Bidirectional WDM Self-Healing Ring Network for Hub/Remote Nodes

We demonstrate a bidirectional WDM self-healing ring network for hub/remote nodes with one fiber. In this network, self-healing can be achieved within 8 ms. The transmission capacity can be doubled in the operating state.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.

Central corneal epithelium self-healing after ring-shaped glycerin-cryopreserved lamellar keratoplasty in Terrien marginal degeneration

Dear Sir, I am Dr Yan-Long Bi, from the Department of Ophthalmology, Tongji University Affiliated to Tongji University School of Medicine, Shanghai, China. I write to present a case report of total limbal stem cells deficiency after treatment with ring-shaped lamellar keratoplasty secondary to Terrien marginal degeneration. During 3 years

Developing a novel big dataset and a deep neural network to predict the bearing capacity of a ring footing

The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.

An integrated self-healing algorithm for resilient packet ring

Resilient Packet Ring (RPR) is a Media Access Control (MAC) layer protocol that operates over a double counter-rotating ring network topology. RPR is designed to enhance Synchronous Digital Hierarchy(SDH) in order to handle data traffic more efficiently. Since Intelligent Protection Switching(IPS) is one of the key technologies in ring networks, RPR provides two intelligent protection algorithms: steering and wrapping. While wrapping in RPR in essence inherits the automatic protection switching(APS) algorithm of SDH, it also wastes the bandwidth on the wrapping ringlets and may result in severe congestion. Whereas steering in RPR provides high bandwidth utilization, its switching speed is low, because it is indeed a high layer's restoration algorithm. In this paper, integrated self-healing(ISH) algorithm as an effective algorithm for RPR is proposed, which synthesizes the merits of the two algorithms by transporting healing signal and computing routing in MAC layer. At last, the performance of ISH algorithm is analyzed and simulated.

An Average Distance Based Self-Relocation and Self-Healing Algorithm for Mobile Sensor Networks

The sensing coverage of a wireless sensor network is an important measure of the quality of service. It is desirable to develop energy efficient methods for relocating mobile sensors in order to achieve optimum sensing coverage. This paper introduces an average distance based self-relocation and self-healing algorithm for randomly deployed mobile sensor networks. No geo-location or relative location information is needed by this algorithm thereby no hardware such as GPS is required. The tradeoff is that sensors need to move longer distance in order to achieve certain coverage. Simulations are conducted in order to evaluate the proposed relocation and self-healing algorithms. An average of 94% coverage is achieved in the cases that we are examined with or without obstacles.

THE EFFECT OF VP SWITCHES ON THE PERFORMANCE OF BACKUP-VP ALGORITHM IN ATM SELF-HEALING NETWORKS

In this approach, three typical implementation schemes of self-healing function in VP switches are discussed and three corresponding queue models for backup-VP self-healing algorithm are established. Computer simulations are made to these queue models, and detailed analyses are presented to the effect of both the three implementation schemes of self-healing function and some architecture parameters in VP switches on self-healing performance.

A Self-Healing and Nonflammable Cross-Linked Network Polymer Electrolyte with the Combination of Hydrogen Bonds and Dynamic Disulfide Bonds for Lithium Metal Batteries

The self-healing solid polymer electrolytes(SHSPEs)can spontaneously eliminate mechanical damages or micro-cracks generated during the assembly or operation of lithium-ion batteries(LIBs),significantly improving cycling performance and extending service life of LIBs.Here,we report a novel cross-linked network SHSPE(PDDP)containing hydrogen bonds and dynamic disulfide bonds with excellent self-healing properties and nonflammability.The combination of hydrogen bonding between urea groups and the metathesis reaction of dynamic disulfide bonds endows PDDP with rapid self-healing capacity at 28°C without external stimulation.Furthermore,the addition of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide(EMIMTFSI)improves the ionic conductivity(1.13×10^(−4)S cm^(−1)at 28°C)and non-flammability of PDDP.The assembled Li/PDDP/LiFePO_(4)cell exhibits excellent cycling performance with a discharge capacity of 137 mA h g^(−1)after 300 cycles at 0.2 C.More importantly,the self-healed PDDP can recover almost the same ionic conductivity and cycling performance as the original PDDP.

Soft measurement model of ring's dimensions for vertical hot ring rolling process using neural networks optimized by genetic algorithm

Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.

A Ring Signature Suitable for Wireless Sensor Networks

Wireless Sensor Network （WSN） nodes are severely limited by their power, communication bandwidth, and storage space, and the traditional signature algorithm is not suitable for WSN environments. In this paper, we present a ring signature scheme designed for WSNs. In this scheme, all of the wireless sensor nodes are divided into several sub-groups and the sub-group nodes are used to generate the signature instead of the WSN cluster nodes. This scheme can effectively avoid the single node failure problem, and it also has a high availability. All nodes are flee to sign their own message, and the nodes that generate signatures can simultaneously calculate their own part of the signature, meeting the distributed parallel computing requirements. Compared with the traditional ring signature, this scheme reduces the energy consumption, and therefore is very suitable for WSNs.

Synchronizability of Two-Layer Cluster Ring Networks

Multilayer network is a frontier direction of network science research. In this paper, the cluster ring network is extended to a two-layer network model, and the inner structures of the cluster blocks are random, small world or scale-free. We study the influence of network scale, the interlayer linking weight and interlayer linking fraction on synchronizability. It is found that the synchronizability of the two-layer cluster ring network decreases with the increase of network size. There is an optimum value of the interlayer linking weight in the two-layer cluster ring network, which makes the synchronizability of the network reach the optimum. When the interlayer linking weight and the interlayer linking fraction are very small, the change of them will affect the synchronizability.

Prediction of Partial Ring Current Index Using LSTM Neural Network

The local time dependence of the geomagnetic disturbances during magnetic storms indicates the necessity of forecasting the localized magnetic storm indices.For the first time,we construct prediction models for the SuperMAG partial ring current indices(SMR-LT),with the advance time increasing from 1 h to 12 h by Long Short-Term Memory(LSTM)neural network.Generally,the prediction performance decreases with the advance time and is better for the SMR-06 index than for the SMR-00,SMR-12,and SMR-18 index.For the predictions with 12 h ahead,the correlation coefficient is 0.738,0.608,0.665,and 0.613,respectively.To avoid the over-represented effect of massive data during geomagnetic quiet periods,only the data during magnetic storms are used to train and test our models,and the improvement in prediction metrics increases with the advance time.For example,for predicting the storm-time SMR-06 index with 12 h ahead,the correlation coefficient and the prediction efficiency increases from 0.674 to 0.691,and from 0.349 to 0.455,respectively.The evaluation of the model performance for forecasting the storm intensity shows that the relative error for intense storms is usually less than the relative error for moderate storms.

Performance Evaluation and Pseudo-Conservation Laws in Token Ring Network with Batch Arrivals and Limited Services

This paper,using pseudo-conservation laws in cyclic-service systems, derives some expressions for the weighted sum of the mean waiting time token ring networks with exhaustive limitedservice policies on condition that messages arrived with batch Poisson, and discusses boundary conditions. At the same time, the results of the token ring network with exhaustive and non-exhaustiveservice strategy are obtained. Finally the exact expression of mean waiting time in symmetric ringnetwork with same service strategy is given.

Using Neural Network to Predict the Interfacial Friction and Flow Stress of Materials via Ring Compression

In this study a neural network approach is proposed to realize an automatic numerical prediction of the interfacial friction factor and the flow stress of materials. Decrease in the inner diameter and reduction in the height of the ring are taken as input

ORPOM model for optimum distribution of tree ring sampling based on the climate observation network

Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree ring sampling sites based on climate information from the Climate Observation Network(ORPOM model) is presented in this article.In this setup,the tree rings in a typical region are used for surface representation,by applying excellent correlation with the climate information as the main principle.Taking the Horqin Sandy Land in the cold and arid region of China as an example,the optimum distribution range of the tree ring sampling sites was obtained through the application of the ORPOM model,which is considered a reasonably practical scheme.

The Kemeny’s Constant and Spanning Trees of Hexagonal Ring Network

Spanning tree(τ)has an enormous application in computer science and chemistry to determine the geometric and dynamics analysis of compact polymers.In the field of medicines,it is helpful to recognize the epidemiology of hepatitis C virus(HCV)infection.On the other hand,Kemeny’s constant(Ω)is a beneficial quantifier characterizing the universal average activities of a Markov chain.This network invariant infers the expressions of the expected number of time-steps required to trace a randomly selected terminus state since a fixed beginning state si.Levene and Loizou determined that the Kemeny’s constant can also be obtained through eigenvalues.Motivated by Levene and Loizou,we deduced the Kemeny’s constant and the number of spanning trees of hexagonal ring network by their normalized Laplacian eigenvalues and the coefficients of the characteristic polynomial.Based on the achieved results,entirely results are obtained for the M鯾ius hexagonal ring network.

An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

Wireless body area networks(WBANs)are an emerging technology for the real-time monitoring of physiological signals.WBANs provide a mechanism for collecting,storing,and transmitting physiological data to healthcare providers.However,the open wireless channel and limited resources of sensors bring security challenges.To ensure physiological data security,this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption(CP-HRSC)scheme,in which sensors are in a certificateless cryptosystem(CLC)environment,and the server is in a public key infrastructure(PKI)environment.CLC could solve the limitations of key escrow in identity-based cryptography(IBC)and certificate management for public keys in PKI.While PKI is suited for the server because it is widely used on the Internet.Furthermore,this paper designs a ring signcryption method that allows the controller to anonymously encrypt physiological data on behalf of a set of sensors,but the server does not exactly know who the sensor is.The construction of this paper can achieve anonymity,confidentiality,authentication,non-repudiation,and integrity in a logically single step.Under the computational Diffie-Hellman(CDH)problem,the formal security proof is provided in the random oracle model(ROM).This paper demonstrates that this scheme has indistinguishability against adaptive chosen ciphertext attacks(IND-CCA2)and existential unforgeability against adaptive chosen message attacks(EUF-CMA).In terms of computational cost and energy usage,a comprehensive performance analysis demonstrates that the proposed scheme is the most effective.Compared to the three existing schemes,the computational cost of this paper’s scheme is reduced by about 49.5%,4.1%,and 8.4%,and the energy usage of our scheme is reduced by about 49.4%,3.7%,and 14.2%,respectively.

Study of Radio over Fiber Transmission with a Single Line in Ring Topology for Deployment of MIMO Antenna Access Points in a Cell-less Network

The massive growth of wireless traffic goes hand in hand with the deployment of advanced radio interfaces as well as network densification. This growth has a direct impact on the radio access architecture, which today is moving from centralized to distributed deployments through the use of a large number of access points (APs). This paper verifies the feasibility of deploying multiple APs in series on a single line in a ring topology in a cell-less network. On the one hand, this technique will further improve the communication capacity and flexibility of a Radio-over-Fiber (RoF) based mobile communication system and will reduce its construction cost. And on the other hand, this deployment topology is a solution to achieve a massive cell-free Multiple-Input Multiple-Output (MIMO) architecture and a cost-effective fronthaul solution. First, a passive optical add/drop multiplexer (OADM) is used to extract and add downlink and uplink signals from the remote access points of one kilometer. Then, a deployment model is developed with version 17 Optisystem software. The results obtained showed that the quadrature amplitude modulation (QAM) does not adapt to this multi-carrier transmission to deploy several AP in series on a single line. Thus, the performance degradation increases when the number of APs integrated on the line increases.