A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

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 C1,αestimates across the discontinuity surfaces and provide an example to illustrate the issue regarding the regularity at the corners.

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.

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.

Numerical Study of Co-flow Jet Control on Corner Separation in Compressor Cascade

The design objectives of modern aircraft engines include high load capacity,efficiency,and stability.With increasing loads,the phenomenon of corner separation in compressors intensifies,affecting engine performance and stability.Therefore,the adoption of appropriate flow control technology holds significant academic and engineering significance.This study employs the Reynolds-averaged Navier-Stokes(RANS)method to investigate the effects and mechanisms of active/passive Co-flow Jet(CFJ)control,implemented by introducing full-height and partial height jet slots between the suction surface and end wall of a compressor cascade.The results indicate that passive CFJ control significantly reduces the impact of corner separation at small incidence,with partial-height control further enhancing the effectiveness.The introduction of active CFJ enables separation control at large incidence,improving blade performance under different operating conditions.Active control achieves this by reducing the scale of corner separation vortices,effectively reducing the size of the separation region and enhancing blade performance.

Traffic condition estimation with pre-selection space time model

A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.

A Spectrum Prediction-Based Frequency Band Pre-Selection over Deteriorating HF Electromagnetic Environment

As the earliest invented and utilized communication approach, shortwave, known as high frequency(HF) communication now experience the deterioration of HF electromagnetic environment. Finding quality frequency in efficient manner becomes one of the key challenges in HF communication. Spectrum prediction infers the future spectrum status from history spectrum data by exploring the inherent correlations and regularities. The investigation of HF electromagnetic environment data reveals the correlations and predictability of HF frequency band in both time and frequency domain. To solve this problem, we develop a Spectrum Prediction-based Frequency Band Pre-selection(SP-FBP) for HF communications. The pre-selection of HF frequency band mainly incorporated in prediction of HF spectrum occupancy and prediction of HF usable frequency, which provide the frequency band ranking of spectrum occupancy and alternative frequency for spectrum sensing, respectively. Performance evaluation via real-world HF spectrum data shows that SP-FBP significantly improves the efficiency of finding quality frequency in HF communications.

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.

面向自动驾驶道路场景中异常案例的多模态数据挖掘算法

基于深度学习的视觉感知技术的发展有利于自动驾驶系统中环境感知技术的进步。然而,对于自动驾驶场景中的异常案例,目前的感知模型还存在一些问题。这是因为基于深度学习的感知模型的能力取决于训练数据集的分布。尤其是驾驶场景中的类别从未出现在训练集中,感知系统也往往很脆弱。因此识别未知类别和极端场景仍然是自动驾驶感知技术安全性的挑战。本文从处理数据集的角度出发,提出了一种新颖的多模态异常案例自动挖掘流程(corner case mining pipeline, CCMP)。为验证CCMP的有效性,在Waymo开放数据集的基础上构建了异常案例子集“Waymo-Anomaly”,该子集共有3 200个图像,每个图像都将包含文本中定义的异常案例场景。并且基于私有数据集Waymo-Anomaly,证明了CCMP针对异常案例场景挖掘的召回率可以达到91.7%。此外,还通过实验验证了目标检测器在包含异常案例的数据集中针对长尾分布的有效性。最终,希望从处理数据集的角度来提高自动驾驶感知模型在现实世界中的真实性。

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。

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.

基于灰度均值的自适应FAST角点检测优化算法

光照不均、突变引起的灰度变化会影响图像特征检测效果。为此,设计一种基于灰度均值的自适应FAST-9-12角点检测算法。首先,利用特征点的延展性设计一种小面积双重检测模板,减少像素点与中心点的比较次数,提高区域正检率和检测速度;其次,依据图像局部灰度均值,在每个像素点检测模板内自适应调整阈值,避免灰度变化影响检测效果;最后,根据柔性非极大值抑制的思想设计角点半径抑制原则,筛选鲁棒性更强的角点。在Inria遥感影像数据集上的实验结果表明,FAST-9-12角点检测速度比FAST-12-16,FAST-9-16两种模板提高22%左右,因自适应阈值的提取方式不易受光照影响,检测准确率分别提高4.16和3.11个百分点,实现了图像特征快速和精准检测。

基于机器视觉的芯片字符区域分割和定位算法

芯片表面的字符对分选具有重要意义,对字符的定位是分选工作的关键步骤。为了提高分选工作定位效率和定位精度,提出了一种基于改进的区域生长算法和凸包检测算法分割和定位芯片表面字符区域方法。首先,对采集图像进行预处理操作,利用改进的Canny算法获取无干扰图像边缘,将图像边缘作为区域生长法的种子点并以图像自适应阈值作为生长准则分割图像,使用最大内接矩形算法粗定位字符区域;其次,采用Harris角点检测算法获取字符角点分布位置;最后,筛选角点并提取关键点,利用一种改进的凸包检测算法定位字符区域。经过实验验证,所设计的算法能够完整的分割和定位芯片表面字符区域,定位精度和效率较原有方法提升5.3%和15.4%,满足实际工业生产的要求。

共同结构规范中舭部曲板作为硬角单元的适用条件研究

按照共同结构规范要求,对于船舶舭部板的船体梁极限强度和残存强度计算,规定在一般情况下应将其视为硬角单元,但未明确可以将其视为硬角单元的具体条件。本文利用共同结构规范对于曲板屈曲能力的评估方法和非线性屈曲有限元分析方法,对船舯区域和船舯以外区域的典型几何形状的舭部曲板进行了研究,得到了在共同结构规范要求的船体梁极限强度和残存强度计算中,舭部板可以被视为硬角单元的简要条件。

水下多格弹性角反射体声反射特性及强度增强方法

单格角反射体只能反射一定方向的入射波,为了反射不同方向入射声波,需要构造多格角反射体并研究其声反射特性。以不同类型八格金属板角反射体为对象,基于结构有限元耦合间接边界元法,对水下多格弹性角反射体的散射声场进行数值仿真,分析不同频率、材料、厚度、入射角度等因素影响下不同类型多格角反射体声反射性能,从便于工程应用角度提出增强其声反射能力的方法。通过典型情况下的水池实验,对仿真计算与实验数据的一致性进行验证。实验结果表明:水下多格弹性角反射体目标强度随入射频率增大而增大,并趋向稳定;目标强度随入射角度改变波动幅度较大,不同类型角反射体目标强度值差异较大;目标强度随平板厚度的增加而增大,但不显著;目标强度随着边长的增加而明显增大;软介质材料构成的多格角反射体,水下声反射性能明显优于金属角反射体。因此,为增强水下多格角反射体声反射能力,增大反射体边长及选用低阻抗材料是更有效的方法。