958 resultados para Computer-driven foot
Resumo:
An estimate of the irrigation potential over and above the existing utilization was made based on the ground water potential in the Vedavati river basin. The estimate is based on assumed crops and cropping patterns as per existing practice in the various taluks of the basin. Irrigation potential was estimated talukwise based on the available ground water potential identified from the simulation study. It is estimated that 84,100 hectares of additional land can be brought under irrigation from ground water in the entire basin.
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The probable modes of binding of some complex carbohydrates, which have the trimannosidic core structure (Man3GlcNAc2), to concanavalin A (Con A) have been determined using a computer modelling technique. These studies show that Con a can bind to the terminal mannose residues of the trimannosidic core structure and to the internal mannosyl as well as to the terminal N-acetylglucosamine residues of the N-acetylglucosamine substituted trimannosidic core structure. The oligosaccharide with terminal mannose residues can bind in its minimum energy conformers, whereas the oligosaccharide with internal mannosyl and terminal N-acetylglucosamine residues can bind only in higher energy conformers. In addition the former oligosaccharide forms more hydrogen bonds with Con A than the latter. These results suggest that, for these oligosaccharides, the terminal mannose residue has a much higher probability of reaching the binding site than either the internal mannosyl or the terminal N-acetylglucosamine residues. The substitution of a bisecting N-acetylglucosamine residue on these oligosaccharides, affects significantly the accessibility of the residues which bind to Con A and thereby reduces their binding affinity. It thus seems that the binding affinity of an oligosaccharide to Con A depends not only on the number of sugar residues which possess free 3-, 4- and 6-hydroxyl groups but also on the accessibility of these sugar residues to Con A. This study also reveals that the sugar binding site of Con A is small and that the interactions between Con A and carbohydrates are extended slightly beyond the single sugar residue that is placed in the binding site.
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Data flow computers are high-speed machines in which an instruction is executed as soon as all its operands are available. This paper describes the EXtended MANchester (EXMAN) data flow computer which incorporates three major extensions to the basic Manchester machine. As extensions we provide a multiple matching units scheme, an efficient, implementation of array data structure, and a facility to concurrently execute reentrant routines. A simulator for the EXMAN computer has been coded in the discrete event simulation language, SIMULA 67, on the DEC 1090 system. Performance analysis studies have been conducted on the simulated EXMAN computer to study the effectiveness of the proposed extensions. The performance experiments have been carried out using three sample problems: matrix multiplication, Bresenham's line drawing algorithm, and the polygon scan-conversion algorithm.
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Socio-economic and demographic changes among family forest owners and demands for versatile forestry decision aid motivated this study, which sought grounds for owner-driven forest planning. Finnish family forest owners’ forest-related decision making was analyzed in two interview-based qualitative studies, the main findings of which were surveyed quantitatively. Thereafter, a scheme for adaptively mixing methods in individually tailored decision support processes was constructed. The first study assessed owners’ decision-making strategies by examining varying levels of the sharing of decision-making power and the desire to learn. Five decision-making modes – trusting, learning, managing, pondering, and decisive – were discerned and discussed against conformable decision-aid approaches. The second study conceptualized smooth communication and assessed emotional, practical, and institutional boosters of and barriers to such smoothness in communicative decision support. The results emphasize the roles of trust, comprehension, and contextual services in owners’ communicative decision making. In the third study, a questionnaire tool to measure owners’ attitudes towards communicative planning was constructed by using trusting, learning, and decisive dimensions. Through a multivariate analysis of survey data, three owner groups were identified as fusions of the original decision-making modes: trusting learners (53%), decisive learners (27%), and decisive managers (20%). Differently weighted communicative services are recommended for these compound wishes. The findings of the studies above were synthesized in a form of adaptive decision analysis (ADA), which allows and encourages the decision-maker (owner) to make deliberate choices concerning the phases of a decision aid (planning) process. The ADA model relies on adaptability and feedback management, which foster smooth communication with the owner and (inter-)organizational learning of the planning institution(s). The summarized results indicate that recognizing the communication-related amenity values of family forest owners may be crucial in developing planning and extension services. It is therefore recommended that owners, root-level planners, consultation professionals, and pragmatic researchers collaboratively continue to seek stable change.
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There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.
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This work deals with the formulation and implementation of finite deformation viscoplasticity within the framework of stress-based hybrid finite element methods. Hybrid elements, which are based on a two-field variational formulation, are much less susceptible to locking than conventional displacement-based elements. The conventional return-mapping scheme cannot be used in the context of hybrid stress methods since the stress is known, and the strain and the internal plastic variables have to be recovered using this known stress field.We discuss the formulation and implementation of the consistent tangent tensor, and the return-mapping algorithm within the context of the hybrid method. We demonstrate the efficacy of the algorithm on a wide range of problems.
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A parentheses-free code is suggested for the description of two-terminal electrical networks for computer analysis.
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A recent report to the Australian Government identified concerns relating to Australia's capacity to respond to a medium to large outbreak of FMD. To assess the resources required, the AusSpread disease simulation model was used to develop a plausible outbreak scenario that included 62 infected premises in five different states at the time of detection, 28 days after the disease entered the first property in Victoria. Movements of infected animals and/or contaminated product/equipment led to smaller outbreaks in NSW, Queensland, South Australia and Tasmania. With unlimited staff resources, the outbreak was eradicated in 63 days with 54 infected premises and a 98% chance of eradication within 3 months. This unconstrained response was estimated to involve 2724 personnel. Unlimited personnel was considered unrealistic, and therefore, the course of the outbreak was modelled using three levels of staffing and the probability of achieving eradication within 3 or 6 months of introduction determined. Under the baseline staffing level, there was only a 16% probability that the outbreak would be eradicated within 3 months, and a 60% probability of eradication in 6 months. Deployment of an additional 60 personnel in the first 3 weeks of the response increased the likelihood of eradication in 3 months to 68%, and 100% in 6 months. Deployment of further personnel incrementally increased the likelihood of timely eradication and decreased the duration and size of the outbreak. Targeted use of vaccination in high-risk areas coupled with the baseline personnel resources increased the probability of eradication in 3 months to 74% and to 100% in 6 months. This required 25 vaccination teams commencing 12 days into the control program increasing to 50 vaccination teams 3 weeks later. Deploying an equal number of additional personnel to surveillance and infected premises operations was equally effective in reducing the outbreak size and duration.
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Data-driven approaches such as Gaussian Process (GP) regression have been used extensively in recent robotics literature to achieve estimation by learning from experience. To ensure satisfactory performance, in most cases, multiple learning inputs are required. Intuitively, adding new inputs can often contribute to better estimation accuracy, however, it may come at the cost of a new sensor, larger training dataset and/or more complex learning, some- times for limited benefits. Therefore, it is crucial to have a systematic procedure to determine the actual impact each input has on the estimation performance. To address this issue, in this paper we propose to analyse the impact of each input on the estimate using a variance-based sensitivity analysis method. We propose an approach built on Analysis of Variance (ANOVA) decomposition, which can characterise how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We apply the proposed approach to a terrain-traversability estimation method we proposed in prior work, which is based on multi-task GP regression, and we validate this implementation experimentally using a rover on a Mars-analogue terrain.
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Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.
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Explosive driven micro blast waves are generated in the laboratory using NONEL tubes. The explosive mixture coated to the inner walls of the plastic Nonel tube comprises of HMX and Aluminum ( 18mg/m). The detonation is triggered electrically to generate micro blast waves from the open end of the tube. Flow visualization and over pressure measurements have been carried out to understand the propagation dynamics of these micro-blast waves in both confined and unconfined domains. The classical cubic root law used for large scale blast correlation appears to hold good even for these micro-blasts generated in the laboratory.
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Recently established moderate size free piston driven hypersonic shock tunnel HST3 along with its calibration is described here. The extreme thermodynamic conditions prevalent behind the reflected shock wave have been utilized to study the catalytic and non-catalytic reactions of shock heated test gases like Ar, N2 or O2 with different material like C60 carbon, zirconia and ceria substituted zirconia. The exposed test samples are investigated using different experimental methods. These studies show the formation of carbon nitride due to the non-catalytic interaction of shock heated nitrogen gas with C60 carbon film. On the other hand, the ZrO2 undergoes only phase transformation from cubic to monoclinic structure and Ce0.5Zr0.5O2 in fluorite cubic phase changes to pyrochlore (Ce2Zr2O7±δ) phase by releasing oxygen from the lattice due to heterogeneous catalytic surface reaction.