Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

Zhongshan:Embracing New Links

On June 30,2024,the much-anticipated Shenzhen-Zhongshan Link officially began trial operation.The world-class cross-sea cluster project integrating two bridges,two islands,and an underwater tunnel is expected to shorten the driving time from Shenzhen to Zhongshan from two hours to 30 minutes,helping create a 30-minute commute circle across the area.As the flow of innovation factors accelerates through the Shenzhen Zhongshan Link,Zhongshan City has been proactively exploring cooperation models such as“Shenzhen headquarters plus Zhongshan manufacturing,”“Shenzhen leading businesses plus Zhongshan support,”and“Shenzhen R&D plus Zhongshan commercialization”to form a one-hour science and technology industrial cooperation circle with Shenzhen and build a more open,coordinated,and efficient regional innovation system.

电动汽车电控液压制动系统CarSim/Simulink联合仿真研究

针对某款国产电动汽车的电控液压制动系统,文章基于滑移率的比例-积分-微分(PID)控制提出了防抱死制动系统(ABS)模型,以改善车辆制动性能,提高在对开路面上的制动有效性和安全性。首先,使用Simulink软件建立液压电控制动系统的动力学模型;然后,基于滑移率设计PID控制器,并通过1/4车辆模型验证其有效性;最后,利用S函数将ABS控制器的Simulink模型输入CarSim平台中,开展CarSim/Simulink双平台联合控制仿真。结果表明,基于滑移率的PID控制的ABS对比无ABS的车辆,制动性能更加优越,在对开路面上制动稳定性更加明显。

一种MAKLINK图多节点链路建模的路径规划研究

针对传统MAKLINK图规划路径线路改变时,其最优化路径易与环境约束条件冲突的问题,提出了在MAKLINK图中各链路上增加节点数目的方法,以提高系统建模的适应性和鲁棒性。设计的多节点链路通过dijkstra算法得到更为理想的次优化路径,由蚁群算法进行迭代计算获得最优化路径,实现了在保证路径适应度的前提下,提高优化路径对环境约束条件的适应性。实验结果表明,与基本MAKLINK图路径规划算法相比,多节点链路的建模路径规划算法可有效提高次优路径的建模精度,最优路径的适应度值较单节点链路减小了1.43%,具有一定的建模优势。

面向Link16的QualNet与虚拟机信息交互接口设计与实现

Link16是美国国防部采用的高速视距战术数据链,广泛应用于美国海军、联合部队和北约部队,针对其开展测试评估具有重要军事意义。通过硬件在环技术将Link16实物设备接入到仿真测试中,可有效提高测试结果的真实性和准确性。然而当测试场景需要进行实物设备组网测试时,仍会带来成本问题。为此,提出一种面向QualNet MAC层的Link16专属模型以及与之匹配的虚拟机信息交互接口。该模型可高逼真模拟Link16通信行为,实现Link16节点竞争接入、时隙划分、NPG分组等功能。并基于数据分布式服务实现了虚拟机交互接口,将运行在虚拟机的Link16设备模型接入QualNet测试场景。实验测试结果表明,所设计模型具有较高真实性和准确性且接口引入延时不超过1 ms,为大规模数据链网络测试提供一种新方法。

Coherent optical frequency transfer via 972-km fiber link

We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.

一种改进的Link16信号检测方法

直接序列扩频、高速跳频与跳时相结合的技术,造成了对Link16信号的检测具有相当的难度。文中针对突发Link16信号脉冲宽度强规律性,借鉴双滑动窗算法在突发信号检测上的应用,提出了改进后基于相关处理的双滑动窗Link16信号检测方法,该方法可实现复杂电磁环境下对Link16信号的高灵敏度、高概率检测,同时正确估算出脉宽、码速率等参数信息。仿真实验数据验证了理论分析的正确性和所述方法的有效性,相较于其他Link16信号检测方法,改进后的基于相关处理的双滑动窗检测算法明显提高了在低信噪比下对Link16信号的检测能力。

Corneal collagen cross-linking in patients with keratoconus from the Dresden protocol to customized solutions:theoretical basis

Keratoconus is an ectatic condition characterized by gradual corneal thinning,corneal protrusion,progressive irregular astigmatism,corneal fibrosis,and visual impairment.The therapeutic options regarding improvement of visual function include glasses or soft contact lenses correction for initial stages,gas-permeable rigid contact lenses,scleral lenses,implantation of intrastromal corneal ring or corneal transplants for most advanced stages.In keratoconus cases showing disease progression corneal collagen crosslinking(CXL)has been proven to be an effective,minimally invasive and safe procedure.CXL consists of a photochemical reaction of corneal collagen by riboflavin stimulation with ultraviolet A radiation,resulting in stromal crosslinks formation.The aim of this review is to carry out an examination of CXL methods based on theoretical basis and mathematical models,from the original Dresden protocol to the most recent developments in the technique,reporting the changes proposed in the last 15y and examining the advantages and disadvantages of the various treatment protocols.Finally,the limits of non-standardized methods and the perspectives offered by a customization of the treatment are highlighted.

Rainfall Monitoring Using a Microwave Links Network:A Long-Term Experiment in East China

The first long-term rainfall monitoring experiment using the commercial microwave links(CMLs)network in East China is introduced.The network,located in Jiangyin,Jiangsu Province,consists of 49 links with frequencies ranging from 15 GHz to 26 GHz and lengths from 1.14 km to 4.78 km.An OTT PARSIVEL disdrometer is deployed to refine the local rain-induced attenuation relationship,and the CML observations are compared simultaneously with five rain gauges.The inversion parameters of the CML are optimized by minimizing the error of the accumulated rainfall of historical rainfall events.The inversion results show that the daily accumulated rainfall retrieved by the CMLs agrees well with the rain gauge measurements.As an opportunistic approach to monitor near-surface rainfall with high spatiotemporal representativeness and accuracy,the CML network can be used to monitor and forecast urban flood disasters,especially in regions where the widepread deployment of conventional meteorological instruments is impractical.

Percolation transitions in edge-coupled interdependent networks with directed dependency links

We propose a model of edge-coupled interdependent networks with directed dependency links(EINDDLs)and develop the theoretical analysis framework of this model based on the self-consistent probabilities method.The phase transition behaviors and parameter thresholds of this model under random attacks are analyzed theoretically on both random regular(RR)networks and Erd¨os-Renyi(ER)networks,and computer simulations are performed to verify the results.In this EINDDL model,a fractionβof connectivity links within network B depends on network A and a fraction(1-β)of connectivity links within network A depends on network B.It is found that randomly removing a fraction(1-p)of connectivity links in network A at the initial state,network A exhibits different types of phase transitions(first order,second order and hybrid).Network B is rarely affected by cascading failure whenβis small,and network B will gradually converge from the first-order to the second-order phase transition asβincreases.We present the critical values ofβfor the phase change process of networks A and B,and give the critical values of p andβfor network B at the critical point of collapse.Furthermore,a cascading prevention strategy is proposed.The findings are of great significance for understanding the robustness of EINDDLs.

An RVT-based power allocation method for dynamic LEO-MEO links

Optimizing the power resources allocation method of low earth orbit(LEO)satellites to medium earth orbit(MEO)satellite'links is a significant way to construct efficient satellite constellations for satellite communication.A game theory power allocation method based on remaining visible time(RVT)of LEO-MEO satellites is proposed.Firstly,one LEO-MEO satellite network is classified as a cluster in which the RVT of LEO satellites is modeled.Secondly,the cost function of RVT concerning the character of orbit and throughput in each LEO satellite is mainly designed,which gives greater punishment of utility value to LEO satellites with less RVT and is an essential part of the reasonable utility function applied in diverse motion scenes.Meanwhile,the existence of Nash equilibrium for the proposed utility function in game theory area is proved.Thirdly,an off-cluster scheme for LEO satellites through the proposed threshold is raised to ensure the overall utility value of the whole LEO satellites in cluster.Finally,the performance improvement of the proposed algorithm to the baseline algorithm is verified through simulations in different scenarios.

Identification of Key Links in Electric Power Operation Based-Spatiotemporal Mixing Convolution Neural Network

As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately.Therefore,more reliable and accurate security control methods are urgently needed.In order to improve the accuracy and reliability of the operation risk management and control method,this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network.To provide early warning and control of targeted risks,first,the video stream is framed adaptively according to the pixel changes in the video stream.Then,the optimized MobileNet is used to extract the feature map of the video stream,which contains both time-series and static spatial scene information.The feature maps are combined and non-linearly mapped to realize the identification of dynamic operating scenes.Finally,training samples and test samples are produced by using the whole process image of a power company in Xinjiang as a case study,and the proposed algorithm is compared with the unimproved MobileNet.The experimental results demonstrated that the method proposed in this paper can accurately identify the type and start and end time of each operation link in the whole process of electric power operation,and has good real-time performance.The average accuracy of the algorithm can reach 87.8%,and the frame rate is 61 frames/s,which is of great significance for improving the reliability and accuracy of security control methods.

基于GS1 Digital Link的Web编码构建与案例应用

为探索GS1 Digital Link技术在产品物流中的应用潜力,分析研究了GS1系统和GS1 Digital Link的基本结构、编码特点以及技术优势,充分利用GS1 Digital Link技术可以为产品从源头到零售整个物流过程提供相关对象的Web地址编码的特点,以鲜活大闸蟹物流过程为例,构建了基于GS1 Digital Link的鲜活大闸蟹Web编码,为实现产品营销与追溯提供了标准化、动态化、多样化的编码数据支撑。

MDTCNet:Multi-Task Classifications Network and TCNN for Direction of Arrival Estimation

The direction-of-arrival(DoA) estimation is one of the hot research areas in signal processing. To overcome the DoA estimation challenge without the prior information about signal sources number and multipath number in millimeter wave system,the multi-task deep residual shrinkage network(MTDRSN) and transfer learning-based convolutional neural network(TCNN), namely MDTCNet, are proposed. The sampling covariance matrix based on the received signal is used as the input to the proposed network. A DRSN-based multi-task classifications model is first introduced to estimate signal sources number and multipath number simultaneously. Then, the DoAs with multi-signal and multipath are estimated by the regression model. The proposed CNN is applied for DoAs estimation with the predicted number of signal sources and paths. Furthermore, the modelbased transfer learning is also introduced into the regression model. The TCNN inherits the partial network parameters of the already formed optimization model obtained by the CNN. A series of experimental results show that the MDTCNet-based DoAs estimation method can accurately predict the signal sources number and multipath number under a range of signal-to-noise ratios. Remarkably, the proposed method achieves the lower root mean square error compared with some existing deep learning-based and traditional methods.

Time Transfer in a 1839-km Telecommunication Fiber Link Demonstrating a Picosecond-Scale Stability

An implementation of high-precision time transfer over a 1839-km field fiber loop back link between two provincial capitals of China,Xi’an and Taiyuan,is reported.Time transfer stabilities of 6.5 ps at averaging time of 1 s and 4.6 ps at 40000 s were achieved.The uncertainty for the time transfer system was evaluated,showing a budget of 56.2 ps.These results stand for a significant milestone in achieving high-precision time transfer over a field fiber link spanning thousands of kilometers,signifying a record-breaking achievement for the real-field time transfer in both stability and distance,which paves the way for constructing the nationwide high-precision time service via fiber network.

Vital Links

The year 2023 marks the 60th anniversary of the establishment of diplomatic relations between China and Kenya.Over the past 60 years,the two sides have always trusted and respected each other,and closely cooperated in diverse fields.On this important occasion,ChinAfrica interviewed Dennis Munene,executive director of the China-Africa Centre at the Africa Policy Institute,to hear his views on the development of China-Kenya relations.

Robust free-space optical frequency transfer in time-varying link distances conditions

Future inter-satellite clock comparison on high orbit will require optical time and frequency transmission technology between moving objects.Here,we demonstrate robust optical frequency transmission under the condition of variable link distance.This variable link is accomplished by the relative motion of a single telescope fixed on the experimental platform to a corner-cube reflector(CCR)installed on a sliding guide.Two acousto–optic modulators with different frequencies are used to separate forward signal from backward signal.With active phase noise suppression,when the CCR moves back and forth at a constant velocity of 20 cm/s and an acceleration of 20 cm/s^(2),we achieve the best frequency stability of 1.9×10^(-16) at 1 s and 7.9×10^(-19) at 1000 s indoors.This work paves the way for future studying optical frequency transfer between ultra-high-orbit satellites.

Dilation,discrimination and Uhlmann's theorem of link products of quantum channels

We establish the Stinespring dilation theorem of the link product of quantum channels in two different ways,discuss the discrimination of quantum channels,and show that the distinguishability can be improved by self-linking each quantum channel n times as n grows.We also find that the maximum value of Uhlmann's theorem can be achieved for diagonal channels.

基于FANUC系统I/O LINK轴的一种新型垂度补偿功能

由于自身重力的原因,配置多附件头的数控落地镗铣床的滑枕在长行程伸出时会在垂直方向上产生相应的形变。为降低由于形变引入的误差对加工精度所造成的影响,以FANUC 0i MF数控系统作为控制平台,结合I/O LINK轴的应用,提出了一种不使用FANUC系统“平直度补偿”功能的补偿方案。运用区间补偿的思想,将整个滑枕的行程划分为多个运动区间,以误差测量实验的方式将滑枕垂向的误差转换为补偿轴的坐标并得出补偿数据,通过PLC程序将补偿轴坐标与滑枕实际位置进行匹配,以同一运动区间调用固定补偿值的方式对滑枕进行线性补偿。通过对不同的附件头创建不同的补偿程序,并使用K地址调用相应补偿数据的方式,排除了不同补偿数据间相互干扰的隐患。所提方案在实际机床中的应用结果表明:其补偿效果可达到与FANUC系统“平直度补偿”功能相一致的水平。

Underwater Image Classification Based on EfficientnetB0 and Two-Hidden-Layer Random Vector Functional Link

The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a classification model that combines an EfficientnetB0 neural network and a two-hidden-layer random vector functional link network(EfficientnetB0-TRVFL).The features of underwater images were extracted using the EfficientnetB0 neural network pretrained via ImageNet,and a new fully connected layer was trained on the underwater image dataset using the transfer learning method.Transfer learning ensures the initial performance of the network and helps in the development of a high-precision classification model.Subsequently,a TRVFL was proposed to improve the classification property of the model.Net construction of the two hidden layers exhibited a high accuracy when the same hidden layer nodes were used.The parameters of the second hidden layer were obtained using a novel calculation method,which reduced the outcome error to improve the performance instability caused by the random generation of parameters of RVFL.Finally,the TRVFL classifier was used to classify features and obtain classification results.The proposed EfficientnetB0-TRVFL classification model achieved 87.28%,74.06%,and 99.59%accuracy on the MLC2008,MLC2009,and Fish-gres datasets,respectively.The best convolutional neural networks and existing methods were stacked up through box plots and Kolmogorov-Smirnov tests,respectively.The increases imply improved systematization properties in underwater image classification tasks.The image classification model offers important performance advantages and better stability compared with existing methods.