Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Evolutionary game dynamics of combining two different aspiration-driven update rules in structured populations

In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.

An Updated Lagrangian Particle Hydrodynamics (ULPH)-NOSBPD Coupling Approach forModeling Fluid-Structure Interaction Problem

A fluid-structure interaction approach is proposed in this paper based onNon-Ordinary State-Based Peridynamics(NOSB-PD)and Updated Lagrangian Particle Hydrodynamics(ULPH)to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid.In the coupled framework,the NOSB-PD theory describes the deformation and fracture of the solid material structure.ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy.The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid problems,with good computational stability and robustness.A fluidstructure coupling algorithm using pressure as the transmission medium is established to deal with the fluidstructure interface.The dynamic model of solid structure and the PD-ULPH fluid-structure interaction model involving large deformation are verified by numerical simulations.The results agree with the analytical solution,the available experimental data,and other numerical results.Thus,the accuracy and effectiveness of the proposed method in solving the fluid-structure interaction problem are demonstrated.The fluid-structure interactionmodel based on ULPH and NOSB-PD established in this paper provides a new idea for the numerical solution of fluidstructure interaction and a promising approach for engineering design and experimental prediction.

Updated Lagrangian Particle Hydrodynamics (ULPH)Modeling of Natural Convection Problems

Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat transfer,climate,and fluid mixing in industrial processes.This work aims to use the Updated Lagrangian Particle Hydrodynamics(ULPH)theory to address natural convection problems.The Navier-Stokes equation is discretized using second-order nonlocal differential operators,allowing a direct solution of the Laplace operator for temperature in the energy equation.Various numerical simulations,including cases such as natural convection in square cavities and two concentric cylinders,were conducted to validate the reliability of the model.The results demonstrate that the proposed model exhibits excellent accuracy and performance,providing a promising and effective numerical approach for natural convection problems.

Scoping review update on somatic symptom disorder that includes additional Chinese data

Somatic symptom disorder(SSD)is a new diagnosis introduced into the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),which is expected to solve the diagnostic difficulties of patients with medically unexplained symptoms.Based on the previous work,this review aims to comprehensively synthesise updated evidence related to SSD from recent years in English publications and,more extensively,from data published in Chinese language journals.The scoping review update was based on an earlier scoping review and included Chinese language publication data from China National Knowledge Internet(CNKI),WANFANG and WEIPU between January 2013 and May 2022 and data from PubMed,PsyclNFO,and Cochrane Library between June 2020 and May 2022.Initially,2984 articles were identified,of which 63 full texts were included for analysis.In China,SSD is mainly applied in scientific research,but it also shows good predictive validity and clinical application potential.The mean frequency of SSD was 4.5%in the general population,25.2%in the primary care population and 33.5%in diverse specialised care settings.Biological factors,such as brain region changes and heart rate variability,are associated with the onset of sSD.Psychological impairment related to somatic symptoms is the best predictor of prognosis.While adolescent SSD is significantly associated with family function,SSD overall is associated with an increased dysfunction of cognition and emotion,decreased quality of life,and high comorbidity with anxiety and depressive disorders.Further research is needed on suicide risk and cultural and gender-related issues.Updating the data of Chinese language studies,our research enriches the evidence-based findings related to the topics addressed in the text sections of the SSD chapter of DSM-5.However,research gaps remain about SSD reliability,population-based prevalence,suicide risk,and cultural and gender-related issues.

Updates in the Diagnosis of Gestational Trophoblast Disease

GTD (Gestational Trophoblastic Disease) is a pathology that encompasses benign and malignant clinical forms, affects women of childbearing age, has a variable incidence and is more frequent in developing or underdeveloped countries, colliding with the economic barrier. The frequent absence of clear protocols and guidelines for the correct diagnosis of the pathology results in inadequate classification, imprecise treatment and failed post-therapeutic observation, increasing the risk of relapses, morbidity and mortality. The present study aims to point out updated national and international practice protocols of diagnosis of GTD, through an integrative review. Seven articles were selected and it was observed that the main international reference centers are agreed with the management suggested by the IFGO (International Federation of Gynecology and Obstetrics), being the conduct in the Hydatidiform Mole (HM): evacuation by suction and curettage under ultrasound guidance, followed by hCG monitoring every 1 - 2 weeks until normalized (usually one month for Partial Hydatidiform Mole six months for Complete Hydatidiform Mole and one year for Gestational Trophoblastic Neoplasia). Unfortunately, regarding the diagnosis of MH, the guidelines of some countries show the absence or difficulty of access to the karyotype test and ploid p57 or pelvic ultrasound accompanying the uterine curettage, contrary to what is proposed by the IFGO guideline. Establishing and complying with consistent guidelines can improve patient care, with early diagnosis of the pathology and its complications, reducing the rate of recurrence, morbidity and mortality, especially in less developed countries.

基于改进UpdateNet的行人视觉跟踪算法

目前,基于孪生网络的跟踪器主要是把跟踪过程看作是目标模板分支和待检测区域分支的一种互相关计算,它能够在速度和精度方面达到一个良好的均衡。然而,在跟踪过程中当前帧模板是对前一帧累积模板的线性结合,目标遮挡的问题一直很难被解决。针对该问题,本文采用改进SiamRPN跟踪器并融合UpdateNet网络的方案实现对行人单目标的跟踪。首先利用改进SiamRPN网络模块生成线性模板,然后在此基础上融合UpdateNet网络生成更新模板并进行多阶段训练,最后根据数据集的评价指标选取最优参数模型完成行人跟踪任务。本文在基准数据集OTB2015和其子集上进行实验,实验结果表明,本文所采用的方法取得的效果相比原来方法有明显提升,精度和成功率分别提高2.1和1.6个百分点,而且保持了实时跟踪帧率,同时在解决遮挡问题方面超过了DaSiamRPN、SiamDW等先进方法.

Inference of interactions between players based on asynchronously updated evolutionary game data

The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the game.The strategies of each player are updated asynchronously during the game.Two inference methods of the interactions between players are derived with naive mean-field(n MF)approximation and maximum log-likelihood estimation(MLE),respectively.Two methods are tested numerically also for fully connected asymmetric Sherrington-Kirkpatrick models,varying the data length,asymmetric degree,payoff,and system noise(coupling strength).We find that the mean square error of reconstruction for the MLE method is inversely proportional to the data length and typically half(benefit from the extra information of update times)of that by n MF.Both methods are robust to the asymmetric degree but work better for large payoffs.Compared with MLE,n MF is more sensitive to the strength of couplings and prefers weak couplings.

Health Data Availability Protection:Delta-XOR-Relay Data Update in Erasure-Coded Cloud Storage Systems

To achieve the high availability of health data in erasure-coded cloud storage systems,the data update performance in erasure coding should be continuously optimized.However,the data update performance is often bottlenecked by the constrained cross-rack bandwidth.Various techniques have been proposed in the literature to improve network bandwidth efficiency,including delta transmission,relay,and batch update.These techniques were largely proposed individually previously,and in this work,we seek to use them jointly.To mitigate the cross-rack update traffic,we propose DXR-DU which builds on four valuable techniques:(i)delta transmission,(ii)XOR-based data update,(iii)relay,and(iv)batch update.Meanwhile,we offer two selective update approaches:1)data-deltabased update,and 2)parity-delta-based update.The proposed DXR-DU is evaluated via trace-driven local testbed experiments.Comprehensive experiments show that DXR-DU can significantly improve data update throughput while mitigating the cross-rack update traffic.

System Reliability Analysis for Truss Structures Based on Automatic Updated Model

Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.

Fast Verification of Network Configuration Updates

With the expansion of network services,large-scale networks have progressively become common.The network status changes rapidly in response to customer needs and configuration changes,so network configuration changes are also very frequent.However,no matter what changes,the network must ensure the correct conditions,such as isolating tenants from each other or guaranteeing essential services.Once changes occur,it is necessary to verify the after-changed network.Whereas,for the verification of large-scale network configuration changes,many current verifiers show poor efficiency.In order to solve the problem ofmultiple global verifications caused by frequent updates of local configurations in large networks,we present a fast configuration updates verification tool,FastCUV,for distributed control planes.FastCUV aims to enhance the efficiency of distributed control plane verification for medium and large networks while ensuring correctness.This paper presents a method to determine the network range affected by the configuration change.We present a flow model and graph structure to facilitate the design of verification algorithms and speed up verification.Our scheme verifies the network area affected by obtaining the change of the Forwarding Information Base(FIB)before and after.FastCUV supports rich network attributes,meanwhile,has high efficiency and correctness performance.After experimental verification and result analysis,our method outperforms the state-of-the-art method to a certain extent.

Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut(2018)Prediction

In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillations introduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and life histories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme is proposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.For each scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.The results demonstrate the superiority of the multi-scale IAU scheme.

基于实测数据的半潜式平台贝叶斯模型修正方法研究

随着半潜式平台的长期海上服役,平台的基本设计参数会发生变化,如仍基于原始设计参数对平台进行分析将影响结果的准确性。本文以半潜式平台服役中易发生变化的基本参数(平台排水量、重心高度和三个自由度回转半径)作为修正参数,以平台横摇、纵摇和垂荡自由度的方差和波频功率谱密度构建目标函数,建立可依据实测数据的半潜式平台贝叶斯参数修正方法。以我国某半潜式平台实测数据为例,开展平台的参数修正研究,并基于修正后的参数对平台多年一遇环境荷载下的响应进行对比评估。

基于多源数据融合的水利工程测量信息动态更新系统

现有的水利工程测量信息动态更新系统,在传输测量信息时没有最佳的路径概念,采用车轮搜索,导致信息更新所需时间较长,为优化系统运行效率,设计基于多元数据融合设计水利工程测量信息动态更新系统。设计可以增强数据更新速度的芯片作为系统硬件;构造有效路径代价函数,整编水利工程测量多源数据;选择数据传输最短路径;建立最小二乘估计数学模型,引入多元数据融合设计信息更新算法。实验结果显示:在系统更新时间的测试中,面对不同数量的并行服务器,三个对照组用时均高于实验组,可见该系统具备更好的运行效率。

计及采样扰动抑制的电压源逆变器三矢量无模型预测电流控制方法

针对传统电压源逆变器无模型预测电流控制(model-free predictive current control,MFPCC)方法存在电流纹波大、电流梯度更新停滞以及预测性能易受采样扰动影响的问题。该文提出一种计及采样扰动的三矢量MFPCC方法。在一个控制周期应用3个基本矢量,并根据价值函数计算矢量作用时间,降低了输出电流纹波;其次,通过建立不同矢量作用下的电流梯度方程组,实现电流梯度数据的实时更新,消除了停滞现象;再次,分析采样扰动对MFPCC的影响,采用扩张状态观测器估计采样扰动以补偿预测电流控制,抑制其对输出电流的影响。最后,通过仿真和实验,对所提方法的有效性进行了验证。

中国新型基础设施建设:统计测度及产业结构升级效应

系统梳理新基建的主要领域,重塑新基建的测度指标体系,在考察2017—2021年中国新基建水平及特征的基础上,探讨新基建对产业结构升级的影响。研究发现:党的十九大以来,中国新基建水平实现跨越式提升,有效提振了国内需求并推动了数字化转型工作;目前融合基础设施、创新基础设施是部署新基建的主要堵点和难点;随着区域协调发展战略的贯彻落实,近年来新基建的地区差距有所缓解,在区域一体化水平日益提高的基础上应进一步加强区域间的协同联动;新基建可显著促进产业结构升级,且考察期内随时间推移这种正向促进效应愈加明显。

结合Cokriging模型和单目标函数的随机模型修正

将Cokriging代理模型技术和单目标函数进行结合,提出了一种随机模型修正方法。该方法将不确定性模型修正问题转化为较简单的待修正参数统计特征的修正问题,能够在保证模型修正精度的同时,有效缓解模型修正中由于分步修正和多目标修正造成的计算成本高的问题。首先,假设待修正参数和响应均服从高斯分布,采用拉丁超立方抽样获取训练集样本,构造满足精度要求的Cokriging模型替代复杂的有限元模型参与迭代计算。然后,建立有限元模型计算响应统计特征与试验响应统计特征的加权残差目标函数,引入土狼优化算法最小化该单目标函数来得到待修正参数的统计特征。最后,通过二维和三维桁架结构验证了所提方法的可行性。

价值网络视角下跨界整合对企业创新绩效的影响——组织柔性的中介效应

在数字经济背景下,跨界创新成为企业新的创新范式。跨界整合对于企业顺利实施跨界创新战略极为关键。现有研究关注跨界整合产生的影响,但对于企业如何在跨界整合过程中通过调整组织结构与惯例影响创新绩效的机制探讨不足。基于价值网络视角,以358家企业为研究对象,采用层次回归分析方法检验跨界整合对企业创新绩效的影响机制以及组织柔性的中介作用。研究发现:①跨界资源价值识取与跨界资源价值配用作为跨界整合的两个维度对企业创新绩效具有显著正向影响;②组织结构柔性和惯例更新在跨界整合与创新绩效之间发挥显著中介作用。厘清跨界整合不同维度对创新绩效的作用,验证“跨界整合—组织柔性—创新绩效”影响路径,可深化既有理论对跨界整合作用的认知,对于企业跨界创新战略实施具有重要指导意义。

基于MEC边缘云的智慧商城数据更新控制算法

针对智慧商城中数据量较大的问题,提出基于MEC边缘云的智慧商城数据更新控制算法。在MEC边缘云环境中将数据信息经过整合分类处理后直接推送至用户端,将万有引力搜索算法和布谷鸟搜索算法融合构建CS-GSA算法,用于MEC边缘云智慧商城数据库数据清洗。在差分数据更新方法中引入游程编码和哈夫曼编码,采用游程编码将连续重复的数据压缩处理,降低数据规模,然后通过哈夫曼编码再次压缩,降低传输过程中的通信开销,实现MEC边缘云智慧商城数据更新。实验结果表明,所提方法的解编码时间、数据更新时间更短、通信开销较小,说明其能够提高数据更新质量。

桅杆结构有限元模型修正与参数敏感性研究

基于台风“圆规”激励下的实测加速度响应识别了深圳356 m高气象梯度观测塔的模态参数,结合带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)对气象塔有限元模型进行修正。结果表明:气象塔模态非常密集,且纤绳模态的参与程度较为显著。气象塔X向和Y向的基频分别为0.614 Hz和0.603 Hz,其前3阶弯曲模态阻尼比在1%~2%之间。塔身密度、纤绳弹模对塔身模态频率和振型有显著影响,高层纤绳的线质量和塔身弹模对其也有一定影响,但纤绳张力的影响较低。气象塔有限元模型修正后的风致响应高于修正前,并更接近实测结果,验证了修正模型的准确性。