Asynchronism of the spreading dynamics underlying the bursty pattern

The potential mechanisms of the spreading phenomena uncover the organizations and functions of various systems.However,due to the lack of valid data,most of early works are limited to the simulated process on model networks.In this paper,we track and analyze the propagation paths of real spreading events on two social networks:Twitter and Brightkite.The empirical analysis reveals that the spreading probability and the spreading velocity present the explosive growth within a short period,where the spreading probability measures the transferring likelihood between two neighboring nodes,and the spreading velocity is the growth rate of the information in the whole network.Besides,we observe the asynchronism between the spreading probability and the spreading velocity.To explain the interesting and abnormal issue,we introduce the time-varying spreading probability into the susceptible-infected(SI)and linear threshold(LT)models.Both the analytic and experimental results reproduce the spreading phenomenon in real networks,which deepens our understandings of spreading problems.

Asynchronism-synchronism of regional precipitation in South-to-North Water Transfer planned areas

This paper proposes a method on analyzing the asynchronism-synchronism of precipitation of different hydrological regions regarding the S-to-N water transfer areas of eastern China. The general process of the analysis includes three steps. Firstly, we created the rainfall series of the region concerned by calculating the regional average rainfall of the stations in the area with the help of the classical Thiessen Polygon method. Secondly, the standards of assessment indices for wetness or dryness are set according to Gamma distribution function with a certain probability P 37.5% or 62.5% given respectively. Finally, the frequency of nine combinations are counted as the quantitative feature of asynchronism and synchronism in three time scales, that is the yearly, seasonal and monthly scales. The asynchronism-synchronism of two region pairs has been estimated. The results show that the frequency of precipitation asynchronism in 1957–1998 is larger than the synchronism frequency for both the North China-middle and lower Yangtze River pair and for the North China-upper Hanjiang River pair. As for the synchronism phenomena, the frequency of Nd?Sd is rather low. As the combinations that are suitable for water transfers are Nd?Sw, Nn?Sw, Nd?Sn and Nn?Sn, the total frequency of these combinations for North China-middle and lower Yangtze River is 40% on an annual basis, but only 28% in spring when water shortages are most likely to occur. The total frequency of these combinations for North China-upper Hanjiang River is about 24% on an annual basis, but 35% in spring and winter. It should be noted that if future precipitation patterns are similar to that of the period 1957–1998, it is very important to change the natural character of asynchronism-synchronism by enhancing the capability of hydro-projects regulation and improving management of the water transfer project.

Effects of layer interactions on instantaneous stability of finite Stokes flows

The stability analysis of a finite Stokes layer is of practical importance in flow control. In the present work, the instantaneous stability of a finite Stokes layer with layer interactions is studied via a linear stability analysis of the frozen phases of the base flow. The oscillations of two plates can have different velocity amplitudes, initial phases, and frequencies. The effects of the Stokes-layer interactions on the stability when two plates oscillate synchronously are analyzed. The growth rates of two most unstable modes when δ < 0.12 are almost equal, and δ = δ*/h*, where δ*and h*are the Stokes-layer thickness and the half height of the channel, respectively. However, their vorticities are different. The vorticity of the most unstable mode is symmetric, while the other is asymmetric. The Stokes-layer interactions have a destabilizing effect on the most unstable mode when δ < 0.68, and have a stabilizing effect when δ > 0.68. However, the interactions always have a stabilizing effect on the other unstable mode. It is explained that one of the two unstable modes has much higher dissipation than the other one when the Stokes-layer interactions are strong. We also find that the stability of the Stokes layer is closely related to the inflectional points of the base-flow velocity profile. The effects of inconsistent velocity-amplitude, initial phase, and frequency of the oscillations on the stability are analyzed. The energy of the most unstable eigenvector is mainly distributed near the plate of higher velocity amplitude or higher oscillation frequency. The effects of the initial phase difference are complicated because the base-flow velocity is extremely sensitive to the initial phase.

Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

A Joint Activity and Data Detection Scheme for Asynchronous Grant-Free Rateless Multiple Access

This paper considers the frameasynchronous grant-free rateless multiple access(FAGF-RMA)scenario,where users can initiate access at any symbol time,using shared channel resources to transmit data to the base station.Rateless coding is introduced to enhance the reliability of the system.Previous literature has shown that FA-GFRMA can achieve lower access delay than framesynchronous grant-free rateless multiple access(FSGF-RMA),with extreme reliability enabled by rateless coding.To support FA-GF-RMA in more practical scenarios,a joint activity and data detection(JADD)scheme is proposed.Exploiting the feature of sporadic traffic,approximate message passing(AMP)is exploited for transmission signal matrix estimation.Then,to determine the packet start points,a maximum posterior probability(MAP)estimation problem is solved based on the recovered transmitted signals,leveraging the intrinsic power pattern in the codeword.An iterative power-pattern-aided AMP algorithm is devised to enhance the estimation performance of AMP.Simulation results verify that the proposed solution achieves a delay performance that is comparable to the performance limit of FA-GF-RMA.

Harmonics in the Squirrel Cage Induction Motor Analytic Calculation Part III: Influence on the Torque-speed Characteristic

The harmonics that appear in the squirrel cage asynchronous machine have been discussed in great detail in the literature for a long time. However, the systematization of the phenomenon is still pending, so we made an attempt to fill this gap in the previous parts of our study by elaborating formulas for calculation of parasitic torques. It was a general demand among those who work in this field towards the author to verify his formulas with measurements. In the literature, it seems,only one detailed, purposeful series of measurements has been published so far, the purpose of which was to investigate the effect of the number of rotor slots on the torque-speed characteristic curve of the machine. The main goal of this study is to verify the correctness of the formulas by comparing them with the referred series of measurements. Relying on this, the expected synchronous parasitic torques were developed for the frequently used rotor slot numbers-as a design guide for the engineer.Thus, together with our complete table for radial magnetic pull published in our previous work, the designer has all the principles, data and formulas available for the right number of rotor slots for his given machine and for the drive system. This brings this series of papers to an end.

Subsequent total joint arthroplasty: Are we learning from the first stage?

BACKGROUND With the increasing incidence of total joint arthroplasty(TJA),there is a desire to reduce peri-operative complications and resource utilization.As degenerative conditions progress in multiple joints,many patients undergo multiple proce-dures.AIM To determine if both physicians and patients learn from the patient’s initial arth-roplasty,resulting in improved outcomes following the second procedure.METHODS The institutional database was retrospectively queried for primary total hip arth-roplasty(THA)and total knee arthroplasty(TKA).Patients with only unilateral THA or TKA,and patients undergoing same-day bilateral TJA,were excluded.Patient demographics,comorbidities,and implant sizes were collected at the time of each procedure and patients were stratified by first vs second surgery.Outcome metrics evaluated included operative time,length of stay(LOS),disposition,90-d readmissions and emergency department(ED)visits.RESULTS A total of 642 patients,including 364 undergoing staged bilateral TKA and 278 undergoing bilateral THA,were analyzed.There was no significant difference in demographics or comorbidities between the first and second procedure,which were separated by a mean of 285 d.For THA and TKA,LOS was significantly less for the second surgery,with 66%of patients having a shorter hospitalization(P<0.001).THA patients had significantly decreased operative time only when the same sized implant was utilized(P=0.025).The vast majority(93.3%)of patients were discharged to the same type of location following their second surgery.However,when a change in disposition was present from the first surgery,patients were significantly more likely to be discharged to home after the second procedure(P=0.033).There was no difference between procedures for post-operative readmissions(P=0.438)or ED visits(P=0.915).CONCLUSION After gaining valuable experience recovering from the initial surgery,a patient’s perioperative outcomes are improved for their second TJA.This may be the result of increased confidence and decreased anxiety,and it supports the theory that enhanced patient education pre-operatively may improve outcomes.For the surgical team,the second procedure of a staged THA is more efficient,although this finding did not hold for TKA.

Review on the Usage of Synchronous and Asynchronous FIFOs in Digital Systems Design

First-Input-First-Output (FIFO) buffers are extensively used in contemporary digital processors and System-on-Chips (SoC). There are synchronous FIFOs and asycnrhonous FIFOs. And different sized FIFOs should be implemented in different ways. FIFOs are used not only for the pipeline design within a processor, for the inter-processor communication networks, for example Network-on-Chips (NoCs), but also for the peripherals and the clock domain crossing at the whole SoC level. In this paper, we review the interface, the circuit implementation, and the various usages of FIFOs in various levels of the digital design. We can find that the usage of FIFOs could greatly facilitate the signal storage, signal decoupling, signal transfer, power domain separation and power domain crossing in digital systems. We hope that more attentions are paid to the usages of synchronous and asynchronous FIFOs and more sophististicated usages are discovered by the digital design communities.

Joint Flexible Duplexing and Power Allocation with Deep Reinforcement Learning in Cell-Free Massive MIMO System

Network-assisted full duplex(NAFD)cellfree(CF)massive MIMO has drawn increasing attention in 6G evolvement.In this paper,we build an NAFD CF system in which the users and access points(APs)can flexibly select their duplex modes to increase the link spectral efficiency.Then we formulate a joint flexible duplexing and power allocation problem to balance the user fairness and system spectral efficiency.We further transform the problem into a probability optimization to accommodate the shortterm communications.In contrast with the instant performance optimization,the probability optimization belongs to a sequential decision making problem,and thus we reformulate it as a Markov Decision Process(MDP).We utilizes deep reinforcement learning(DRL)algorithm to search the solution from a large state-action space,and propose an asynchronous advantage actor-critic(A3C)-based scheme to reduce the chance of converging to the suboptimal policy.Simulation results demonstrate that the A3C-based scheme is superior to the baseline schemes in term of the complexity,accumulated log spectral efficiency,and stability.

A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

Nowadays,smart wearable devices are used widely in the Social Internet of Things(IoT),which record human physiological data in real time.To protect the data privacy of smart devices,researchers pay more attention to federated learning.Although the data leakage problem is somewhat solved,a new challenge has emerged.Asynchronous federated learning shortens the convergence time,while it has time delay and data heterogeneity problems.Both of the two problems harm the accuracy.To overcome these issues,we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems.The scheme improves the Delay Compensated Asynchronous Stochastic Gradient Descent(DC-ASGD)algorithm based on the second-order Taylor expansion as the delay compensation.It adds the FedProx operator to the objective function as the heterogeneity compensation.Besides,the proposed scheme motivates the federated learning process by adjusting the importance of the participants and the central server.We conduct multiple sets of experiments in both conventional and heterogeneous scenarios.The experimental results show that our scheme improves the accuracy by about 5%while keeping the complexity constant.We can find that our scheme converges more smoothly during training and adapts better in heterogeneous environments through numerical experiments.The proposed double-compensation-based federated learning scheme is highly accurate,flexible in terms of participants and smooth the training process.Hence it is deemed suitable for data privacy protection of smart wearable devices.

Harmonics in the Squirrel Cage Induction Motor Analytic Calculation-Part Ⅰ: Differential Leakage, Attenuation, Asynchronous Parasitic Torques

The magnetic field generated in the air gap of the cage asynchronous machine and the harmonics of the magnetomotive forces creating that magnetic field, as well as the related differential leakage, attenuation, asynchronous parasitic torques have been discussed in great detail in the literature, but always separately, for a long time. However, systematization of the phenomenon still awaits. Therefore, it is worth summarizing the completeness of the phenomena in a single study – with a new approach at the same time-in order to reveal the relationships between them. The role of rotor slot number is emphasized much more than before. An existing, commonly used, but still impractical basic figure has been modified to more clearly demonstrate the response of the rotor for the harmonics of the stator. The need to treat differential leakage, asynchronous parasitic torques and attenuation together will be demonstrated: new formula for asynchronous parasitic torque is derived;the long-used characteristic curves for differential leakage and attenuation used separately so far was merged into one, correct curve in order to provide a correct design guide for the engineers.

Matrix pencil based robust control for feedforward systems with event-triggered communications and sensor/actuator faults

In this paper we address the issue of output-feedback robust control for a class of feedforward nonlinear systems.Essentially different from the related literature,the feedback/input signals are corrupted by additive noises and can only be transmitted intermittently due to the consideration of event-triggered communications,which bring new challenges to the control design.With the aid of matrix pencil based design procedures,regulating the output to near zero is globally solved by a non-conservative dynamic low-gain controller which requires only an a priori information on the upper-bound of the growth rate of nonlinearities.Theoretical analysis shows that the closed-loop system is input-to-state stable with respect to the sampled errors and additive noise.In particular,the observer and controller designs have a dual architecture with a single dynamic scaling parameter whose update law can be obtained by calculating the generalized eigenvalues of matrix pencils offline,which has an advantage in the sense of improving the system convergence rate.

Fully asynchronous distributed optimization with linear convergence over directed networks

We study distributed optimization problems over a directed network,where nodes aim to minimize the sum of local objective functions via directed communications with neighbors.Many algorithms are designed to solve it for synchronized or randomly activated implementation,which may create deadlocks in practice.In sharp contrast,we propose a fully asynchronous push-pull gradient(APPG) algorithm,where each node updates without waiting for any other node by using possibly delayed information from neighbors.Then,we construct two novel augmented networks to analyze asynchrony and delays,and quantify its convergence rate from the worst-case point of view.Particularly,all nodes of APPG converge to the same optimal solution at a linear rate of O(λ^(k)) if local functions have Lipschitz-continuous gradients and their sum satisfies the Polyak-?ojasiewicz condition(convexity is not required),where λ ∈(0,1) is explicitly given and the virtual counter k increases by one when any node updates.Finally,the advantage of APPG over the synchronous counterpart and its linear speedup efficiency are numerically validated via a logistic regression problem.

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.

A Secure and Effective Energy-Aware Fixed-Point Quantization Scheme for Asynchronous Federated Learning

Asynchronous federated learning(AsynFL)can effectivelymitigate the impact of heterogeneity of edge nodes on joint training while satisfying participant user privacy protection and data security.However,the frequent exchange of massive data can lead to excess communication overhead between edge and central nodes regardless of whether the federated learning(FL)algorithm uses synchronous or asynchronous aggregation.Therefore,there is an urgent need for a method that can simultaneously take into account device heterogeneity and edge node energy consumption reduction.This paper proposes a novel Fixed-point Asynchronous Federated Learning(FixedAsynFL)algorithm,which could mitigate the resource consumption caused by frequent data communication while alleviating the effect of device heterogeneity.FixedAsynFL uses fixed-point quantization to compress the local and global models in AsynFL.In order to balance energy consumption and learning accuracy,this paper proposed a quantization scale selection mechanism.This paper examines the mathematical relationship between the quantization scale and energy consumption of the computation/communication process in the FixedAsynFL.Based on considering the upper bound of quantization noise,this paper optimizes the quantization scale by minimizing communication and computation consumption.This paper performs pertinent experiments on the MNIST dataset with several edge nodes of different computing efficiency.The results show that the FixedAsynFL algorithm with an 8-bit quantization can significantly reduce the communication data size by 81.3%and save the computation energy in the training phase by 74.9%without significant loss of accuracy.According to the experimental results,we can see that the proposed AsynFixedFL algorithm can effectively solve the problem of device heterogeneity and energy consumption limitation of edge nodes.

Integrated system of traditional THz time-domain spectroscopy and asynchronous optical sampling

Terahertz time-domain spectroscopy(THz-TDS)system,as a new means of spectral analysis and detection,plays an increasingly pivotal role in basic scientific research.However,owing to the long scanning time of the traditional THz-TDS system and the complex control of the asynchronous optical scanning(ASOPS)system,which requires frequent calibration,we combine traditional THz-TDS and ASOPS systems to form a composite system and propose an all-fiber trigger signal generation method based on the time overlapping interference signal generated by the collinear motion of two laser pulses.Finally,the time-domain and frequency-domain spectra are obtained by using two independent systems in the integrated systems.It is found that the full width at half maximum(FWHM)of the time-domain spectra and the spectral width of the frequency-domain spectra are almost the same,but the sampling speed of the ASOPS system is significantly faster than that of the traditional THz-TDS system,which conduces to the study of the transient characteristics of substances.

Optimizing Polynomial-Time Solutions to a Network Weighted Vertex Cover Game

Weighted vertex cover(WVC)is one of the most important combinatorial optimization problems.In this paper,we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted networks.We first model the WVC problem as a general game on weighted networks.Under the framework of a game,we newly define several cover states to describe the WVC problem.Moreover,we reveal the relationship among these cover states of the weighted network and the strict Nash equilibriums(SNEs)of the game.Then,we propose a game-based asynchronous algorithm(GAA),which can theoretically guarantee that all cover states of vertices converging in an SNE with polynomial time.Subsequently,we improve the GAA by adding 2-hop and 3-hop adjustment mechanisms,termed the improved game-based asynchronous algorithm(IGAA),in which we prove that it can obtain a better solution to the WVC problem than using a the GAA.Finally,numerical simulations demonstrate that the proposed IGAA can obtain a better approximate solution in promising computation time compared with the existing representative algorithms.

Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms.To improve the voltage stability and reactive power economy of wind farms,the improved particle swarmoptimization is used to optimize the reactive power planning in wind farms.First,the power flow of offshore wind farms is modeled,analyzed and calculated.To improve the global search ability and local optimization ability of particle swarm optimization,the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor.Taking the minimum active power loss of the offshore wind farms as the objective function,the installation location of the reactive power compensation device is compared according to the node voltage amplitude and the actual engineering needs.Finally,a reactive power optimizationmodel based on Static Var Compensator is established inMATLAB to consider the optimal compensation capacity,network loss,convergence speed and voltage amplitude enhancement effect of SVC.Comparing the compensation methods in several different locations,the compensation scheme with the best reactive power optimization effect is determined.Meanwhile,the optimization results of the standard particle swarm optimization and the improved particle swarm optimization are compared to verify the superiority of the proposed improved algorithm.

Design and implementation of control system for superconducting RSFQ circuit

The superconducting rapid single flux quantum(RSFQ)integrated circuit is a promising solu-tion for overcoming speed and power bottlenecks in high-performance computing systems in the post-Moore era.This paper presents an architecture designed to improve the speed and power limitations of high-performance computing systems using superconducting technology.Since superconducting microprocessors,which operate at cryogenic temperatures,require support from semiconductor cir-cuits,the proposed design utilizes the von Neumann architecture with a superconducting RSFQ mi-croprocessor,cryogenic semiconductor memory,a room temperature field programmable gate array(FPGA)controller,and a host computer for input/output.Additionally,the paper introduces two key circuit designs:a start/stop controllable superconducting clock generator and an asynchronous communication interface between the RSFQ and semiconductor chips used to implement the control system.Experimental results demonstrate that the proposed design is feasible and effective,provi-ding valuable insights for future superconducting computer systems.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.