An Improved Method for Computing Eigenpair Derivatives of Damped System

The calculation of eigenpair derivatives plays an important role in vibroengineering. This paper presents an improved algorithm for the eigenvector derivative of the damped systems by dividing it into a particular solution and general solution of the corresponding homogeneous equation. Compared with the existing methods, the proposed algorithm can significantly reduce the condition number of the equation for particular solution. Therefore, the relative errors of the calculated solutions are notably cut down. The results on two numerical examples show that such strategy is effective in reducing the condition numbers for both distinct and repeated eigenvalues

A Study on the Damage and Economic Threshold of the Soybean Aphid at the Seedling Stage

Both plot inoculation experiments and field pest scouting at the seedling stage indicated that soybean yield losses were closely related to the number of soybean aphids and the proportion of plants colonized by soybean aphids. The main factors affecting the soybean yield were decrease in plant height and number of pods and seeds, owing to injury by soybean aphids at the seedling stage. Under existing production conditions, the economic injury level was 3.36%. The control threshold was 500 soybean aphids per 100 plants, with 35% of plants colonized by soybean aphids.Originating text in Chinese.Citation: Wang, Xibei, Fang, Yihao, Lin, Zhizhong, Zhang, Lirong, Wang, Huadi. (1994). A Study on the Damage and Economic Threshold of the Soybean Aphid at the Seedling Stage. Plant Protection (Institute of Plant Protection, CAAS, China), 20, 12-13

Eigensensitivity of damped system with defective multiple eigenvalues

This paper considers the sensitivity of defective multiple eigenvalues of reducible matrix pencil, the average of eigenvalues is proved to be analytic, the derivatives of the average eigenvalues and the corresponding eigenvector matrices are obtained when the generalized eigenvalue is reducible. The sensitivity of defective multiple eigenvalues of a quadratic eigenvalue problem dependent on several parameters are also obtained by the result of generalized eigenvalue problem. The results are useful for investigating structural optimal design, model updating and structural damage detection

Computing eigenpair derivatives of asymmetric damped system by generalized inverse

Many existing approaches for asymmetric damped system are based on the assumption that the eigenvalues are simple or semisimple with separated derivatives. This paper presents a new algorithm for computing the derivatives of the semisimple eigenvalues and corresponding eigenvectors of asymmetric damped system. Compared with the existing methods, the algorithm can be applicable to problems whether the repeated eigenvalues have well separated derivatives. In the proposed method, the derivatives of eigenvectors are divided into a particular solution and a homogeneous solution, where the particular solution is constructed by using generalized inverse matrix. The effectiveness of the proposed algorithm is illustrated by one numerical example

Educated Return Migrants in Rural China

University of Technology Sydney. Faculty of Arts and Social Sciences.This research attempts to investigate the rural educated return migrants’ mobility, translocal practice and scale negotiation in rural China through conducting an ethnographic inquiry. Return migrants, or (youth who return to their hometown), in this research, refer to the rural students who graduated in tertiary institutions in the city and returned to their hometown in the countryside. The return migration in China is a counter-mainstream movement, as it is reverse against the dominant trend of rural to urban migration. Rural-urban migration is the most basic rural household livelihood strategy in contemporary China that diversifies the household income plan. Moreover, the modernisation hegemony projects the urban sphere as a symbol of being advanced. In tandem with the discourse that is a unique post-socialist China political-cultural tool, the rural population is motivated and even compelled to go to the city to receive the urban influence, once they reach a certain age. As a result, the number of rural migrants in the city has been increasing since the 1980s. In that vein, the motivation and social context of the reverse migration in this research is particularly interesting to explore. In this research, return migrants are viewed as the nexus of body and place struggle. Drawing on a rubric of cross-disciplinary analysis tool, it examines the educated return migrants’ decision of return, career seeking, family and social life. It also investigates their agency of mediating, negotiating and change-making amid the familial and social constraints. Furthermore, I inspect their contribution in the process of rural development. This research consists of two levels. On the individual level, I explore their personal, work and social life, which present their ambiguous position as the return migrants in a rural setting. On the contextual level, I also examine the formation of the social scale which rationales the current rural development discourse. By drawing an in-depth picture of the educated return migrants’ translocal practice in daily life and their participation in rural development, I present their role as ‘place entrepreneur’ situated in the rural-urban dynamic. This thesis contributes to the academic discussion of how inequality in China impacts subjectivity

Neighborhood Attribute Reduction: A Multicriterion Strategy Based on Sample Selection

In the rough-set field, the objective of attribute reduction is to regulate the variations of measures by reducing redundant data attributes. However, most of the previous concepts of attribute reductions were designed by one and only one measure, which indicates that the obtained reduct may fail to meet the constraints given by other measures. In addition, the widely used heuristic algorithm for computing a reduct requires to scan all samples in data, and then time consumption may be too high to be accepted if the size of the data is too large. To alleviate these problems, a framework of attribute reduction based on multiple criteria with sample selection is proposed in this paper. Firstly, cluster centroids are derived from data, and then samples that are far away from the cluster centroids can be selected. This step completes the process of sample selection for reducing data size. Secondly, multiple criteria-based attribute reduction was designed, and the heuristic algorithm was used over the selected samples for computing reduct in terms of multiple criteria. Finally, the experimental results over 12 UCI datasets show that the reducts obtained by our framework not only satisfy the constraints given by multiple criteria, but also provide better classification performance and less time consumption

An Ensemble Framework to Forest Optimization Based Reduct Searching

Essentially, the solution to an attribute reduction problem can be viewed as a reduct searching process. Currently, among various searching strategies, meta-heuristic searching has received extensive attention. As a new emerging meta-heuristic approach, the forest optimization algorithm (FOA) is introduced to the problem solving of attribute reduction in this study. To further improve the classification performance of selected attributes in reduct, an ensemble framework is also developed: firstly, multiple reducts are obtained by FOA and data perturbation, and the structure of those multiple reducts is symmetrical, which indicates that no order exists among those reducts; secondly, multiple reducts are used to execute voting classification over testing samples. Finally, comprehensive experiments on over 20 UCI datasets clearly validated the effectiveness of our framework: it is not only beneficial to output reducts with superior classification accuracies and classification stabilities but also suitable for data pre-processing with noise. This improvement work we have performed makes the FOA obtain better benefits in the data processing of life, health, medical and other fields

Revealing Impacts of Trees on Modeling Microclimate Behavior in Spaces between Buildings through Simulation Monitoring

Urban trees have been recognized as having different impacts on the microclimate and thermal comfort. Therefore, this study conducted on-site measurement and simulation to explore and clarify how trees impact the microclimate, thermal comfort, and façade temperature. A campus site was selected as the test field and two models—one with and one without trees—were built with the ENVI-met. Meanwhile, one microclimate station and four sensors were installed to simulate and validate the microclimate. Twelve blocks with different tree conditions were also selected to further investigate the specific impacts of trees. The results showed that, firstly, the transpiration and sheltering effect of trees that dominates on sunny days can decrease air temperature and the predicted mean vote. Secondly, trees’ effects on airflow, including on the wind channel and blocking effect, are dominant on cloudy days. Trees inside the group often exhibit the wind-blocking effect, while trees with a downwind determinant at the windward group edge usually exhibit the wind channel effect. Thirdly, high canopy coverage enhances trees’ sheltering effect on solar radiation. The study also provides design recommendations for campus building and trees that account for how trees help improve the microclimate, enhance comfort, and reduce energy consumption.Applied Science, Faculty ofNon UBCEngineering, School of (Okanagan)ReviewedFacultyResearche

Relationship and Accuracy Analyses of Variable Precision Multi-Granulation Rough Sets based on Tolerance Relation

This paper discusses the properties of optimistic, pessimistic and basic approximations of rough sets in ordinary and variable precise multi-granulation models and the ones produced by using union and intersection operations on multi-property relations deeply, and analyzes the relationships between or among them. It explores the approximate accuracy formulas and finds several inequalities to describe their relationships of those approximate accuracy formulas. It proves that approximation accuracy of incomplete variable precision multi-granulation rough sets based on tolerance relation is higher than the non-variable ones

Analysis on Causative Factors and Evolution Paths of Blast Furnace Gas Leak Accident

Although the interest in metallurgical accident investigation of blast furnace gas (BFG) leakage has increased to explore the engineering failures, more effort is needed to address the individual and organizational causative factors to clear and determine the weak links for improving safety management and accident prevention to achieve green metallurgical manufacturing. This study aims to examine the causative factors and evolution paths of BFG leakage by introducing a combined method, the 24 model and Bayesian network (BN), based on 50 cases of fire, explosion and suffocation accidents caused by BFG leakage. A BN model of BFG leakage was established based on the identification of 25 causative factors by the 24 model. Results showed that eight nodes, including A1 (unsafe operation), A2 (unsafe behavior), A4 (unsafe condition), B1 (valve failure), B2 (improper gas safety operation), X4 (use of BFG violates regulations), X5 (water gas is not cut off before shutdown reduction) and X6 (incomplete steam purging), were more sensitive than others, and the posterior probability of nodes A1, A2, A3 (unsafe command), A4, B1, B2, B4 (improper emergency behavior), B5 (unsafe behaviors on BFG site) increased compared to prior probability. Three main accident causal chains were obtained which indicate that control the unsafe operations (A1) related to gas (B2) and valve (B1) are suggested to be improved. Another important factor is A4 (unsafe condition), which is related to intrinsic safety conditions. Considering the results, the key points of 3E strategy about BFG leakage prevention are suggested. This study provides useful insights to understand the organizational and individual factors and their relative influence in BFG leakage accidents, which will support BFG leakage prevention and safety management