bridging link. By presenting two cases from South-East Queensland (SEQ), Australia, through the lenses of different ages and abilities - older children with physical disabilities and their families (Stafford 2013, 2014) and seniors (Baldwin et al. 2012), we intend to increase recognition of users' needs and stimulate the translation of knowledge to the practice of planning inclusive neighbourhoods.

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Abstract is not available.

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The surface water waves are "modal" waves in which the "physical space" (t, x, y, z) is the product of a propagation space (t, x, y) and a cross space, the z-axis in the vertical direction. We have derived a new set of equations for the long waves in shallow water in the propagation space. When the ratio of the amplitude of the disturbance to the depth of the water is small, these equations reduce to the equations derived by Whitham (1967) by the variational principle. Then we have derived a single equation in (t, x, y)-space which is a generalization of the fourth order Boussinesq equation for one-dimensional waves. In the neighbourhood of a wave froat, this equation reduces to the multidimensional generalization of the KdV equation derived by Shen & Keller (1973). We have also included a systematic discussion of the orders of the various non-dimensional parameters. This is followed by a presentation of a general theory of approximating a system of quasi-linear equations following one of the modes. When we apply this general method to the surface water wave equations in the propagation space, we get the Shen-Keller equation.

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Insulin receptor (IR) signaling is critical to controlling nutrient uptake and metabolism. However, only a low-resolution (3.8 Å) structure currently exists for the IR ectodomain, with some segments ill-defined or unmodeled due to disorder. Here, we revise this structure using new diffraction data to 3.3 Å resolution that allow improved modeling of the N-linked glycans, the first and third fibronectin type III domains, and the insert domain. A novel haptic interactive molecular dynamics strategy was used to aid fitting to low-resolution electron density maps. The resulting model provides a foundation for investigation of structural transitions in IR upon ligand binding.

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There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.