Frequency Analysis on the Data of Field Fertilizer Efficiency Test and Fertilization Decision-making

To solve the problems of abnormal larger, abnormal lower or even negative of target yield and fertilizing amount recommended by part of non-typical fertilizer effect equations using agricultural experiments and statistical analysis software,Yangzhou analyzer（2.2）, regression analysis of Excel, which objected to local actual production, the study adopted the principle and method of basic knowledge and the frequency of using probability theory, and carried out statistical analysis on the rape field fertilizer experiment data by frequency analysis method, the rape yield after optimizing fertilizing amount was 1 732.4 kg/hm^2, the ranges of N, P and K optimal combinations were： N=210.36-149.64 kg/hm^2,P2O5=81.89-58.11 kg/hm^2, K2O=81.89-58.11 kg/hm^2,which was consistent with local actual production. This study was based on frequency analysis, using weighted average method to determine the production combinations of different yield objectives, hereinto, the combinations with high yield, high frequency of occurrence（dependable crop） and fertilizer-saving were viewed as the optimizing production measures, and they had the merits of increasing fertilization decision-making information, reducing or avoiding the risk of small probability event. The results of this study can solve the problem of abnormal values fertilizing amount and target yield recommended by non-typical fertilizer effect function, which did not accord with local actual production, caused by Yangzhou analyzer（2.2）, regression analysis of Excel, and DPS statistical analysis software. For the fertilizer effect function equation established by regression analysis which did not reach significance level using variance analysis, whether the method can be adapted to for carrying out fertilization decision-making, recommending optimization combinations of N, P and K fertilizers and yield under optimized fertilizing amount should be further researched in future working practice.

Theoretical analyses of testing efficiency in long-term breeding of poplar

The major goal for long-term poplar breeding can be formulated as maximizing annual progress in Group Merit Gain at a given annual budget （GMG/Y＊）. To evaluate different breeding scenarios, a deterministic simulator BREEDING CYCLE ANALYZER covering the most important aspects （gain, cost, time, technique, and gene diversity） of a full breeding cycle was used. The breeding strategies considered was based on pairwise crossing of the selected breeding population and balanced within family selection for the next breeding population. A main scenario and a number of alternative scenarios within these constraints were evaluated using estimates of the best available inputs for poplars. In focus was a comparison between three different testing scenarios for selecting the parents mated to create future breeding generations, thus selecting based on phenotype, clone test or progeny test. For the main scenario, the highest GMG/Y, and the optimal selection age for clone, phenotype and progeny strategies were 0.7480 %, 0.6989% and 0.4675%; 7, 6, and 11 years respectively. Clone test was best except when heritability was high, plant price was high or total budget was low; phenotype strategy was the second except for the case of extremely low narrow-sense heritability, for which the progeny strategy was a little more efficient than phenotype strategy. GMG/Y was markedly affected by narrow-sense heritability, additive variance at mature age, rotation age, plant-dependent cost, total budget and the time needed to produce the test plants, while diversity loss and recombination cost had rather weak effect on GMG/Y. Short rotation age and cheap testing cost favoured all three testing strategies. Comparably short rotation age, low plant-dependent cost and high total budget seem to promote early selection for progeny strategy.

Parallel Test Tasks Scheduling and Resources Configuration Based on GA-ACA

A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.

Viewing English Teaching and Test Method from a Brand-new Perspective

There has been close relationship between English test method and teaching method. When we make great efforts to reform the English teaching method we should improve the English test method. In this way, we can increase the test efficiency, trustiness, English teaching quality and evaluation function, to transform the teaching from examination-oriented education into quality education.

Flexible,efficient,and accurate tests for epidemics

Group testing involves discovering a small subset of distinguished subjects from a large population while efficiently reducing the total number of tests.It has been widely used for industrial testing,information technology,and biology,especially epidemic screening.Tests,in reality,are noisy for the presence of false outcomes.Some tests are accurate but time-consuming,while others are cheaper but less accurate.Exactly which test to use is constrained by various considerations,such as availability,cost,accuracy,and efficiency.In this paper,we propose flexible,efficient,and accurate tests(FEATs).FEATs are based on group testing with simple but careful designs by incorporating ideas such as close contact cliques and repeated tests.FEATs could dramatically improve the efficiency or accuracy of existing tests.For example,for accurate but slow tests,the FEAT can improve efficiency multiple times without compromising accuracy.On the other hand,for fast but inaccurate tests,the FEAT can sharply reduce the false-negative rate(FNR)and significantly increase efficiency.Theoretical justifications are provided.We point out some scenarios where the FEAT can be effectively employed.

Turbine efficiency test on a large hydraulic turbine unit

The flow rate measurements are the most difficult part of efficiency tests on prototype hydraulic turbines.Among the numerous flow rate measurement methods,the Winter Kennedy method is preferred for measuring turbine flow rates,since it is convenient,practical and economical.This paper describes efficiency tests on a large 300 MW Francis turbine,with the flow rate measured using the Winter Kennedy method and the Winter Kennedy flow rate coefficient calibrated using the Gibson method.The measured turbine efficiency curve is then compared with the curve provided by the manufacturer.The CFD calculations including the spiral case are then used to analyze the influence with the coefficient K and index n in the Winter Kennedy flow rate formula on the flow rate measurement.The uncertainty values of n and K are a key reason for the differences between the curves obtained from the efficiency test and the curves provided by the manufacturer.

A new method for improving efficiency of protocol testing

Traditional solutions have encountered some bottleneck in improving the efficiency of protocol testing.A novel method that records the test sequence dynamically is proposed.Three dynamically reordering algorithms are brought forward in line with different fault conditions.The impact of the new method of testing efficiency is also presented.Simulation results demonstrate that the proposed solution is better than the traditional ones in terms of testing efficiency.