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To solve the problem of difficulty for robots to quickly explore unknown environments with narrow entrances, as well as the decrease in exploration efficiency caused by wandering between targets with close exploration benefits, this paper proposed a self-exploration algorithm USAGE (uniformly scanning and attentive guidance explorer), which included uniform scanning and attentive guidance strategy. USAGE used the uniform scanning method to detect boundary points, and clustered the boundary points to obtain the points to be explored, and finally determined the optimal exploration target through an attentive guidance strategy. This strategy introduced the steering cost evaluation index into the traditional evaluation function containing information gain and path cost, and constrained the execution of the exploration task according to the robot's state, and guided the robot to focus on exploration. Through building a simulation environment in the robot operating system for verification, the experimental results show that compared with the exploration algorithm based on rapidly-exploring random tree (RRT), USAGE occupies less system memory by more than 11.34%, reduces the exploration time and exploration path level by 26. 90% and 31.94% respectively, which improves autonomous exploration efficiency. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of domestic wastewater treatment process design, a wastewater treatment process database was established to save data samples abstracted from real domestic wastewater treatment processes, and the process was selected by the support vector machine classification algorithm based on boundary points(BP-SVM). Support vector machine classification algorithm based on boundary points(BP-SVM)was used to select the process. Multiple BP-SVMs were set up to solve the multi-classification problem. Parameter optimization of BP-SVM parameters was performed using genetic algorithm(GA). The results of the study show that the process design algorithm gives a suitable solution, verifies an accuracy of 94%, and consumes less compared to other algorithms. The feasibility and effectiveness of the algorithm is proved. [ABSTRACT FROM AUTHOR]

Accurate land surveying is beneficial for land planning and management. This article briefly introduced the global positioning system (GPS) positioning principle and the process of conducting land surveys using GPS technology. A case of Anyi Street, Yanhu District, Yuncheng City, Shanxi Province, was analyzed. The results indicated that the GPS means used effectively obtained land mapping maps and were sufficiently accurate, with a measurement plane error of less than 10 mm for the marking points and a land boundary deviation of 0-10 mm. [ABSTRACT FROM AUTHOR]

Relatively low ground-penetrating radar antenna frequencies are usually selected for tunnel inspection due to the thickness of the lining, which causes the geometric features of voids in the image to be blurred and difficult to identify. Therefore, the boundary points of the voids are determined by combining reflection and attenuation coefficients, and the geometric features are constructed to identify the voids. Depending on the electromagnetic differences between the void and other mediums in the lining, when the electromagnetic wave propagates from the lining concrete to the void, the reflection coefficient is positive, and the phase of the reflected wave is the same as the incident wave. Conversely, the phase of the reflected wave is opposite to the incident wave. Therefore, the boundary point can be determined in the one dimension time-waveform diagram (A-Scan) based on the phase change. Moreover, the amplitude of the electromagnetic wave attenuates exponentially in the concrete, but it attenuates slowly in the void. Also, electromagnetic waves exhibit high-frequency characteristics in the lining but low-frequency characteristics in the voids. Boundary points that conform to the variation of amplitude and frequency characteristics in the void are screened. These boundary points are then constructed in two-dimensional scan data (B-Scan) to identify the voids by using the geometry of the voids. This method is applied to the Hu Sa Tunnel. The voids are successfully identified in the mileage section YK81+310–YK81+422 of the Hu Sa Tunnel, and the depth of cover and the area of voids are correctly estimated. [ABSTRACT FROM AUTHOR]

The main goal of the work is to construct the boundaries of the stability regions of the stationary solution of autonomous Hamiltonian systems in the parameter plane. The paper specifies the conditions under which one or more smooth boundary curves pass through a point of the boundary of the stability region. [ABSTRACT FROM AUTHOR]

The global positioning system real-time kinematic (GPS-RTK) instrument is a commonly used instrument to obtain GPS coordinates in cadastral surveying, but its use is limited to unshielded environments. This study proposes a new method based on a visual simultaneous localization and mapping (SLAM) algorithm that uses a stereo-camera to replace traditional methods. The benefits of our method are a higher measurement efficiency, fewer required professionals, and fewer restrictions on the operating environment compared with the traditional RTK and total station method. First, we propose a robust non-planar camera calibration algorithm that uses three non-planar chessboards to obtain intrinsic parameters of a stereo-camera to improve the accuracy of the measurement. Second, we propose a detailed algorithm that uses a stereo-camera and known GPS coordinates to obtain unknown GPS coordinates. Using experiments, we demonstrated the effectiveness and stability of our method to provide accurate GPS coordinates.

Aiming at the problem of time-consuming point cloud registration due to the large amount of point cloud data of the workpiece,this paper proposed a point cloud registration method based on key points optimization after downsampling.It calculated the center of gravity of several voxels in the point cloud and used kd-tree to quickly traverse the neighboring points of the center of gravity to replace the voxel.It proposed an adaptive point cloud average distance calculation method to extract the ISS3 D key points from the down-sampled point cloud,and used boundary point judgment method of the spherical neighborhood to optimize.The characteristic of FPFH described the key points after optimized.It used SAC-IA to solve approximate transformation matrix,and used ICP algorithm for precise registration to obtain the precise pose information of the workpiece.The experimental results show that compared with the other four registration algorithms,the registration accuracy has improved by96.9%,98.1%,93.3%,and 3.5%,the registration speed has increased by 77.2%,77.7%,76.9%,and 85.4%,it shows the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Objectives: The extraction of boundary points and boundary lines is a very important work in land ownership confirmation. The traditional boundary points and boundary lines extraction method first needs to be judged manually, and then the attribute information corresponding to the boundary points and boundary lines is manually input into the attribute table according to the result of judgment. Excessive manual intervention not only makes the work inefficient, but also easy to cause all kinds of errors.Methods: In or-der to solve the above problems, an optimization algorithm for boundary points and boundary lines extrac-tion is proposed. The idea of the algorithm is as follows: (1) Using the modeling tools in ArcGIS to estab-lish a set of data preprocessing model for all parcels, and generate the template files of boundary points and boundary lines through the model; (2) Read some attribute field information of parcel and template file by using GDAL (geographic data abstraction library); (3) Generate and automatically read parcel boundary points and boundary lines file.Results: The experimental results show that this method can effectively avoid human intervention and greatly improve the extraction efficiency of boundary points and boundary lines. Conclusions: In the actual production, especially in the extraction of large quantities of boundary points and lines, this method has considerable advantages and provides original technical support for similar land moni-toring and management in China [ABSTRACT FROM AUTHOR]

In this paper, a method for classifying 3D unorganized points into interior and boundary points using a deep neural network is proposed. The classification of 3D unorganized points into boundary and interior points is an important problem in the nonuniform rational B-spline (NURBS) surface reconstruction process. A part of an existing neural network PointNet, which processes 3D point segmentation, is used as the base network model. An index value corresponding to each point is proposed for use as an additional property to improve the classification performance of the network. The classified points are then provided as inputs to the NURBS surface reconstruction process, and it has been demonstrated that the reconstruction is performed efficiently. Experiments using diverse examples indicate that the proposed method achieves better performance than other existing methods. [ABSTRACT FROM AUTHOR]

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Copyright of Qing History Journal is the property of Renmin University of China, Institute of Qing History 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 evaluation of clustering results plays an important role in clustering analysis. However, the existing validity indices are limited to a specific clustering algorithm, clustering parameter, and assumption in practice. In this paper, we propose a novel validity index to solve the above problems based on two complementary measures: boundary points matching and interior points connectivity. Firstly, when any clustering algorithm is performed on a dataset, we extract all boundary points for the dataset and its partitioned clusters using a nonparametric metric. The measure of boundary points matching is computed. Secondly, the interior points connectivity of both the dataset and all the partitioned clusters are measured. The proposed validity index can evaluate different clustering results on the dataset obtained from different clustering algorithms, which cannot be evaluated by the existing validity indices at all. Experimental results demonstrate that the proposed validity index can evaluate clustering results obtained by using an arbitrary clustering algorithm and find the optimal clustering parameters. [ABSTRACT FROM AUTHOR]

In this paper the new concept of nano topological boundary approach is introduced to identify the bone fracture in it digital images. [ABSTRACT FROM AUTHOR]

For linear systems with bounded control, a new approach to real-time implementation of a resource-optimal control is proposed. The computational costs are separated between preliminary computations and computations in the control process. The preliminary computations are independent of the particular initial condition and are based on the approximation of sets reachable in different times by a family of hyperplanes. Methods for constructing an approximating family and selecting a supporting hyperplane are described. A method for finding an approximate optimal control time and correctly specifying the transfer time in resource consumption minimization is proposed. A technique specifying an initial approximation for low-cost iterative computations of a resource optimal control is developed. A computational algorithm is described, and simulation and numerical results are presented. [ABSTRACT FROM AUTHOR]

There are some real-world problems in which multiple objectives conflict with each other and the objectives change with time. These problems require an optimization algorithm to track the moving Pareto front or Pareto set over time. In this paper, we propose a predictive strategy based on special points (SPPS) which consists of three mechanisms. The first one is that the non-dominated set is predicted directly by feed-forward center points, which can eliminate many useless individuals predicted by traditional prediction using feed-forward center points. The second one is that a special point set (such as boundary point and knee point) is introduced into the predicted population which can track Pareto front or Pareto set more accurately. The third one is the adaptive diversity maintenance mechanism based on boundary points and center points. The mechanism can introduce diverse individuals of the corresponding number according to the degree of difficulty of the problem to keep the diversity of the population. The number of these diverse individuals is strongly related to the center points. Then, they are generated evenly throughout the decision space between the boundary points. The proposed strategy is compared with the four other state-of-the-art strategies. The experimental results show that SPPS can do well for dynamic multi-objective optimization. [ABSTRACT FROM AUTHOR]

In this study, a boundary analysis is carried out for the derivative of driving point impedance (DPI) functions, which is mainly used for the synthesis of networks containing resistor‐inductor, resistor–capacitor and resistor–inductor–capacitor circuits. It is known that DPI function, Z(s), is an analytic function defined on the right half of the s‐plane. In this study, the authors present four theorems using the modulus of the derivative of DPI function, |Z′(0)|, by assuming the Z(s) function is also analytic at the boundary point s=0 on the imaginary axis and finally, the sharpness of the inequalities obtained in the presented theorems are proved. It is also shown that simple inductor–capacitor tank circuits and higher‐order filters are synthesised using the unique DPI functions obtained in each theorem. [ABSTRACT FROM AUTHOR]

This paper characterizes the minimax linear estimator of the value of an unknown function at a boundary point of its domain in a Gaussian white noise model under the restriction that the first-order derivative of the unknown function is Lipschitz continuous. The result is then applied to construct the minimax optimal estimator for the regression discontinuity design model, where the parameter of interest involves function values at boundary points. [ABSTRACT FROM AUTHOR]

Gene selection (or feature selection) from DNA-microarray data can be focused on different techniques, which generally involve statistical tests, data mining and machine learning. In recent years there has been an increasing interest in using hybrid-technique sets to face the problem of meaningful gene selection; nevertheless, this issue remains a challenge. In an effort to address the situation, this paper proposes a novel hybrid framework based on data mining techniques and tuned to select gene subsets, which are meaningfully related to the target disease conducted in DNA-microarray experiments. For this purpose, the framework above deals with approaches such as statistical significance tests, cluster analysis, evolutionary computation, visual analytics and boundary points. The latter is the core technique of our proposal, allowing the framework to define two methods of gene selection. Another novelty of this work is the inclusion of the age of patients as an additional factor in our analysis, which can leading to gaining more insight into the disease. In fact, the results reached in this research have been very promising and have shown their biological validity. Hence, our proposal has resulted in a methodology that can be followed in the gene selection process from DNA-microarray data. [ABSTRACT FROM AUTHOR]