A new project, the 230 MeV proton superconducting synchrocyclotron for cancer therapy, was proposed at CIAE in 2013. A model cavity is designed to verify the frequency modulation trimming algorithm featuring a half wa...
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A new project, the 230 MeV proton superconducting synchrocyclotron for cancer therapy, was proposed at CIAE in 2013. A model cavity is designed to verify the frequency modulation trimming algorithm featuring a half wave structure and eight sets of rotating blades for 1 kHz frequency modulation. Based on the electromagnetic (EM) field distribution analysis of the model cavity, the variable capacitor works as a function of time and the frequency can be written in Maclaurin series. Curve fitting is applied for theoretical frequency and original simulation frequency. The second-order fitting excels at the approximation given its minimum variance. Constant equivalent inductance is considered as an important condition in the calculation. The equivalent parameters of theoretical frequency can be achieved through this conversion. Then the trimming formula for rotor blade outer radius is found by discretization in time domain. Simulation verification has been performed and the results show that the calculation radius with minus 0.012 m yields an acceptable result. The trimming amendment in the time range of 0.328-0.4 ms helps to reduce the frequency error to 0.69% in Simulation C with an increment of 0.075 mm/0.001 ms, which is half of the error in Simulation A (constant radius in 0.328-0.4 ms). The verification confirms the feasibility of the trimming algorithm for synchrocyclotron frequency modulation.
We establish an affine equivariant, constrained heteroscedastic model and criterion with trimming for clustering contaminated, grouped data. We show existence of the maximum likelihood estimator, propose a method for ...
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We establish an affine equivariant, constrained heteroscedastic model and criterion with trimming for clustering contaminated, grouped data. We show existence of the maximum likelihood estimator, propose a method for determining an appropriate constraint, and design a strategy for finding reasonable clusterings. We finally compute breakdown points of the estimated parameters thereby showing asymptotic robustness of the method.
With day to day exponential increase in the number of vehicles, it is essential to communicate travel information for road travellers to enhance their travelling experience. One of the recent technologies that aid in ...
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With day to day exponential increase in the number of vehicles, it is essential to communicate travel information for road travellers to enhance their travelling experience. One of the recent technologies that aid in real time and faster communication of information is Vehicular Ad-hoc Network (VANET). To ensure significant connectivity and continuous data flow, Road Side Units (RSU) are installed in VANET. RSUs receive the traffic information from vehicles and communicate it to other RSUs, Traffic Management Centre (TMC) or other adjacent vehicles. However, identifying the appropriate locations to deploy RSUs to maintain network connectivity and reduce cost of installation in a given area are still challenging and cannot be decided based on a single parameter. This paper proposes an Optimal RSU Distribution Planner (ORDP) using a Fusion algorithm (FA) comprising of Evolutionary Genetic algorithm (EGA) and D-trimming. Further it also provides the feasibility to choose the appropriate parameter configuration based on user requirement which makes the model feasible and efficient. The scalability and efficiency of the planner are tested against simulated and realistic datasets and it is seen that ORDP has proved to deliver improved results compared with other greedy approaches.
A study of the relationship between grain yield (GY) and grain protein concentration (GPC) in bread wheat was carried out on a 11-year series of trials conducted by the Groupement d'Etude des Varietes Et Semences ...
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A study of the relationship between grain yield (GY) and grain protein concentration (GPC) in bread wheat was carried out on a 11-year series of trials conducted by the Groupement d'Etude des Varietes Et Semences (GEVES) for the registration of new cultivars on the French National List. Values for GY and GPC came from 458 individual trials, grouped together in 21 series of bi-annual and multi-site data. The correlations between the two characters, calculated environment by environment, appeared highly variable due to high "genotype x environment" interactions for GY and GPC. The use of mean values, calculated on the 21 series of GEVES trials, enabled a better assessment of the relationship between the two characters, and an algorithm was proposed to avoid bias due to potential outliers. Using the well-assessed relationship obtained, grain protein deviations (GPDs) were defined as the standardized residuals of the regression of GPC on GY. These deviations appeared to have a partly genetic basis, as the lines with high deviations were about the same in the two independent datasets constituted by the two consecutive years of GEVES experiments. Some lines used as standards in GEVES trials obtained significant GPD for different series of bi-annual and multi-site trials, confirming the genetic origin of high-GPD. Simulations made to determine the minimum experimental design, showed that at least five sites per year for two consecutive years, were necessary to have a good assessment of the GY-GPC relationship, and hence reliable estimates of GPD.
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