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.

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.

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。

Ambiguity function analysis and side peaks suppression of Link16 signal based passive radar

Link16 data link is the communication standard of the joint tactical information distribution system(JTIDS)used by the U.S.military and North Atlantic Treaty Organization,which is applied as the opportunistic illuminator for passive radar in this paper.The time-domain expression of the Link16 signal is established,and its ambiguity function expression is derived.The timedelay dimension and Doppler dimension side peaks of which lead to the appearance of the false target during target detection.To solve the problem,the time-delay dimension and Doppler dimension side peaks suppression methods are proposed.For the problem that the conventional mismatched filter(MMF)cannot suppress the time-delay dimension side peaks,a neighborhood MMF(NMMF)is proposed.Experimental results demonstrate the effectiveness of the proposed methods.

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.

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.

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.

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.

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.

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。

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.

Enhanced Mechanism for Link Failure Rerouting in Software-Defined Exchange Point Networks

Internet Exchange Point(IXP)is a system that increases network bandwidth performance.Internet exchange points facilitate interconnection among network providers,including Internet Service Providers(ISPs)andContent Delivery Providers(CDNs).To improve service management,Internet exchange point providers have adopted the Software Defined Network(SDN)paradigm.This implementation is known as a Software-Defined Exchange Point(SDX).It improves network providers’operations and management.However,performance issues still exist,particularly with multi-hop topologies.These issues include switch memory costs,packet processing latency,and link failure recovery delays.The paper proposes Enhanced Link Failure Rerouting(ELFR),an improved mechanism for rerouting link failures in software-defined exchange point networks.The proposed mechanism aims to minimize packet processing time for fast link failure recovery and enhance path calculation efficiency while reducing switch storage overhead by exploiting the Programming Protocol-independent Packet Processors(P4)features.The paper presents the proposed mechanisms’efficiency by utilizing advanced algorithms and demonstrating improved performance in packet processing speed,path calculation effectiveness,and switch storage management compared to current mechanisms.The proposed mechanism shows significant improvements,leading to a 37.5%decrease in Recovery Time(RT)and a 33.33%decrease in both Calculation Time(CT)and Computational Overhead(CO)when compared to current mechanisms.The study highlights the effectiveness and resource efficiency of the proposed mechanism in effectively resolving crucial issues inmulti-hop software-defined exchange point networks.

Fault diagnosis method of link control system for gravitational wave detection

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed.Different from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling nonlinearity.By constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault parameters.The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

SHEL:a semantically enhanced hardware-friendly entity linking method

With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.

Mitigating while Accessing:A Lightweight Defense Framework Against Link Flooding Attacks in SDN

Link flooding attack(LFA)is a type of covert distributed denial of service(DDoS)attack.The attack mechanism of LFAs is to flood critical links within the network to cut off the target area from the Internet.Recently,the proliferation of Internet of Things(IoT)has increased the quantity of vulnerable devices connected to the network and has intensified the threat of LFAs.In LFAs,attackers typically utilize low-speed flows that do not reach the victims,making the attack difficult to detect.Traditional LFA defense methods mainly reroute the attack traffic around the congested link,which encounters high complexity and high computational overhead due to the aggregation of massive attack traffic.To address these challenges,we present an LFA defense framework which can mitigate the attack flows at the border switches when they are small in scale.This framework is lightweight and can be deployed at border switches of the network in a distributed manner,which ensures the scalability of our defense system.The performance of our framework is assessed in an experimental environment.The simulation results indicate that our method is effective in detecting and mitigating LFAs with low time complexity.

Update understanding on diagnosis and histopathological examination of atrophic gastritis:A review

Chronic atrophic gastritis(CAG)is a complex syndrome in which long-term chronic inflammatory stimulation causes gland atrophy in the gastric mucosa,reducing the stomach's ability to secrete gastric juice and pepsin,and interfering with its normal physiological function.Multiple pathogenic factors contribute to CAG incidence,the most common being Helicobacter pylori infection and the immune reactions resulting from gastric autoimmunity.Furthermore,CAG has a broad spectrum of clinical manifestations,including gastroenterology and extraintestinal symptoms and signs,such as hematology,neurology,and oncology.Therefore,the initial CAG evaluation should involve the examination of clinical and serological indicators,as well as diagnosis confirmation via gastroscopy and histopathology if necessary.Depending on the severity and scope of atrophy affecting the gastric mucosa,a histologic staging system(Operative Link for Gastritis Assessment or Operative Link on Gastritis intestinal metaplasia)could also be employed.Moreover,chronic gastritis has a higher risk of progressing to gastric cancer(GC).In this regard,early diagnosis,treatment,and regular testing could reduce the risk of GC in CAG patients.However,the optimal interval for endoscopic monitoring in CAG patients remains uncertain,and it should ideally be tailored based on individual risk evaluations and shared decision-making processes.Although there have been many reports on CAG,the precise etiology and histopathological features of the disease,as well as the diagnosis of CAG patients,are yet to be fully elucidated.Consequently,this review offers a detailed account of CAG,including its key clinical aspects,aiming to enhance the overall understanding of the disease.

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。

Link Budget and Enhanced Communication Distance for Ambient Internet of Things

Backscatter communications will play an important role in connecting everything for beyond 5G(B5G)and 6G systems.One open challenge for backscatter communications is that the signals suffer a round-trip path loss so that the communication distance is short.In this paper,we first calculate the communication distance upper bounds for both uplink and downlink by measuring the tag sensitivity and reflection coefficient.It is found that the activation voltage of the envelope detection diode of the downlink tag is the main factor limiting the back-scatter communication distance.Based on this analysis,we then propose to implement a low-noise amplifier(LNA)module before the envelope detection at the tag to enhance the incident signal strength.Our experimental results on the hardware platform show that our method can increase the downlink communication range by nearly 20 m.

Research on Heterogeneous Information Network Link Prediction Based on Representation Learning

A heterogeneous information network,which is composed of various types of nodes and edges,has a complex structure and rich information content,and is widely used in social networks,academic networks,e-commerce,and other fields.Link prediction,as a key task to reveal the unobserved relationships in the network,is of great significance in heterogeneous information networks.This paper reviews the application of presentation-based learning methods in link prediction of heterogeneous information networks.This paper introduces the basic concepts of heterogeneous information networks,and the theoretical basis of representation learning,and discusses the specific application of the deep learning model in node embedding learning and link prediction in detail.The effectiveness and superiority of these methods on multiple real data sets are demonstrated by experimental verification.