Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

ELLIPTIC EQUATIONS IN DIVERGENCE FORM WITH DISCONTINUOUS COEFFICIENTS IN DOMAINS WITH CORNERS

We study equations in divergence form with piecewise Cαcoefficients.The domains contain corners and the discontinuity surfaces are attached to the edges of the corners.We obtain piecewise C^(1,α) estimates across the discontinuity surfaces and provide an example to illustrate the issue regarding the regularity at the corners.

An angular blinking jamming method based on electronically controlled corner reflectors

Passive jamming is believed to have very good potential in countermeasure community.In this paper,a passive angular blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitude of the incident wave can be modulated by switching the corner reflector between the penetration state and the reflection state,and the ensemble of multiple corner reflectors with towing rope can result in complex angle decoying effects.Dependency of the decoying effect on corner reflectors’radar cross section and positions are analyzed and simulated.Results show that the angle measured by a monopulse radar can be significantly interfered by this method while the automatic tracking is employed.

Topological edge and corner states of valley photonic crystals with zipper-like boundary conditions

We present a stable valley photonic crystal(VPC)unit cell with C_(3v)symmetric quasi-ring-shaped dielectric columns and realize its topological phase transition by breaking mirror symmetry.Based on this unit cell structure,topological edge states(TESs)and topological corner states(TCSs)are realized.We obtain a new type of wave transmission mode based on photonic crystal zipper-like boundaries and apply it to a beam splitter assembled from rectangular photonic crystals(PCs).The constructed beam splitter structure is compact and possesses frequency separation functions.In addition,we construct a box-shaped triangular PC structures with zipper-like boundaries and discover phenomena of TCSs in the corners,comparing its corner states with those formed by other boundaries.Based on this,we explore the regularities of the electric field patterns of TESs and TCSs,explain the connection between the characteristic frequencies and locality of TCSs,which helps better control photons and ensures low power consumption of the system.

Topological laser on square lattice with gain–loss-induced higher-order corner modes

We investigate the higher-order topological laser in the two-dimensional(2D) coupled-cavity array. By adding staggered on-site gain and loss to the 2D Hermitian array with a trivial phase, the system will emerge degenerate topological corner modes, which are protected by bulk band gap. For such a non-Hermitian model, by adjusting the parameters of the system and introducing the pumping into the cavity at the corner, a single-mode lasing with topological protection emerges.Furthermore, single-mode lasing exists over a wide range of pumping strengths. No matter where the cavity is initially stimulated, after enough time evolution, all the cavities belonging to the topological corner mode can emit a stable laser.

The cornerstone of fiber-optic distributed vibration/acoustic sensing: Ф-OTDR

Fiber-optic distributed vibration/acoustic sensing(DVS/DAS) technology achieves breakthrough performance and explores broad cornerstone industrial applications.

Tailoring topological corner states in photonic crystals by near-and far-field coupling effects

We explore the behaviors of optically coupled topological corner states in supercell arrays composed of photonic crystal rods,where each supercell is a second-order topological insulator.Our findings indicate that the coupled corner states possess nondegenerate eigenfrequencies at theΓpoint,with coupled dipole corner states excited resonantly by incident plane waves and displaying a polarization-independent characteristic.The resonance properties of coupled dipole corner states can be effectively modulated via evanescently near-field coupling,while multipole decomposition shows that they are primarily dominated by electric quadrupole moment and magnetic dipole moment.Furthermore,we demonstrate that these coupled corner states can form surface lattice resonances driven by diffractively far-field coupling,leading to a dramatic increase in the quality factor.This work introduces more optical approaches to tailoring photonic topological states,and holds potential applications in mid-infrared topological micro-nano devices.

Closed corner divertor with B×▽B away from the divertor:a promising divertor scenario for tokamak power exhaust

A major challenge facing the steady-state operation of tokamak fusion reactors is to develop a viable divertor solution with order-of-magnitude increase in power handling capability as compared with present experience.A recently developed divertor concept for this end has been tested recently on EAST tokamak through combining the effects of a closed divertor corner and E×B drifts.The E×B drifts in the divertor move particles towards the outer divertor corner area in the scrape-off layer for B×▽B directed away from the divertor,which can significantly enhance the particle concentration there,facilitating divertor detachment.In recent EAST experiments,the effects have been demonstrated where the lowest electron temperature at the divertor plate is obtained with strike point located close to the corner in the horizontal target and with B×▽B away from the divertor.These experimental results are in reasonable agreement with SOLPS-ITER simulations including drift effects,suggesting that the new divertor concept potentially provides a promising divertor solution for long-pulse operations of future tokamak fusion reactors with much higher power fluxes.

DELIVERING THE GOODS China’s courier and logistics sector has thrived in its huge market and become a cornerstone of global supply chains

As China moves to fundamentally improve its virus response by downgrading COVID-19 management to Class B from top-level Class A,one sector that has remained crucial yet bruised by the three-year battle against the disease finally released a sigh of relief.

Passengers gathering-scattering analysis at the corners of subway stations

During both daily operation and emergency evacuation,the corners of walking facilities in subway stations play an important role in efficient circulation.However,the effectiveness of the corner is difficult to assess.In this paper,a method of passenger gathering and scattering analysis based on queueing models was proposed to investigate the corner performance in subway stations.Firstly,we constructed a set of state spaces of passenger flow according to passenger density and proposed the state transition model of passenger flow.Moreover,the model of passenger flow blocking and unblocking probability were also presented.Then,to illustrate the validity of the method and model,several passenger gathering-scattering scenarios and were simulated to verify the influence of passenger distribution and facility width on passenger walking,and the blocking probability,throughput,and expected time were also analyzed under various widths of the target corridor and arrival rates.Results showed that the proposed model can reproduce the trend of walking parameters changing and the self-organizing phenomenon of'faster is lower'.With the increase of arrival rates of passengers,walking speeds of passengers decrease and the expected walking time is prolonged,and the blocking probability sharply increased when the arrival rate exceeded 7 peds/s.In addition,with change of width of the target facility,efficiency of capacity of walking circulation facility fluctuated.With the width of the target corridor enlarged by 10%,the steady state of passenger flow was less crowded.Therefore,corridor width is critical to the circulation efficiency of passengers in subway stations.The conclusions will help to develop reasonable passenger flow control plans to ease the jam and keep passengers walking safely.

CornerNet-Ghost:基于Hourglass-Ghost的轻量型目标检测模型

针对目前工业上目标检测任务较多,却限于设备原因无法流畅运行常规大型目标检测网络,对轻量型目标检测网络需求较大的问题,提出一种新型的轻量化目标检测模型:CornerNet-Ghost。采用特征提取网络Hourglass-Ghost作为骨干网络,对待测物体的左上和右下角点进行检测,并搭配级联角点池化优化提取的角点位置。实验结果表明,CornerNet-Ghost性能超过现有主流的轻量级角点检测网络CornerNet-Squeeze,且在检测计算时间远少于大型网络的条件下达到相近的准确性。

An Incremental Algorithm for Non-Slicing Floorplan Based on Corner Block List Representation

We present a novel incremental algorithm for non-slicing floorplans based on the corner block list representation. The horizontal and vertical adjacency graphs are derived from the packing of the initial floorplanning results. Based on the critical path and the accumulated slack distances we define,we choose the best position for insertion and do a series of operations incrementally, such as deleting modules, adding modules, and resizing modules quickly. This incremental floorplanning algorithm has a very high speed less than 1μm,which is one of the most important measures in this research. The algorithm preserves the original good performances on area and wire length. It can also supply other tools with good physical estimates for area, wire length, and other performance guidelines.

Intel Knights Corner的结点级内存访问优化

传统编程优化(Traditional Programming Optimization,TPO)在Intel Knights Corner(KNC)上收效甚微,因此提出内存访问优化(Memory Access Optimization,MAO)。将MAO应用到已经过TPO的程序Diffusion 3D上,发现其性能仍然提高了39.1%。主要有2个贡献:1)提出MAO,认为TPO+MAO有助于在KNC上获取最优化性能;2)发现对于stencil代码,基于intrinsic的MAO比基于编译器的MAO更高效。这些发现对于在KNC上优化大规模应用有启发意义。

NEW CORNER DETECTION ALGORITHM BASED ON MULTI-FEATURE SYNTHESIS

Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.

TOOL PATH OPTIMIZATION OF POCKET CORNER

In milling around sharp corners, residual materials are left at sharp corners when the stepover is extremely long in the contour-parallel tool path. Milling force at the sharp corner rises momentarily due to the increase of the cutter contact length, thus shortening the tool life and leading to machine chatter, even cutter breakage. Then a tool path improvement method by inserting biarc transition segments in the contour-parallel tool path is proposed for milling the pocket. Using the method, the cutter moves along the biarc transition tool path. And the corner material is removed. The improved tool path is continuous for clearing residual materials at the sharp corner. Finally, the machining experiment validates the proposed method.

A Gridless Router Based on Hierarchical PB Corner Stitching Structure

A multi layer gridless area router is reported.Based on corner stitching,this router adopts tile expansion to explore path for each net.A heuristic method that penalizes nodes deviating from the destination is devised to accelerate the algorithm.Besides,an enhanced interval tree is used to manage the intermediate data structure.In order to improve the completion rate of routing,a new gridless rip up and rerouting algorithm is proposed.The experimental results indicate that the completion rate is improved after the rip up and reroute process and the speed of this algorithm is satisfactory.

GRAPH GRAMMAR METHOD FOR 3-D CORNER DETECTION

Most of local feature descriptors assume that the scene is planar. In the real scene, the captured images come from the 3-D world. 3-D corner as a novel invariant feature is important for the image matching and the object detection, while automatically discriminating 3-D corners from ordinary corners is difficult. A novel method for 3-D corner detection is proposed based on the image graph grammar, and it can detect the 3-D features of corners to some extent. Experimental results show that the method is valid and the 3-D corner is useful for image matching.

An Analysis of College Students’ Learning Motivationin English Corner——Take Xi’An Innovation College of Yan’an University as An Example

There are many factors affecting English learning,and motivation of learner is crucial to it.The purpose of this paper is to explore some measures to stimulate English learning motivation and help college students to learn English better.Based on the investigation of college students’participation in English corner,this paper focuses on the main factors affecting the English learning motivation of Chinese college students.The paper investigates the situation of college students taking part in English corner,and analyzes what is the English learning motivation of college students,based on a questionnaire survey of 180 random students in Xi’an Innovation College of Yan’an University,as well as uses other relevant scholars’ideas for reference.And then it puts forward some efficient measures to promote college students’English learning.

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

This paper presents a corner-based image alignment algorithm based on the procedures of corner-based template matching and geometric parameter estimation. This algorithm consists of two stages: 1) training phase, and 2) matching phase. In the training phase, a corner detection algorithm is used to extract the corners. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. A parabolic function is further applied to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against non-liner light changes. The accuracy and precision of the corner-based image alignment are competitive to that of edge-based image alignment under the same environment. In practice, the proposed algorithm demonstrates its precision, efficiency and robustness in image alignment for real world applications.

机器学习驱动的多Corner STA加速方法

静态时序分析在芯片的物理设计中扮演着重要的作用,其贯穿设计流程始终,耗时巨大,多数时间用于在不同工艺、电压、温度条件下的多Corner组合分析。论文研究多Corner在时序分析方面的相关性并利用机器学习的方法对其进行建模,以利用已知Corner时序结果预测未知Corner时序结果而不需额外的运行时间。实验结果表明,线性模型可以有效地进行预测,在利用7个已知时序结果的Corner预测余下7个未知时序结果的Corner时,能达到2.07ps(1.76%)的平均绝对误差。同时,基于模型的强稳健性,可以采用约束驱动的Corner选取策略,有效地减少多Corner角组合时序分析所需的时间,加速物理设计流程。