Intellicise Model Transmission for Semantic Communication in Intelligence-Native 6G Networks

To facilitate emerging applications and demands of edge intelligence(EI)-empowered 6G networks,model-driven semantic communications have been proposed to reduce transmission volume by deploying artificial intelligence(AI)models that provide abilities of semantic extraction and recovery.Nevertheless,it is not feasible to preload all AI models on resource-constrained terminals.Thus,in-time model transmission becomes a crucial problem.This paper proposes an intellicise model transmission architecture to guarantee the reliable transmission of models for semantic communication.The mathematical relationship between model size and performance is formulated by employing a recognition error function supported with experimental data.We consider the characteristics of wireless channels and derive the closed-form expression of model transmission outage probability(MTOP)over the Rayleigh channel.Besides,we define the effective model accuracy(EMA)to evaluate the model transmission performance of both communication and intelligence.Then we propose a joint model selection and resource allocation(JMSRA)algorithm to maximize the average EMA of all users.Simulation results demonstrate that the average EMA of the JMSRA algorithm outperforms baseline algorithms by about 22%.

Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

Container Based Nomadic Vehicular Cloud Using Cell Transmission Model

Nomadic Vehicular Cloud(NVC)is envisaged in this work.The predo-minant aspects of NVC is,it moves along with the vehicle that initiates it and functions only with the resources of moving vehicles on the heavy traffic road without relying on any of the static infrastructure and NVC decides the initiation time of container migration using cell transmission model(CTM).Containers are used in the place of Virtual Machines(VM),as containers’features are very apt to NVC’s dynamic environment.The specifications of 5G NR V2X PC5 interface are applied to NVC,for the feature of not relying on the network coverage.Nowa-days,the peak traffic on the road and the bottlenecks due to it are inevitable,which are seen here as the benefits for VC in terms of resource availability and residual in-network time.The speed range of high-end vehicles poses the issue of dis-connectivity among VC participants,that results the container migration failure.As the entire VC participants are on the move,to maintain proximity of the containers hosted by them,estimating their movements plays a vital role.To infer the vehicle movements on the road stretch and initiate the container migration prior enough to avoid the migration failure due to vehicles dynamicity,this paper proposes to apply the CTM to the container based and 5G NR V2X enabled NVC.The simulation results show that there is a significant increase in the success rate of vehicular cloud in terms of successful container migrations.

Global Dynamics Analysis of a Cholera Transmission Model with General Incidence and Multiple Modes of Infection

This paper develops an SIBR cholera transmission model with general incidence rate. Necessary and sufficient conditions for local and global asymptotic stability of the equilibria are established by Routh Hurwitz criterium, Lyapunov function, and the second additive composite matrix theorem. What is more, exploiting the DED is cover simulation tool, the parameter values of the model are estimated with the 1998-2021 cholera case data in China. Finally, we perform sensitivity analysis for the basic reproduction number to seek for effective interventions for cholera control. .

Transmission Line Modelling of Geomagnetic Induction in the Ocean/Earth Conductivity Structure

During geomagnetic disturbances, electric fields induced in the Earth and in power systems, pipelines and submarine cables can interfere with the operation of these systems. Calculations for submarine cables are complicated by the need to consider not just the induction directly into the cable but also the earth potentials produced at the coast at each end of the cable. To determine the coast potentials, we present a new model of the ocean and earth conductivity structure that spans the whole length of a cable from one coast to another. Calculations are based on the generalised thin sheet approach introduced by Ranganayaki and Madden but converted to a transmission line model that can be solved using standard circuit theory techniques. It is shown how the transmission line model can be used to calculate the earth potential profile from one side of an ocean or sea to the other. Example calculations are presented for a shallow sea, a shallow ocean, and a deep ocean that are simplified approximations to the North Sea, Tasman Sea and Pacific Ocean and show that the peak potentials occur at the coast. An examination is also made of how the width of a shallow sea and the width of the continental shelf affect these coast potentials. The modelling technique and example results provide a guide for more detailed modelling of geomagnetic induction along the routes of specific submarine cables.

A novel conditional cell transmission model for oversaturated arterials

The objective of this work is to develop a novel feature for traffic flow models, when traffic queues on two-way arterials periodically extend until then they block an upstream signal in oversaturated conditions. The new model, proposed as conditional cell transmission model （CCTM） has been developed with two improvements. First, cell transmission model （CTM） is expanded for two-way arterials by taking account of all diverging and merging activities at intersections. Second, a conditional cell is added to simulate periodic spillback and blockages at an intersection. The results of experiments for a multilane, two-way, three-signal sample network demonstrate that CCTM can accommodate various traffic demands and accurate representation of blockages at intersections. The delay of left turns is underestimated by 40 % in moderate conditions and by 58% in oversamrated condition when using the CTM rather than CCTM. Finally, the consistency between HCS 2000 and CCTM shows that CCTM is a reliable methodology of modeling traffic flow in oversaturated condition.

Sensitivity analysis of key input parameters in conditional cell transmission model for oversaturated arterials

A novel conditional cell transmission model （CCTM） is a potential simulation tool because it accommodates all traffic conditions from light condition to oversaturated condition. To test the performance of the CCTM, a series of experiments for sensitivity analysis were designed and performed for a multilane, two-way, three-signal sample network. Experiment 1 shows that the model is performed in a logical and expected manner with variations in traffic demand with time and direction. Experiment 2 shows when the possibility of the occurrence of a useful gap increases to 60% and 100%, the delays in left rams decrease by 5% and 15%, respectively. In Experiment 3, comparing the possibility of a conditional cell of 0 with 100%, delay of left turn and delay of the entire network were underestimated by 58% and 11%, respectively. Hence, sensitivity analysis demonstrates that by reflecting local drivers＇ behaviors properly, the CCTM provides an accurate representation of traffic flow in simulating oversaturated traffic conditions.

Chloride Ion Transmission Model under the Drying-wetting Cycles and Its Solution

The chloride ion transmission model considering diffusion and convection was established respectively for different zones in concrete by analyzing chloride ion transmission mechanism under the dryingwetting cycles. The finite difference method was adopted to solve the model. The equation of chloride ion transmission model in the convection and diffusion zone of concrete was discreted by the group explicit scheme with right single point （GER method） and the equation in diffusion zone was discreted by FTCS difference scheme. According to relative humidity characteristics in concrete under drying-wetting cycles, the seepage velocity equation was formulated based on Kelvin Equation and Darcy＇s Law. The time-variant equations of chloride ion concentration of concrete surface and the boundary surface of the convection and diffusion zone were established. Based on the software MATLAB the numerical calculation was carried out by using the model and basic material parameters from the experiments. The calculation of chloride ion concentration distribution in concrete is in good agreement with the drying-wetting cycles experiments. It can be shown that the chloride ion transmission model and the seepage velocity equation are reasonable and practical. Studies have shown that the chloride ion transmission in concrete considering convection and diffusion under the drying-wetting cycles is the better correlation with the actual situation than that only considering the diffusion.

Cell transmission model based traffic signal timing in oversaturated conditions

In order to investigate enhancements to cell transmission model (CTM) as a tool for traffic signal timing in oversaturated conditions, randomly distributed saturation flow rates and arrival rates were used instead of constant values to simulate traffic flow movement, estimate the average delay of the network and search for an optimal traffic signal timing plan. A case study was given to demonstrate that the proposed methodology can capture unique phenomena in oversaturated conditions such as forward wave, spillback and lane entrance blockage. The results show that CTM underestimates travel time by 25% when compared to Simtraffic, while the enhanced CTM underestimates by only 3%. A second case study shows that a dynamic signal timing plan is superior to a fixed signal timing plan in the term of average delay.

A Learning-Based Channel Model for Synergetic Transmission Technology

It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily.

A Theoretical Model for the Asymmetric Transmission of Powerful Acoustic Wave in Double-Layer Liquids

A theoretical model which couples the oscillation of cavitation bubbles with the equation of an acoustic wave is utilized to describe the sound fields in double-layer liquids, which can be used to realize the asymmetric transmission of acoustic waves. Numerical simulations show that the asymmetry is related to the properties of the host liquids and the input acoustic wave. Asymmetry can be enhanced if the maximum number density or the ambient radius of the cavitation bubbles in the low cavitation threshold liquid increases. Moreover, the direction of rectification will be reversed if the amplitude of the input acoustic wave becomes high enough.

Transmission Capacity Analysis for Linear VANET under Physical Model

In this study, the transmission capacity of VANETs in a highway scenario is analysed on the basis of a 1D line model and the carrier sense multiple access with collision avoidance(CSMA/CA) protocol. We describe the CSMA/CA protocol used in IEEE802.11 p from the perspective of the geometric relationship amongst simultaneous transmitters. The desired channel and interfering channels are assumed to experience the same amount of path-loss and Rayleigh fading. On the basis of the proposed model, we analyse the attempted transmission probability of each road segment and the maximum intensity of active transmitters, including their theoretical values. Then, we employ the physical model to obtain the outage probability and derive the upper bound of the transmission capacity of a VANET, which is defined as the average spatial density of successful transmissions in the network. Simulation results indicate that the theoretical value offers a good bound on network capacity.

MODELING, VALIDATION AND OPTIMAL DESIGN OF THE CLAMPING FORCE CONTROL VALVE USED IN CONTINUOUSLY VARIABLE TRANSMISSION

Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.

Minimization of Electric Power Losses on 132 kV and 220 kV Uganda Electricity Transmission Lines

The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.

Valuation and comparison of the actual and optimal control strategy in an emerging infectious disease:Implication from a COVID-19 transmission model

To effectively combat emerging infectious diseases like COVID-19,it is crucial to adopt strict prevention and control measures promptly to effectively contain the spread of the epidemic.In this paper,we propose a transmission model to investigate the influence of two control strategies:reducing contact numbers and improving medical resources.We examine these strategies in terms of constant control and time-varying control.Through sensitivity analysis on two reproduction numbers of the model with constant control,we demonstrate that reducing contact numbers is more effective than improving medical resources.Furthermore,these two constant controls significantly influence the peak values and timing of infections.Specifically,intensifying control measures can reduce peak values,albeit at the expense of delaying the peak time.In the model with time-varying control,we initially explore the corresponding optimal control problem and derive the characteristic expression of optimal control.Subsequently,we utilize real data from January 10th to April 12th,2020,in Wuhan city as a case study to perform parameter estimation by using our proposed improved algorithm.Our findings illustrate that implementing optimal control measures can effectively reduce infections and deaths,and shorten the duration of the epidemic.Then,we numerically explore that implementing control measures promptly and increasing intensity to reduce contact numbers can make actual control be more closer to optimized control.Finally,we utilize the real data from October 31st to November 18th,2021,in Hebei province as a second case study to validate the feasibility of our proposed suggestions.

Schistosomiasis transmission in Zimbabwe:Modelling based on machine learning

Zimbabwe,located in Southern Africa,faces a significant public health challenge due to schistosomiasis.We investigated this issue with emphasis on risk prediction of schistosomiasis for the entire population.To this end,we reviewed available data on schistosomiasis in Zimbabwe from a literature search covering the 1980-2022 period considering the potential impact of 26 environmental and socioeconomic variables obtained from public sources.We studied the population requiring praziquantel with regard to whether or not mass drug administration(MDA)had been regularly applied.Three machinelearning algorithms were tested for their ability to predict the prevalence of schistosomiasis in Zimbabwe based on the mean absolute error(MAE),the root mean squared error(RMSE)and the coefficient of determination(R2).The findings revealed different roles of the 26 factors with respect to transmission and there were particular variations between Schistosoma haematobium and S.mansoni infections.We found that the top-five correlation factors,such as the past(rather than current)time,unsettled MDA implementation,constrained economy,high rainfall during the warmest season,and high annual precipitation were closely associated with higher S.haematobium prevalence,while lower elevation,high rainfall during the warmest season,steeper slope,past(rather than current)time,and higher minimum temperature in the coldest month were rather related to higher S.mansoni prevalence.The random forest(RF)algorithm was considered as the formal best model construction method,with MAE=0.108;RMSE=0.143;and R^(2)=0.517 for S.haematobium,and with the corresponding figures for S.mansoni being 0.053;0.082;and 0.458.Based on this optimal model,the current total schistosomiasis prevalence in Zimbabwe under MDA implementation was 19.8%,with that of S.haematobium at 13.8% and that of S.mansoni at 7.1%,requiring annual MDA based on a population of 3,003,928.Without MDA,the current total schistosomiasis prevalence would be 23.2%,that of S.haematobium 17.1% and that of S.mansoni prevalence at 7.4%,requiring annual MDA based on a population of 3,521,466.The study reveals that MDA alone is insufficient for schistosomiasis elimination,especially that due to S.mansoni.This study predicts a moderate prevalence of schistosomiasis in Zimbabwe,with its elimination requiring comprehensive control measures beyond the currently used strategies,including health education,snail control,population surveillance and environmental management.

Proactive Resilience Enhancement of Power Systems with Link Transmission Model-based Dynamic Traffic Assignment Among Electric Vehicles

The rapid development of electric vehicles(EVs)is strengthening the bi-directional interactions between electric power networks(EPNs)and transportation networks(TNs)while providing opportunities to enhance the resilience of power systems towards extreme events.To quantify the temporal and spatial flexibility of EVs for charging and discharging,a novel dynamic traffic assignment(DTA)problem is proposed.The DTA problem is based on a link transmission model(LTM)with extended charging links,depicting the interaction between EVs and power systems.It models the charging rates as continuous variables by an energy boundary model.To consider the evacuation requirements of TNs and the uncertainties of traffic conditions,the DTA problem is extended to a two-stage distributionally robust version.It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs.The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers.Case studies are performed on two test networks.The effectiveness is verified by the numerical results,e.g.,reducing the load shedding amount without increasing the unmet traffic demand.

Effect of air breakdown on microwave pulse energy transmission

The energy transmission of the long microwave pulse for the frequency of 2.45 GHz and 5.8 GHz is studied by using the electron fluid model, where the rate coefficients are deduced from the Boltzmann equation solver named BOLSIG＋. The breakdown thresholds for different air pressures and incident pulse parameters are predicted, which show good agreement with the experimental data. Below the breakdown threshold, the transmitted pulse energy is proportional to the square of the incident electric field amplitude. When the incident electric field amplitude higher than the breakdown threshold increases,the transmitted pulse energy decreases monotonously at a high air pressure, while at a low air pressure it first decreases and then increases. We also compare the pulse energy transmission for the frequency of 2.45 GHz with the case of 5.8 GHz.

Assessing high-energy x-ray and proton irradiation effects on electrical properties of P-GaN and N-GaN thin films

The effects of ionizing and displacement irradiation of high-energy x-ray and 2-MeV proton on GaN thin films were investigated and compared in this study.The electrical properties of both P-GaN and N-GaN,separated from power devices,were gauged for fundamental analysis.It was found that the electrical properties of P-GaN were improved as a consequence of the disruption of the Mg-H bond induced by high-dose x-ray irradiation,as indicated by the Hall and circular transmission line model.Specifically,under a 100-Mrad(Si)x-ray dose,the specific contact resistance pc of P-GaN decreased by 30%,and the hole carrier concentration increased significantly.Additionally,the atom displacement damage effect of a 2-MeV proton of 1×10^(13)p/cm^(2)led to a significant degradation of the electrical properties of P-GaN,while those of N-GaN remained unchanged.P-GaN was found to be more sensitive to irradiation than N-GaN thin film.The effectiveness of x-ray irradiation in enhancing the electrical properties of P-GaN thin films was demonstrated in this study.

应急状态下新冠流行曲线预测的方法学研究——基于北京市百度搜索和传统流感样病例监测

Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore new surveillance methods.This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness(ILI)surveillance.A novel hybrid model(multiattention bidirectional gated recurrent unit(MABG)-susceptible-exposed-infected-removed(SEIR))was developed,which leveraged a deep learning algorithm(MABG)to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever,pyrexia,cough,sore throat,anti-fever medicine,and runny nose.By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019(COVID-19)cases,a transmission dynamics model(SEIR)was formulated to estimate the transmission dynamics and epidemic curve of SARS-Co V-2.During the COVID-19 pandemic,when conventional surveillance measures have been suspended temporarily,cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19.In the specific case of Beijing,it has been ascertained that cumulative infection attack rate surpass 80.25%(95%confidence interval(95%CI):77.51%-82.99%)since December 17,2022,with the apex of the outbreak projected to transpire on December 12.The culmination of existing patients is expected to occur three days subsequent to this peak.Effective reproduction number(Rt)represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic,remained below 1 since December 17,2022.The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support.Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks.Syndrome surveillance on COVID-19 should be established to following on the epidemic,clinical severity,and medical resource demand.