Nonlinear behavior of a spur gear pair transmission system with backlash

In order to investigate the nonlinear characteristics of gear transmission system under the action of external and internal excitations, a dynamic model of a spur gear pair was established involving the backlash, damping, transmission error and the meshing stiffness. Based on the incremental harmonic balance method (IHBM), the general forms of the periodic solution with arbitrary precision are deduced. The vibration response obtained by IHBM compare very well with the results obtained by New-Mark method, which verifies the accuracy and electiveness of the analytical methodology (IHBM) and provide information on the dynamic characteristic of spur gear. The simulation results revealed that several types of steady-state periodic solution are identified and determined by employing the IHBM. Due to the effect of backlash, the nonlinear characteristics of jump discontinuity phenomena and multiple stable solutions coexist and the meshing impact phenomenon are obvious. In addition, the influences of the system damping, transmission error and excitation amplitude on the amplitude frequency characteristic are illustrated by a series of diagrams. The results implicate that increasing the external excitation amplitude and system damping can effectively decrease the system resonant amplitude and control the nonlinear vibration response of the gear system and the effect of hardening spring behavior becomes weaker. The transmission error excitation amplitude variation also tends to worse the degree of nonlinearity. Therefore, it presents some useful information to reduce the vibration and noise of gear system

Continuity of family of Calder\'on projections

We consider a continuous family of linear elliptic differential operators of arbitrary order over a smooth compact manifold with boundary. Assuming constant dimension of the spaces of inner solutions, we prove that the orthogonalized Calder\'on projections of the underlying family of elliptic operators form a continuous family of projections. Hence, its images (the Cauchy data spaces) form a continuous family of closed subspaces in the relevant Sobolev spaces. We use only elementary tools and classical results: basic manipulations of operator graphs and other closed subspaces in Banach spaces; elliptic regularity; Green's formula and trace theorems for Sobolev spaces; well-posed boundary conditions; duality of spaces and operators in Hilbert space; and the interpolation theorem for operators in Sobolev spaces. \keywords{Calder{\'o}n projection\and Cauchy data spaces \and Elliptic differential operators \and Green's formula\and Interpolation theorem\and Manifolds with boundary\and Parameter dependence \and Trace theorem \and Variational propertie

Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization

Artificial bee colony (ABC) algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum. In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC) algorithm. To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages. Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms

Mapping the scientific research on integrated care: a bibliometric and social network analysis

BackgroundIntegrated care (IC) is the cornerstone of the sustainable development of the medical and health system. A thorough examination of the existing scientific literature on IC is essential for assessing the present state of knowledge on this subject. This review seeks to offer an overview of evidence-based knowledge, pinpoint existing knowledge gaps related to IC, and identify areas requiring further research.MethodsData were retrieved from the Web of Science Core Collection, from 2010 to 2020. Bibliometrics and social network analysis were used to explore and map the knowledge structure, research hotspots, development status, academic groups and future development trends of IC.ResultsA total of 7,501 articles were obtained. The number of publications on IC was rising in general. Healthcare science services were the most common topics. The United States contributed the highest number of articles. The level of collaboration between countries and between authors was found to be relatively low. The keywords were stratified into four clusters: IC, depression, integrative medicine, and primary health care. In recent years, complementary medicine has become a hotspot and will continue to be a focus.ConclusionThe study provides a comprehensive analysis of global research hotspots and trends in IC, and highlights the characteristics, challenges, and potential solutions of IC. To address resource fragmentation, collaboration difficulties, insufficient financial incentives, and poor information sharing, international collaboration needs to be strengthened to promote value co-creation and model innovation in IC. The contribution of this study lies in enhancing people’s understanding of the current state of IC research, guiding scholars to discover new research perspectives, and providing valuable references for researchers and policymakers in designing and implementing effective IC strategies

Exploiting Shopping and Reviewing Behavior to Re-score Online Evaluations

Analysis to product reviews has attracted great attention from both academia and industry. Generally the evaluation scores of reviews are used to generate the average scores of products and shops for future potential users. However, in the real world, there is the inconsistency problem between the evaluation scores and review content, and some customers do not give out fair reviews. In this work, we focus on detecting the credibility of customers by analyzing online shopping and review behaviors, and then we re-score the reviews for products and shops. In the end, we evaluate our algorithm based on the real data set from Taobao, the biggest E-commerce site in China

PLDS-SLAM: Point and Line Features SLAM in Dynamic Environment

Visual simultaneous localization and mapping (SLAM), based on point features, achieves high localization accuracy and map construction. They primarily perform simultaneous localization and mapping based on static features. Despite their efficiency and high precision, they are prone to instability and even failure in complex environments. In a dynamic environment, it is easy to keep track of failures and even failures in work. The dynamic object elimination method, based on semantic segmentation, often recognizes dynamic objects and static objects without distinction. If there are many semantic segmentation objects or the distribution of segmentation objects is uneven in the camera view, this may result in feature offset and deficiency for map matching and motion tracking, which will lead to problems, such as reduced system accuracy, tracking failure, and track loss. To address these issues, we propose a novel point-line SLAM system based on dynamic environments. The method we propose obtains the prior dynamic region features by detecting and segmenting the dynamic region. It realizes the separation of dynamic and static objects by proposing a geometric constraint method for matching line segments, combined with the epipolar constraint method of feature points. Additionally, a dynamic feature tracking method based on Bayesian theory is proposed to eliminate the dynamic noise of points and lines and improve the robustness and accuracy of the SLAM system. We have performed extensive experiments on the KITTI and HPatches datasets to verify these claims. The experimental results show that our proposed method has excellent performance in dynamic and complex scenes