Circle packings and total geodesic curvatures in hyperbolic background geometry

In this paper, we study a new type of circle packings in hyperbolic background geometry. Horocycles and hypercycles are also considered in this packing. We give the existence and rigidity of this type of circle packing with conical singularities in terms of the total geodesic curvature. Moreover, we introduce the combinatorial curvature flow on surfaces to find the desired circle packing with the prescribed total geodesic curvature

Structural Settlement Analysis and Pre-Reinforcement Research by Considering Structure Stiffness

The movement of the ground caused by the excavation of subway tunnels and the sinking of the earth\u27s surface inevitably affect above-ground buildings, with the impact on historical and cultural buildings, which are already in disrepair, being more prominent. In existing research, the impact of the stiffness of a building itself is often neglected when assessing the influence of the displacement of the stratum caused by tunnel excavation on the building. However, as the settlement and deformation of the building are related to the structural characteristics of the building itself, the effect of the building stiffness should not be completely ignored. This study analyzed the case of the national key protected cultural relics (Red House Hotel) located near the tunnel of the Qingdao Metro (Line 3). Based on the factors affecting the stiffness of the building structure, the Peck empirical formula was modified to predict the effect on the building in the stratum. Subsequently, a three-dimensional finite element model was established and force analysis conducted. Considering the results of the finite element analysis, which determined the stress condition of the cultural relic buildings, a reinforcement design was carried out and implemented in the project

Exploring the factors influencing business model innovation using grounded theory: the case of a Chinese high-end equipment manufacturer

Business model innovation is vitally important for firms to gain competitive advantages and improve their performance. While it has attracted much attention recently, considerable work is still needed to properly understand business model innovation. This study aims to examine the factors influencing business model innovation through a case study of Shaanxi Blower, a high-end equipment manufacturer in China. Using grounded theory in terms of open coding, axial coding and selective coding, this case study found seven main factors that influenced business model innovation, namely, market pressure, government policy, entrepreneurship, culture and strategy, technology, human resources, and organizational capabilities. Market pressure, government policy and information technology are external factors, whereas, entrepreneurship and technological innovation are internal factors. Culture and strategy, human resources, and organizational capabilities are the guarantee factors. This study’s findings add to the growing literature by developing a more holistic understanding of the factors that influence business model innovation in the Chinese context, which indicates a possibility for Chinese high-end equipment manufacturers to improve their competitiveness and performance through better management of their business model innovation. View Full-Tex

Average Consensus in Multiagent Systems with the Problem of Packet Losses When Using the Second-Order Neighbors’ Information

This paper mainly investigates the average consensus of multiagent systems with the problem of packet losses when both the first-order neighbors’ information and the second-order neighbors’ information are used. The problem is formulated under the sampled-data framework by discretizing the first-order agent dynamics with a zero-order hold. The communication graph is undirected and the loss of data across each communication link occurs at certain probability, which is governed by a Bernoulli process. It is found that the distributed average consensus speeds up by using the second-order neighbors’ information when packets are lost. Numerical examples are given to demonstrate the effectiveness of the proposed methods

Hyperbolic Circle Packings and Total Geodesic Curvatures on Surfaces with Boundary

This paper investigates a generalized hyperbolic circle packing (including circles, horocycles or hypercycles) with respect to the total geodesic curvatures on the surface with boundary. We mainly focus on the existence and rigidity of circle packing whose contact graph is the $1$-skeleton of a finite polygonal cellular decomposition, which is analogous to the construction of Bobenko and Springborn [4]. Motivated by Colin de Verdi\`ere's method [6], we introduce the variational principle for generalized hyperbolic circle packings on polygons. By analyzing limit behaviours of generalized circle packings on polygons, we give an existence and rigidity for the generalized hyperbolic circle packing with conical singularities regarding the total geodesic curvature on each vertex of the contact graph. As a consequence, we introduce the combinatoral Ricci flow to find a desired circle packing with a prescribed total geodesic curvature on each vertex of the contact graph.Comment: 26 pages, 7 figure

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation

LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment. Recently, many works project the point cloud onto the 2D image and adopt the 2D Convolutional Neural Networks (CNNs) or vision transformer for LiDAR point cloud semantic segmentation. However, since more than one point can be projected onto the same 2D position but only one point can be preserved, the previous 2D image-based segmentation methods suffer from inevitable quantized information loss. To avoid quantized information loss, in this paper, we propose a novel spherical frustum structure. The points projected onto the same 2D position are preserved in the spherical frustums. Moreover, we propose a memory-efficient hash-based representation of spherical frustums. Through the hash-based representation, we propose the Spherical Frustum sparse Convolution (SFC) and Frustum Fast Point Sampling (F2PS) to convolve and sample the points stored in spherical frustums respectively. Finally, we present the Spherical Frustum sparse Convolution Network (SFCNet) to adopt 2D CNNs for LiDAR point cloud semantic segmentation without quantized information loss. Extensive experiments on the SemanticKITTI and nuScenes datasets demonstrate that our SFCNet outperforms the 2D image-based semantic segmentation methods based on conventional spherical projection. The source code will be released later.Comment: 17 pages, 10 figures, under revie