基于GAN和MS-ResNet的房颤自动检测模型

房颤是一种常见的心律失常疾病,针对现有研究工作大多依赖于单尺度信号段而忽略了不同尺度下潜在的互补信息和数据不平衡问题导致诊断性能下降的问题,提出了一种新颖的基于生成对抗网络(generative adversarial network, GAN)和多尺度残差网络(multiscale residual net, MS-ResNet)的房颤自动检测模型,该网络使用GAN合成具有高形态相似性的单导联心电数据来解决数据的隐私和不平衡问题。同时,设计了MS-ResNet特征提取策略,从不同尺度提取不同大小信号段的特征,从而有效地捕捉P波消失和RR间期不规则特征。该模型联合这两种策略不仅为房颤自动检测生成高质量心电图(electrocardiogram,ECG)数据,还可以利用多尺度网格提取不同波之间的时序特征。在PhysioNet Challenge2017公开ECG数据集上以及平衡后的数据集上评估了MS-ResNet的性能,并将其与现有的房颤分类模型进行了比较。实验结果表明,MS-ResNet在平衡后的数据集上平均F1值和精确率分别达到0.914 1和91.56%,与不平衡数据集相比,F1提高了4.5%,精确率提高了3.5%。

用Network Meta分析系统评价GLP-1受体激动剂类降糖药的心血管安全性

目的使用Network Meta分析系统评价胰高血糖素样肽1(GLP-1)受体激动剂类降糖药的心血管安全性。方法系统检索Medline、Embase、Clinical Trials.gov和Cochrane Library数据库(截止2011年10月)中比较GLP-1受体激动剂与其他降糖药物或安慰剂的心血管安全性的随机对照研究(RCT),采用传统Meta分析和NetworkMeta分析方法对纳入的RCT的研究结果进行合并。结果共纳入45项研究,15883例糖尿病患者,包括八种干预措施(六种GLP-1类药:艾塞那肽、利拉鲁肽、他司鲁肽、阿必鲁肽、利西拉来和LY2189265,以及安慰剂和传统降糖药),研究总臂数为95。传统Meta分析和Network Meta分析结果相近,均未显示GLP-1受体激动剂与其他降糖药物或安慰剂之间心血管疾病安全性有统计学差异(P均>0.05)。此外,结合直接和间接比较的Network Meta分析显示六种GLP-1类药之间两两比较的心血管安全性也均无统计学差异(P均>0.05)。基于贝叶斯理论的Network Meta分析可对八种干预措施进行排序,显示安慰剂心血管风险最大。结论尽管单个研究报道GLP-1类药有潜在的心血管保护效应,但目前Network Meta分析仍无法定论,仍有待专门设计的大型前瞻性研究加以验证。

Mapping the small-world properties of brain networks in Chinese to English simultaneous interpreting by using functional near-infrared spectroscopy

The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS neuroimaging combined with complex network analysis wasperformed to extract the features of functional brain networks underling three translationstrategies associated with Chinese to English SI:"transcoding"that takes the"shortcut"linkingtranslation equivalents between Chinese and the English,code-mixing"that basically does notinvolve blingual procesing,and"transphrasingn that takes the long route"involving amonolingual processing of meaning in Chinese and then another monolingual processing ofmeaning in English.Our results demonstrated that the small-world net work topology was able todistinguish well bet ween the transcoding,code-mixing and transphrasing strategies related toChinese to English SI.

基于3D-ResNet双流网络的VR病评估模型

为了准确地评估VR视频引起不适的程度,提出基于3D双流卷积神经网络的VR病评估模型.模仿人类视觉系统的2条通路,建立外观流和运动流2个子网络;将2D-ResNet50模型改为3D模型,增加一个深度通道,用以学习视频中的时序信息.加入3D-CBAM注意力模块提高了各帧通道之间的空间关联,增强关键信息,去除冗余信息.采用后端融合的方法,实现2个子网络结果的融合.在公开视频数据集上进行实验验证,结果表明,通过3D-CBAM注意力模块引入注意力机制,使得外观流和运动流网络的VR病评估精度分别提升了1.7%和3.6%,与现有文献相比,融合的双流网络模型的精度得到了较大的提升,精度达到93.7%.

Heuristic Solutions of Virtual Network Embedding： A Survey

Network virtualization(NV) is considered as an enabling tool to remove the gradual ossification of current Internet. In the network virtualization environment, a set of heterogeneous virtual networks(VNs), isolated from each other, share the underlying resources of one or multiple substrate networks(SNs) according to the resource allocation strategy. This kind of resource allocation strategy is commonly known as so called Virtual Network Embedding(VNE) algorithm in network virtualization. Owing to the common sense that VNE problem is NP-hard in nature, most of VNE algorithms proposed in the literature are heuristic. This paper surveys and analyzes a number of representative heuristic solutions in the literature. Apart from the analysis of representative heuristic solutions, a taxonomy of the heuristic solutions is also presented in the form of table. Future research directions of VNE, especially for the heuristics, are emphasized and highlighted at the end of this survey.

Satellite Constellation Design with Multi-Objective Genetic Algorithm for Regional Terrestrial Satellite Network

Constellations design for regional terrestrial-satellite network can strengthen the coverage for incomplete terrestrial cellular network. In this paper, a regional satellite constellation design scheme with multiple feature points and multiple optimization indicators is proposed by comprehensively considering multi-objective optimization and genetic algorithm, and "the Belt and Road" model is presented in the way of dividing over 70 nations into three regular target areas. Following this, we formulate the optimization model and devise a multi-objective genetic algorithm suited for the regional area with the coverage rate under simulating, computing and determining. Meanwhile, the total number of satellites in the constellation is reduced by calculating the ratio of actual coverage of a single-orbit constellation and the area of targets. Moreover, the constellations' performances of the proposed scheme are investigated with the connection of C++ and Satellite Tool Kit(STK). Simulation results show that the designed satellite constellations can achieve a good coverage of the target areas.

A TCP Performance Enhancement Scheme in Infrastructure based Vehicular Networks

Transmission Control Protocol(TCP) in infrastructure based vehicular networks is dedicated to support reliable Internet services for mobile users.However,an end-toend TCP flow not only experiences some common challenges in wireless mobile networks,such as high packet loss rate,medium access competition,unstable wireless bandwidth,and dynamic topology,etc.,but also suffers from performance degradation due to traffic congestion at the Road-Side Units(RSUs) that connect the wireline and wireless networks.In order to address the challenging issues related to reliable TCP transmissions in infrastructure based vehicular networks,we propose an RSU based TCP(R-TCP) scheme.For wireline source nodes,R-TCP adopts a novel flow control mechanism to adjust transmission rates according to the status of bottleneck link.Specifically,during the short wireless connection time in Infrastructure based vehicular networks,R-TCP quickly chooses an ideal transmission rate for data transmissions instead of activating the slow start algorithm after the connection is established,and successfully avoids the oscillation of the transmission rate.Simulation results show that R-TCP achieves great advantages than some relate proposals in terms of throughput,end-to-end delay,and packet loss rate.

Topology Discovery Sub-Layer for Integrated Terrestrial-Satellite Network Routing Schemes

With the booming development of terrestrial network, scaling terrestrial network over satellite network to build Integrated Terrestrial-Satellite Network(ITSN) and meanwhile to provide the global Internet access, has become ever more attractive. Naturally, the widely and successfully used terrestrial routing protocols are the promising protocols to integrate the terrestrial and satellite networks. However, the terrestrial routing protocols, which rely on propagating routing messages to discover New Network Topology(NNT) in the terrestrial network with rare topology changes, will suffer from overly numerous routing messages in satellite network whose topology frequently changes as satellites move. In this paper, a Topology Discovery Sub-layer for ITSN Routing Schemes(TDS-IRS) is firstly proposed to avoid the propagation of numerous routing messages by taking advantage of the movement predictability of satellite and the requirements of routing schemes to discover NNT in advance of topology change. Secondly, a Weighted Perfect Matching based Topology Discovery(WPM-TD) model is designed to conduct the NNT discovery on the ground. Thirdly, this paper builds a testbed with real network devices and meanwhile interconnect that testbed with real Internet, to validate that RS-TDS can discover NNT immediately with the less on-board overhead compared with optimized routing schemes. Finally, different network scenarios are applied to validate the WPM-TD, i.e., the core module of TDS-IRS. Extensive experiments show WPM-TD can work efficiently, avoiding the invalid NNT discovery and decreasing 20% ~ 57% of potential topology changes, which can also improve up to 47% ~ 105% of network throughput.

A Combining Call Admission Control and Power Control Scheme for D2D Communications Underlaying Cellular Networks

As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or throughput are regarded as optimization criterion. In this paper, a combining call admission control(CAC) and power control scheme under guaranteeing QoS of every user equipment(UE) is proposed. First, a simple CAC scheme is introduced. Then based on the CAC scheme, a combining call admission control and power control scheme is proposed. Next, the performance of the proposed scheme is evaluated. Finally, maximum DUE pair number and average transmitting power is calculated. Simulation results show that D2 D communications with the proposed combining call admission control and power control scheme can effectively improve the maximum DUE pair number under the premise of meeting necessary QoS.

Impacts of Packet Collisions on Link Throughput in CSMA Wireless Networks

It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network(ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network(EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.

IUKF neural network modeling for FOG temperature drift

A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.

Orchestrating Network Functions in Software-Defined Networks

Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently.

Optimization of Laser Ablation Technology for PDPhSM Matrix Nanocomposite Thin Film by Artificial Neural Networks-particle Swarm Algorithm

A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle （PDPhSM） thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions.

Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm

In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.

The Impact of Delay in Software-Defined Integrated Terrestrial-Satellite Networks

Satellite communication networks have been evolving from standalone networks with ad-hoc infrastructures to possibly interconnected portions of a wider Future Internet architecture. Experts belonging to the fifth-generation(5 G) standardization committees are considering satellites as a technology to integrate in the 5 G environment. Software Defined Networking(SDN) is one of the paradigms of the next generation of mobile and fixed communications. It can be employed to perform different control functionalities, such as routing, because it allows traffic flow identification based on different parameters and traffic flow management in a centralized way. A centralized set of controllers makes the decisions and sends the corresponding forwarding rules for each traffic flow to the involved intermediate nodes that practically forward data up to the destination. The time to perform this process in integrated terrestrial-satellite networks could be not negligible due to satellite link delays. The aim of this paper is to introduce an SDN-based terrestrial satellite network architecture and to estimate the mean time to deliver the data of a new traffic flow from the source to the destination including the time required to transfer SDN control actions. The practical effect is to identify the maximum performance than can be expected.

Incorporating Network Coding into TCP Grounded on Network Utility Maximization in Multi-Radio Multi-Channel Wireless Mesh Networks

A new approach, named TCP-I2NC, is proposed to improve the interaction between network coding and TCP and to maximize the network utility in interference-free multi-radio multi-channel wireless mesh networks. It is grounded on a Network Utility Maxmization (NUM) formulation which can be decomposed into a rate control problem and a packet scheduling problem. The solutions to these two problems perform resource allocation among different flows. Simulations demonstrate that TCP-I2NC results in a significant throughput gain and a small delay jitter. Network resource is fairly allocated via the solution to the NUM problem and the whole system also runs stably. Moreover, TCP-I2NC is compatible with traditional TCP variants.

Secure Data Aggregation Approach Based on Monitoring in Wireless Sensor Networks

In order to avoid internal attacks during data aggregation in wireless sensor networks, a grid-based network architecture fit for monitoring is designed and the algorithms for network division, initialization and grid tree construction are presented. The characteristics of on-off attacks are first studied and monitoring mechanisms are then designed for sensor nodes. A Fast Detection and Slow Recovery (FDSR) algorithm is proposed to prevent on-off attacks by observing the behaviors of the nodes and computing reputations. A recovery mechanism is designed to isolate malicious nodes by identifying the new roles of nodes and updating the grid tree. In the experiments, some situations of on-off attacks are simulated and the results are compared with other approaches. The experimental results indicate that our approach can detect malicious nodes effectively and guarantee secure data aggregation with acceptable energy consumption.

Adaptive coupled synchronization of non-autonomous systems in ring networks

The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotical synchronization for a general coupling ring network with N identical non-autonomous systems~ even when N is large enough. Strict theoretical proofs are given. Numerical simulations illustrate the effectiveness of the present method.