202 research outputs found
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Integrated evolutionary computation neural network quality controller for automated systems
With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time
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Time series modeling of system self-assessment of survival
Self-assessment of survival for a system, subsystem or component is implemented by assessing conditional performance reliability in real-time, which includes modeling and analysis of physical performance data. This paper proposes a time series analysis approach to system self-assessment (prediction) of survival. In the approach, physical performance data are modeled in a time series. The performance forecast is based on the model developed and is converted to the reliability of system survival. In contrast to a standard regression model, a time series model, using on-line data, is suitable for the real-time performance prediction. This paper illustrates an example of time series modeling and survival assessment, regarding an excessive tool edge wear failure mode for a twist drill operation
Socio-Ecological Interactions Promote Outbreaks of a Harmful Invasive Plant in an Urban Landscape
Urban landscapes often harbour organisms that harm people and threaten native biodiversity. These landscapes are characterized by differences in socioeconomic context, habitat suitability and patch connectedness. Identifying which spatial differences enable outbreaks of pests, pathogens and invasive species will improve targeted control efforts.
We tested hypotheses to explain the distribution and demography of puncturevine Tribulus terrestris, a human-dispersed invasive plant in Boise, a city in the western United States. We hypothesized an increase in puncturevine infestations near low-valued properties with a high proportion of bare ground, the species\u27 preferred microhabitat, that are well connected on the urban road network. To test these hypotheses, we collected data on the abundance, emergence and persistence of reproductive plants in transects spanning \u3e100 km of our study city. We then used hierarchical Bayesian models to evaluate the impacts of spatial covariates on puncturevine distribution and demography.
Bare ground cover consistently increased abundance, emergence and persistence of puncturevine, indicating the overarching importance of suitable establishment sites for this invasive species.
Property value had the strongest impact on puncturevine abundance and was the most important main effect in the model for puncturevine emergence. In both models, lower-valued properties had a higher risk of puncturevine occurrence.
The effects of road network connectivity depended on bare ground cover, with the highest predicted abundance and emergence of puncturevine in patches with low connectivity on the road network and high bare ground cover. Understanding these relationships will require data that can disentangle seed dispersal from establishment limitations
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Exploring electronic effects on the partitioning of actinides(III) from lanthanides(III) using functionalised bis-triazinyl phenanthroline ligands
The first examples of 4,7-disubstituted 2,9-bis(5,5,8,8-tetramethyl-5,6,7,8-tetrahydro-1,2,4-benzo-triazin-3-yl)-1,10- phenanthroline (CyMe4 -BTPhen) ligands are reported herein. Evaluating the kinetics, selectivity and stoichiometry of actinide(III) and lanthanide(III) radiotracer extractions has provided a mechanistic insight into the extraction process. For the first time,
it has been demonstrated that metal ion extraction kinetics can be modulated by backbone functionalisation and a promising new CHON compliant candidate ligand with enhanced metal ion extraction kinetics has been identified. The effects of 4,7- functionalisation on the equilibrium metal ion distribution ratios are far more pronounced than those of 5,6-functionalisation. The
complexation of Cm(III) with two of the functionalised ligands was investigated by TRLFS and, at equilibrium, species of 1:2 [M:L] stoichiometry were observed exclusively. A direct correlation between the ELUMO-EHOMO energy gap and metal ion extraction potential is reported, with DFT studies reaffirming experimental findings
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