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Copyright of Urban Geology is the property of Urban Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The microstructure characteristics of rocks are the internal basic properties of fine-grained rocks, which affect their physicochemical behavior. This paper takes an example as fine-grained grains in the Yanchang Formation 7 Member of Ordos Basin. First, the geometric morphology characteristics of fine-grained grains are analyzed quantitatively by field scanning electron microscope and image recognition technology. Then, we characterized the influence of the sedimentary environment on the geometric shape and orientation arrangement of fine-grained grains. Results show that the grains in the deep-semi-deep lacustrine facies take the characteristics of fine grain size (2-3 μm), flat and angular shape. The grains are directionally distributed along with a continuous interval. The intensity of the distribution shows a flat quasi-cone shape and well-directional orientation. The fine grains in shallow lake facies are medium-fine grains (2-8 μm), flat and angular type. Besides, the grains show a sharp distribution a-long with a certain interval with no obvious regularity, which has a moderate orientation arrangement. The fine grains in delta facies are fine-grained (8-12 μm) and quasi-circular type. This type of fine-grained rock has an irregular distribution. The intensity distribution of fine grains is circular or elliptical. The circumferential angularity index and flatness of grains can promote the formation of oriented arrangement structure of grains. By contrast, the anisotropy rate and grain size are unfavorable for the formation of an oriented structure. The results are helpful to understand the microstructural characteristics of fine-grained rocks and establish the relationship between microstructures and macrostructures of rocks. [ABSTRACT FROM AUTHOR]

To explore the influence of fracture structure on mechanical properties of rock mass, compression simulation experiment were carried out on rock samples with prefabricated fractures. Based on SEM, NMR and Vic-3D technology, multi-scale study was carried out on rock mass in combination with acoustic and macro-meso-structural characteristics. The rock sample strength decreases with the increase of fracture length, penetration and number, and decreases first and then increases with the increase of fracture dip angle. The rock sample strength of 30 mm fracture is the lowest, and the rock sample strength of 90° fracture is closest to the intact rock sample. Tensile failure occurred in intact rock samples, 0° and 90° fracture samples and tensile and shear composite failure occurred in rock samples with different fracture penetration degrees. Shear failure occurred in rock samples with different fracture lengths, numbers, 30°, 45° and 60° fractures. After loading, the proportion of micro pores decreases while that of medium and large pores increases, indicating that the initial damage and loading caused by prefabricated fractures can change the internal pore structure of rock samples, thus affecting its macroscopic mechanical properties.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of East China University of Science & Technology is the property of Journal of East China University of Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Fuzhou University is the property of Journal of Fuzhou University, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The visible light positioning system is the hot spot of current indoor positioning technology research. Aiming at the problem of inaccurate azimuth angle acquisition in single-lamp positioning system, this paper proposes a single Light Emitting Diode (LED) indoor positioning system based on marked LED. The scheme uses a single LED light with a non-flickering lamp bead as the transmitter to transmit information while realizing the lighting function. The smartphone acts as the receiver to capture images with bright and dark stripes, and obtain the azimuth angle by combining the geometric features of the projection and processing the algorithm. Then the position of the receiver is obtained by further calculation. The results show that in the actual application scenario, when the experimental heights are 1.75 and 1.45 m. The system can achieve average positioning errors of 6.9 and 6.5 cm, which verifies the feasibility and effectiveness of the scheme.

The visible light positioning system is the hot spot of current indoor positioning technology research. Aiming at the problem of inaccurate azimuth angle acquisition in single-lamp positioning system, this paper proposes a single Light Emitting Diode (LED) indoor positioning system based on marked LED. The scheme uses a single LED light with a non-flickering lamp bead as the transmitter to transmit information while realizing the lighting function. The smartphone acts as the receiver to capture images with bright and dark stripes, and obtain the azimuth angle by combining the geometric features of the projection and processing the algorithm. Then the position of the receiver is obtained by further calculation. The results show that in the actual application scenario, when the experimental heights are 1.75 and 1.45 m. The system can achieve average positioning errors of 6.9 and 6.5 cm, which verifies the feasibility and effectiveness of the scheme.

Objectives: Point cloud has no topological structure, current deep learning semantic segmentation algorithm is difficult to capture geometric features implied in irregular points. In addition, the point cloud is in three-dimensional space with a large amount of data size. If we blindly expand the captive field size during extract neighborhood information, it will increase the number of model parameters, which will make model training difficult. Methods: We propose a point cloud semantic segmentation model based on the dilated convolution and combining elementary geometric features such as angle as the model input. First, during feature extraction, basic geometric features such as the relative coordinates, distance and angle between the centroid and the neighboring points are used as the model input to mine the geometric information. Second, in the process of building local neighborhoods, we expand the image dilated convolution operator to point cloud processing, the point cloud dilated operator can expand the receptive field size with no increasing the number of parameters of the model. Finally, the dilated convolution operator, multi-geometric features encoding modules and U-Net architecture are combined to form a complete point cloud semantic segmentation model. Results: The results show that compared with the traditional neighborhood structure, the overall accuracy (OA) of dilated neighborhood structure is increased by 1.4%. Compared with the model that only uses coordinates as input, multi-geometric features encoding module is increased by 10.7%. The final model based on the two proposed algorithms get mean intersection over union and OA are 91.2% and 68.2%, respectively. Conclusions: The dilated neighborhood structure can effectively extract point cloud information in a larger range without increasing the number of model parameters. multigeometric features encoding module can maximize the capture of shape information in the neighborhood. [ABSTRACT FROM AUTHOR]

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Laser Technology is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposed a feature descriptor based on quadratic error, which had rotation invariance. It obtained two feature descriptors by extracting the quadratic error of the point and the quadratic error of the neighboring point. It emerged point cloud registration algorithms based on the Gaussian mixture model in an endless stream. The main reason was that probabilistic models had better robustness in terms of noise and outliers. However, this type of method did not perform well for larger-scale rotations. This paper used the quadratic error feature descriptor as a local feature of the Gaussian mixture model to optimize the registration effect in the larger rotation of the Gaussian mixture model, and proposed a dual-feature-based registration strategy to optimize the defects of a single feature. Through experiments, compared with the robust ICP and popular feature-based registration algorithm in terms of registration efficiency and precision, the efficiency of the algorithm is 3 - 4 times that of the robust ICP. In large-scale rotation, the proposed algorithm has good robustness and is superior to the most popular algorithms. [ABSTRACT FROM AUTHOR]

Based on the advantages of robustness and view-invariant representation, a skeleton-based action recognition algorithm combining geometric features with LSTM network is proposed to further improve the recognition rate and to break the limitation that the inputs of most methods based on deep learning are human joint coordinates. The geometric features based on the distances between joints and selected lines are selected as the input of the network. Then, time-selective LSTM network is introduced to train. Time selection LSTM network has the ability to select the most recognizable time period features. By using this feature, 99.36% and 99.20% recognition rates are achieved on SBU Interaction dataset and UT Kinect dataset, respectively. The experimental results show that the method is effective for human skeleton-based action recognition. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Sciencepaper is the property of China Sciencepaper and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the problem that the virtual 3D cable of CREO can easily cause interference detection difficult because the cable has a flexible optional deformation characteristic, an algorithm that expresses the cable discretely by using dimensional coordinates point is put forward. Firstly, the algorithm expresses the cable entities by using cable centerline discrete spatial coordinates point. Secondly, space position relation of structure is analyzed. Finally, by utilizing the relationship of space position between cables as well as cable and structure, the fast interference detection for 3D cables is realized. The algorithm is validated on the platform Visual Studio 2010 and CREO by using C++ language and TOOLKIT tools. The results show that the algorithm is fast and has better accuracy to meet the actual needs of the project. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The assembly objects were described with convex polyhedron. Geometric features of the assembly objects were analyzed. The two-element method was proposed. Then, the admissible motion direction, geometric constraint conditions and geometric uncertainty were analyzed. The geometric features of the assembly objects with uncertainty were analyzed by the two-element method ,which simplifies the equations of boundary components with errors. All those provide the foundation of assembly process. [ABSTRACT FROM AUTHOR]