Path planning field for autonomous mobile robot is an optimization problem that involves computing a collision-free path between initial location and goal location. In this paper, we present improved artificial potential based regression search (Improved APF-based RS) method which can obtain global sub-optimal/optimal efficiently without local minima oscillations in complete known environment information. We redefine functions to eliminate non-reachable problems, utilize virtual target...

Abstract Facing large-scale and rapidly growing material science literature data, text mining has become a research hotspot of science. In recent years, natural language processing technology machine learning methods have the main technical means in materials The task is to transform unstructured data into structured by information extraction such as Named Entity Recognition entity relationship extraction. This proposes general solution framework for tasks, introduces concepts processes...

Breast cancer is one of the most prevalent cancers in women nowadays, and medical intervention at an early stage can significantly improve prognosis patients. ultrasound (BUS) a widely used tool for screening breast primary care hospitals but it relies heavily on ability experience physicians. Accordingly, we propose knowledge tensor-based Imaging Reporting Data System (BI-RADS)-score-assisted generalized inference model, which uses BI-RADS score senior physicians as gold standard to...

Abstract It has been a hot spot in the area of material science that how to design an experiment produce kind ceramic matrix composites (CMCs) which possesses ideal performances. An approach is build models with data from previous experiments recorded published papers and predict parameters needed by CMCs. According database CMCs funded National Material Genome Engineering, 8 factors were considered affect tensile property CMCs, basis, reinforcement fiber type, volume content, perform...

Due to workload fluctuation in virtualized systems running multiple Virtual Machines (VMs), tenants often allocate more memory than actually used handle peak demands. Memory adjustment by reclaiming inactive VMs is an effective way enable overcommitment so as improve utilization and reduce the cost. However, may increase chance of swapping thus results performance degradation. While prior work has proposed a variety schemes try guarantee workloads, it still remains unexplored disparity...

This paper presented three dimensional (3-D) micro-spheres assembly using chopsticks manipulator. There were two cantilevers in the The driven by piezoelectric ceramic transducer (PZT). was a flexural hinge providing fulcrum cantilevers. rebounding mechanism also included Tungsten tipped probes used to fix grip spheres. CCD sensors, microscopes, and positioning tables integrated experiment setup. stroke of from 0-120 μm. Releasing precision spheres had been controlled accelerated velocity...

With the rapid development of machine learning, it is possible to use neural networks build models predict performance Ceramic Matrix Composites (CMCs) with raw materials and environments. In traditional material science engineering, always took a long time develop new CMC. Furthermore, there still no theoretical basis providing references design experiments CMCs ideal performances. This work proposed model bending strength Convolution Neural Network (CNN) using 8 factors considered affect...

Geographic information system(GIS) methods play an important role in attaching, processing and gathering the elements' data of spatial units. Especially, through combined graphics operation organically, overlapping analyst resolved division from natural elements to administrative evaluate With steady improvement application technology using GIS crop suitability analysis, rapid development computer network, WebGIS has emerged become a hot topic. It's certain trend that existing agricultural...

Traditional Internet real-time communication applications depend on servers deeply, which causes high operation cost and poor efficiency. Moreover, RTP that they use possesses too much redundant information for P2P in the header, occupies a considerable proportion of communication, results great deal unnecessary network traffic communication. This paper proposes implements an efficient transport protocol named Cotton based UDP, is kind simplification improvement RTP. Furthermore, this...

Referring video object segmentation (RVOS), as a supervised learning task, relies on sufficient annotated data for given scene. However, in more realistic scenarios, only minimal annotations are available new scene, which poses significant challenges to existing RVOS methods. With this mind, we propose simple yet effective model with newly designed cross-modal affinity (CMA) module based Transformer architecture. The CMA builds multimodal few samples, thus quickly semantic information, and...

In petroleum exploitation, the frictional resistance has a great influence on cost and speed of horizontal drilling. Support Vector Machine(SVM) is an efficient supervised machine learning method, Regression(SVR) application SVM in function regression. This paper designed friction predictive model by analyzing data The support vector regression used to analyze drilling find out main parameters degree affecting resistance. Compared with results existing nonlinear multivariate models,...