In smart cities and factories, robotic applications require high accuracy and security, which depends on precise inverse dynamics modeling. However, the physical modeling methods cannot include the (...) nondeterministic factors of the manipulator, such as flexibility, joint clearance, and friction. In this paper, the Semiparametric Deep Learning method is proposed to model robot inverse dynamics. SDL is a type of deep learning framework, designed for optimal inference, combining the Rigid Body Dynamics model and Nonparametric Deep Learning model. The SDL model takes advantage of the global characteristics of classic RBD and the powerful fitting capabilities of the deep learning approach. Moreover, the parametric and nonparametric parts of the SDL model can be optimized at the same time instead of being optimized separately. The proposed method is validated using experiments, performed on a UR5 robotic platform. The results show that the performance of SDL model is better than that of RBD model and NDL model. SDL can always provide relatively accurate joint torque prediction, even when the RBD or NDL model is not accurate. (shrink)
Pattern recognition-based seismic facies analysis techniques are commonly used in modern quantitative seismic interpretation. However, interpreters often treat techniques such as artificial neural networks and self-organizing (...) class='Hi'> maps as a “black box” that somehow correlates a suite of attributes to a desired geomorphological or geomechanical facies. Even when the statistical correlations are good, the inability to explain such correlations through principles of geology or physics results in suspicion of the results. The most common multiattribute facies analysis begins by correlating a suite of candidate attributes to a desired output, keeping those that correlate best for subsequent analysis. The analysis then takes place in attribute space rather than space, removing spatial trends often observed by interpreters. We add a stratigraphy layering component to a SOM model that attempts to preserve the intersample relation along the vertical axis. Specifically, we use a mode decomposition algorithm to capture the sedimentary cycle pattern as an “attribute.” If we correlate this attribute to the training data, it will favor SOM facies maps that follow stratigraphy. We apply this workflow to a Barnett Shale data set and find that the constrained SOM facies map shows layers that are easily overlooked on traditional unconstrained SOM facies map. (shrink)
This study explores the macro education policy design on the vocational education system for the new generation of migrant workers in China. The content system of vocational (...) education, the... (shrink)
This study examines the educational policy related to the inclusion of ethnic minority population in the contemporary China. It has undergone three stages of the educational policy (...) transformation, including the beginning, development and perfection stages. It is characterized by the steadiness, caution, rapidity, quality improvement, standardization and quality. Through implementing the educational policy of the inclusion of ethnic minority population, it has made retrogress and achievements, which has played a positive role in national integration, maintaining national unity and regional stability, improving the academic level and cross-cultural ability of minority students, and sharing educational resources. However, in current China’s education context, the implementation of education policy is faced with some prominent problems, such as the marginalized educational identity, non-communicative education, relative separation of systems and serious cultural barriers, relative emphasis on explicit education. Therefore, it suggested to construct a new integrative and open ethnic education system, strengthen the consciousness of the united integrated education, and enhancing the bi-directionality of ethnic integration. (shrink)
One of the key components of traditional seismic interpretation is to associate or “label” a specific seismic amplitude package of reflectors with an appropriate seismic or geologic (...) facies. The object of seismic clustering algorithms is to use a computer to accelerate this process, allowing one to generate interpreted facies for large 3D volumes. Determining which attributes best quantify a specific amplitude or morphology component seen by the human interpreter is critical to successful clustering. Unfortunately, many patterns, such as coherence images of salt domes, result in a salt-and-pepper classification. Application of 3D Kuwahara median filters smooths the interior attribute response and sharpens the contrast between neighboring facies, thereby preconditioning the attribute volumes for subsequent clustering. In our workflow, the interpreter manually painted [Formula: see text] target facies using traditional interpretation techniques, resulting in attribute training data for each facies. Candidate attributes were evaluated by crosscorrelating their histogram for each facies with low correlation implying good facies discrimination, and Kuwahara filtering significantly increased this discrimination. Multiattribute voxels for the [Formula: see text] interpreter-painted facies were projected against a generative topographical mapping manifold, resulting in [Formula: see text] probability density functions. The Bhattacharyya distance between the PDF of each unlabeled voxel to each of [Formula: see text] facies PDFs resulted in a probability volume of each user-defined facies. We have determined the effectiveness of this workflow to a large 3D seismic volume acquired offshore Louisiana, USA. (shrink)
Ordovician fractured vuggy carbonate reservoirs, which are deeply buried in the Tazhong Shunnan area in China, are characterized by high heterogeneity. Meanwhile, there is no significant difference (...) between the geophysical characteristics of the reservoirs and that of the surrounding rocks. We have introduced the multiscale stack random medium theory and built some theoretical seismic-geologic models for the fractured vuggy carbonate reservoirs. Furthermore, we obtained the seismic reflection characteristics corresponding to these models using finite-difference forward modeling. The small random vugs are characterized by weak and chaotic reflections with high frequency, and the large vugs are characterized by strong and chaotic reflections with low frequency. The amplitude of the seismic reflections increases with the increasing vug density, and it decreases with the increasing roughness factor. Combining the synthetic reflection characteristics corresponding to the fractured vuggy carbonate reservoirs and the actual seismic reflections from the drilled reservoirs, we summarized the recognition patterns of the carbonate reservoirs. The predicted results found that the potential fractured vuggy reservoirs at the top of Yijianfang Formation are located in the southwest and northeast, in the vicinity of fault zones. The reservoirs in Peng-Laiba Formation are distributed in the northwest of the block. (shrink)
This study explores how China’s education responses to COVID-19 from a perspective of policy analysis. Specifically, it involves building an educational policy system for COVID-19 (...) to examine educat... (shrink)
This study explores the online education action for defeating COVID-19 in China from the perspectives of the system, mechanism and mode. In particular, the policy development (...) class='Hi'>of online education in... (shrink)
Recent developments in seismic attributes and seismic facies classification techniques have greatly enhanced the capability of interpreters to delineate and characterize features that are not prominent in (...) conventional 3D seismic amplitude volumes. The use of appropriate seismic attributes that quantify the characteristics of different geologic facies can accelerate and partially automate the interpretation process. Self-organizing maps are a popular seismic facies classification tool that extract similar patterns embedded with multiple seismic attribute volumes. By preserving the distance in the input data space into the SOM latent space, the internal relation among data vectors on an SOM facies map is better presented, resulting in a more reliable classification. We have determined the effectiveness of the modified algorithm by applying it to a turbidite system in Canterbury Basin, offshore New Zealand. By incorporating seismic attributes and distance-preserving SOM classification, we were able to observe architectural elements that are overlooked when using a conventional seismic amplitude volume for interpretation. (shrink)
Seismic attenuation, generally related to the presence of hydrocarbon accumulation, fluid-saturated fractures, and rugosity, is extremely useful for reservoir characterization. The classic constant attenuation estimation model, (...) class='Hi'>focusing on intrinsic attenuation, detects the seismic energy loss because of the presence of hydrocarbons, but it works poorly when spectral anomalies exist, due to rugosity, fractures, thin layers, and so on. Instead of trying to adjust the constant attenuation model to such phenomena, we have evaluated a suite of seismic spectral attenuation attributes to quantify the apparent attenuation responses. We have applied these attributes to a conventional and an unconventional reservoir, and we found that those seismic attenuation attributes were effective and robust for seismic interpretation. Specifically, the spectral bandwidth attribute correlated with the production of a gas sand in the Anadarko Basin, whereas the spectral slope of high frequencies attribute correlated with the production in the Barnett Shale of the Fort Worth Basin. (shrink)
In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution (...) in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)
The target of this study is the Bukuma-minor channel that is distributed along the southern Niger Delta slope. It overlaid the eastern outer levee of the (...) class='Hi'>adjacent Bukuma Channel System to the north, but it converged westward into BCS to the south. Significant morphological variations between and within these two parts as well as their controlling factors were investigated quantitatively, using high-resolution 3D seismic data: Changes of palaeotopographic gradients were supposed to be the largest contributor to morphological variations in section A. Section A1 was developed on the low-gradient sector and characterized by the wide and shallow segment, with a relatively sinuous flowpath, whereas section A2, corresponding to a steep slope, was a linearly entrenched one, characterized by the narrow and deep segment. In addition, there were some positive correlations among geometric parameters in section A1, which, however, had been undermined by the large gradient in section A2. Strong confinement of BCS results in the larger width, smaller thickness, and more stable sinuosity of section B. In general, correlations among geometric parameters in this part are not significant. In light of these correlations among geometric parameters and the influence of palaeotopographic gradients, we established an evolutionary model for general submarine channels. (shrink)
The target of this study is the Bukuma-minor channel that is distributed along the southern Niger Delta slope. It overlaid the eastern outer levee of the (...) class='Hi'>adjacent Bukuma Channel System to the north, but it converged westward into BCS to the south. Significant morphological variations between and within these two parts as well as their controlling factors were investigated quantitatively, using high-resolution 3D seismic data: Changes of palaeotopographic gradients were supposed to be the largest contributor to morphological variations in section A. Section A1 was developed on the low-gradient sector and characterized by the wide and shallow segment, with a relatively sinuous flowpath, whereas section A2, corresponding to a steep slope, was a linearly entrenched one, characterized by the narrow and deep segment. In addition, there were some positive correlations among geometric parameters in section A1, which, however, had been undermined by the large gradient in section A2. Strong confinement of BCS results in the larger width, smaller thickness, and more stable sinuosity of section B. In general, correlations among geometric parameters in this part are not significant. In light of these correlations among geometric parameters and the influence of palaeotopographic gradients, we established an evolutionary model for general submarine channels. (shrink)
