Precise measurement of position and attitude based on convolutional neural network and visual correspondence relationship

Accurate measurement of position and attitude information is particularly important. Traditional measurement methods generally require high-precision measurement equipment for analysis, leading to high costs and limited applicability. Vision-based measurement schemes need to solve complex visual relationships. With the extensive development of neural networks in related fields, it has become possible to apply them to the object position and attitude. In this paper, we propose an object pose measurement scheme based on convolutional neural network and we have successfully implemented end-toend position and attitude detection. Furthermore, to effectively expand the measurement range and reduce the number of training samples, we demonstrated the independence of objects in each dimension and proposed subadded training programs. At the same time, we generated generating image encoder to guarantee the detection performance of the training model in practical applications

The effect of the state sector on wage inequality in urban China: 1988–2007

This paper examines the effect of the public sector and state-owned enterprises (SOEs) on wage inequality in urban China using China Household Income Project data. It applies quantile regression analysis, the Machado and Mata decomposition to investigate how urban wage inequality was affected by the changes in wage structure and employment shares of the public sector and SOEs. We find that since the radical state sector reforms designed to reduce overstaffing and improve efficiency in the late 1990s, urban wage gaps were narrowed due to the reduction in the employment share of the state sector; the wage premium of the state sector in comparison with the non-state sector increased significantly; and changes in the wage structure of the labour market caused the rise in urban wage inequality

Do leaders matter? : Chinese politics, leadership transition and the 17th Party Congress

The opaque nature of decision making in China has generated considerable interest in the internecine machinations of elite politics. Particularly, but not only, when it comes to issues of leadership transition, considerations of factional formation and conflict come to the fore. This is partly to explain the transition process itself, but also out of concern for how new leaders might change the direction of Chinese policy. This paper suggests that whilst leaders and leadership changes do matter, they matter less than they once did. This is partly a result of the de-ideologicization and increasing diverse nature of elite interests and group formation. But it is also partly a result of the changed nature of China’s political economy; in short, there is less desire and less ability for new leaders to impose a clear paradigm shift

Expression and Significance of bag-1, bcl-2 in Non-small Cell Lung Cancer and the Correlation with Multi-drug Resistance

Background and objective bag-1, bcl-2 and bax are all apoptosis-related proteins. They play a role in the diagnosis, progress, metastasis and prognosis of tumor. The aim of the study was to investigate the expression of bag-1, bcl-2 and bax in non-small cell lung cancer, and to study the relationship between their expression levels and the clinical pathological characteristics, furthermore, to evaluate their correlation with multi-drug resistance. Methods The expressions of bag-1, bcl-2 and bax in 140 non-small cell lung cancer tissues (40 of 140 were processed neoadjuvant chemotherapy) and 15 lung benign lesion tissues were examined with SP immuno-histochemical stain. Results The positive expression rates of bag-1 and bcl-2 protein in non-small cell lung cancer were significantly higher than those in pulmonary benign lesion tissues (P < 0.05), but the positive expression rate of bax in non-small cell lung cancer was significantly lower than that in pulmonary benign lesion tissues (P < 0.05). The expressions of bag-1, bcl-2 and bax protein were not related to the age and sex of patients, histological classification, P-TNM stage and lymph node involvement of the cancer (P > 0.05), but bag-1 was related to the differentiation degree of the tumor. The lower the differentiation was, the higher the levels of expression of bag-1 were. bcl-2 protein expression was highly positive correlated with the bag-1 protein expression in non-small cell lung cancer (r =0.371, P < 0.01), and bcl-2 protein was highly negative correlated with bax protein expression (r=-0.225, P < 0.01). The positive expression rates of bag-1 and bcl-2 showed increasing trends from the patients without neoadjuvant therapy to those with neoadjuvant therapy, but the difference had no statistic significance (P > 0.05). Conclusion The high expression of bag-1, bcl-2 protein and the low expression of bax protein exist in nonsmall cell lung cancer. The expression level of bag-1 protein is closely related to the differentiation degree of non-small cell lung cancer. A highly positive correlation exists between bag-1 and bcl-2 expression, and a highly negative correlation is observed between bcl-2 and bax expression. The study doesn’t provide the evidence that there is a close correlation between the expression levels of bag-1, bcl-2, bax and the multi-drug resistance in non-small cell lung cancer

LSTM‐based adaptive robust nonlinear controller design of a single‐axis hydraulic shaking table

Abstract The shaking table has been used extensively in the structure test field to verify the structure's performance against various vibrations, for example earthquakes. In order to replicate the vibrations, which are measured by the acceleration signal, the model of the shaking table should be thoroughly constructed to design the controller. However, parametric uncertainty and strong nonlinearity, such as the nonlinear friction, make it an obstacle to obtaining an accurate model. A neural network‐based controller, specifically a long short‐term memory neural network‐based neural network controller, is designed in this paper to address this issue. The nonlinear systems are estimated by the neural network's universal approximation characteristics, and a long short‐term memory neural network is utilized to optimize the time‐series‐related errors. Furthermore, a robust sliding mode controller is utilized to compensate for the residual error of the neural network and other uncertainties. The semi‐global asymptotic stability of the controller is proved by Lyapunov analysis. Comparative experimental results indicate the superiority of the proposed controller